METHOD FOR PREDICTING AND MODELING ANTI-PSYCHOTIC ACTIVITY USING VIRTUAL SCREENING MODEL

FIELD OF THE INVENTION

The present invention relates to a method for predicting and modeling anti-psychotic activity using virtual screening model.

The present invention further relates to molecular modeling and drug design by quantitative structure activity relationship (QSAR) and molecular docking studies to explore the anti-psychotic compound from derivatives of plant molecules.

BACKGROUND AND PRIOR ART OF THE INVENTION

Psychosis is one of the most dreaded disease of the 20^thcentury and spreading further with continuance and increasing incidences in 21^stcentury. Psychosis means abnormal condition of the mind. People suffering from psychosis are said to be psychotic. A wide variety of central nervous system diseases, from both external toxins, and from internal physiologic illness, can produce symptoms of psychosis. It is considered as an adversary of modernization and advanced pattern of socio-cultured life dominated by western medicine. Multidisciplinary scientific investigations are making best efforts to combat this disease, but the sure-shot perfect cure is yet to be brought in to world of medicine.

References may be made to patent application PCT/IN2010/000208, wherein Srivastava et. al. reported antipsychotic activity of some yohimbine group of alkaloids and here they wish to report virtual screening model for predicting antipsychotic activity. An explanation of conventional drug discovery processes and their limitations is useful for understanding the present invention.

Discovering a new drug to treat or cure some biological condition, is a lengthy and expensive process, typically taking on average 12 years and $800 million per drug, and taking possibly up to 15 years or more and $1 billion to complete in some cases. The process may include wet lab testing/experiments, various biochemical and cell-based assays, animal models, and also computational modeling in the form of computational tools in order to identify, assess, and optimize potential chemical compounds that either serve as drugs themselves or as precursors to eventual drug molecules. In order to avoid unnecessary animal scarifies in animal testing for drug discovery it is the need of hour to switch to virtual screening. Apart from saving animal life, cost, and time this is very fast, reliable and has become one of the essential component of modern drug discovery.

The first goal of a drug discovery process is to identify and characterize a chemical compound or ligand, i.e., binder, biomolecule, that affects the function of one or more other biomolecules (i.e., a drug “target”) in an organism, usually a receptor, via a potential molecular interaction or combination. Herein the term receptor refers to anti-psychotic receptors dopamine D2 and Seratonin (5HT_2A) and the term biomolecule refers to a chemical entity that comprises one or more of a organic chemical compound, including, but not limited to, synthetic, medicinal, drug-like, or natural compounds, or any portions or fragments thereof.

Prior to this invention, there have been no systematic methods for precisely and effectively predicting antipsychotic activity of organic compounds and their derivatives on a computer based bioassay system.

OBJECTIVE OF THE INVENTION

Main objective of the present invention is to provide a method for predicting and modeling anti-psychotic activity using virtual screening model.

Another objective of the present invention is to provide pharmaceutical composition comprising of an antipsychotic agents in an amount effective to control psychosis.

Yet another objective of the present invention is to provide the yohimbine derivatives exhibit antipsychotic activity against dopaminergic-D₂and Serotonergic (5HT_2A) receptors as well as amphetamine induced hyperactive mouse model.

Yet another objective of the present invention is to provide a process for the preparation of yohimbine derivatives.

SUMMARY OF THE INVENTION

Accordingly, the present invention provides a computer aided method for predicting and modeling anti-psychotic activity of a test compound wherein the said method comprising:

- i. validating training set descriptors comprising chemical and structural information of the known antipsychotic drugs/compounds through quantitative structure activity relationship (QSAR) model using the equation: Predicted log IC₅₀(nM)=−0.124236×M+0.0305374×P+1.0651×V−0.0639271×AH−0.380434×AO+9.12642 Where in, M=Dipole Vector Z (debye), P=Steric Energy (kcal/mole), V=Group Count (ether) (V), AH=Molar Refractivity and AO=Shape Index (basic kappa, order 3) in a computational modeling system.
- ii. providing training set descriptors comprising chemical and structural information of the training set compounds and experimental antipsychotic activity against selective antipsychotic targets to the computational modeling system of step (i) and obtaining virtual antipsychotic activity value (Log IC₅₀) of the test (known) and untested (unknown) compounds.
- iii. performing molecular docking studies of the unknown novel compounds exhibiting anti psychotic activity as evaluated in step (ii) against antipsychotic targets using the computational modeling system of step (i).
- iv. evaluating toxicity risk and physicochemical properties of the untested (unknown) compounds as evaluated in step (ii) using the computational modeling system of step (i).
- v. evaluating oral bioavailability, absorption, distribution, metabolism and excretion (ADME) values of the untested (unknown) compounds evaluated in step (ii) using the computational modeling system of step (i) for drug likeness.
- vi. outputting the values obtained in step (ii) to (v) to a computer recordable medium to predict anti-psychotically active untested compound.

In an embodiment of the present invention, the test compounds are selected from the group consisting of formula 1, formula 2, formula 3, formula 4 or formula 5

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wherein R1 in formula 1=COOCH3(methyl ester);

R2 in formula 1 is selected from the group consisting of H, OH, OCH3, OCH2CH2CH3,

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R3 in formula 1 is selected from the group consisting of H, OCO(CH2)10CH3, OCO(CH2)14CH3, OCO(CH)(CH3)3,

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Wherein R₁in formula 2 is selected from the group consisting of

- —COOH, —COO—CH₃, —CO—NH—CH₂—(CH₂)₆—CH₃, —CO—NH—CH₂—CH₂—CH₃, —COO—CH₂—(CH₂)₄—CH₃, —COO—CH₂—CH₂—CH₂—CH₃, —COO—CH₂—CH₂—CH₂—CH₂—CH₃, —COO—CH—(CH₃)₃, —CO—NH—CH₂—COOH —CO—NH—CH₂—CH₂—OCOCH₃, —CO—NH—CH₂—CH₂—OH, —CO—NH—CH₂—COO—CH₃, —CONH—CH₂—COO—CH₃, —CONH—CH₂—COOH, —CONH—CH₂—CH₂—OCOCH₃, —CONH—CH₂—CH₂—OH

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R₂in formula 2 is selected from the group consisting of

- —OH, —OCOCH₃, —OCOCH₂CH₃, —O—CH₂—CH₂—CO—Cl, —OCO—CH₂—(CH₂)₉—CH₃, —OCO—CH₂—(CH₂)₁₃—CH₃, —OCO—CH—(CH₃)₃, —OCO—COO—CH₂—CH₃, —OCO—CO—OH, —OCO—CH₂—CH₂—CH₂—CH₃, —OCO—CH₂—CH₂—CH₂—CH₂—CH₃, —OCO—CH₂—CH₂—CH₂—COOH, —OCO—CH₂—CH₂—CH₂—CH₂—NH₂, —OCO—CH₂—CH₂—SH, —OCO—CH₂—CH₂—COOH, —OCO—CH₂—CH₂—CONH₂, —OCO—CH₂—(CH₂)₄—NH₂, —OCO—CH₂—CH₂—CH₂—S—CH₃, —OCO—CH₂—CH₂—OCO—CH₃, —OCO—CH₂—CH₂—OH, —OCO—CH₂—COO—CH₃,

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Wherein R₁in formula 3 is selected from the group consisting of

- —COOCH₃, —COOH, —CO—NH—CH₂—(CH₂)₆—CH₃, —CO—NH—CH₂—CH₂—CH₃, —COO—CH₂—(CH₂)₄—CH₃, —COO—CH₂—CH₂—CH₂—CH₃, —COO—CH₂—CH₂—CH₂—CH₂—CH₃, —COO—CH—(CH₃)₃, —CO—NH—CH₂—COOH, —CO—NH—CH₂—CH₂—OCOCH₃, —CO—NH—CH₂—CH₂—OH, —CO—NH—CH₂—COO—CH₃,

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wherein R₂in formula 3 is selected from the group consisting of

- —OH, —OCH₃, —OCO—CH₂—(CH₂)₉—CH₃, —OCO—CH₂—(CH₂)₁₂—CH₃, —OCO—CH—(CH₃)₃, —OCO—CH₂—CH₂—CH₃,

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wherein R₃in formula 3 is selected from the group consisting of

- —OH, —OCH₃, —OCO—CH₂—(CH₂)₉—CH₃, —OCO—CH₂—(CH₂)₁₃—CH₃, —OCO—CH—(CH₃)₃—OCO—CH₂—CH₂—CH₃,

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wherein R1 in formulae 4 and 5 is selected from the group consisting of

- —COOCH₃, —COOH, —CO—NH—CH₂—(CH₂)₆—CH₃, —CO—NH—CH₂—CH₂—CH₃, —COO—CH₂—(CH₂)₄—CH₃, —COO—CH₂—CH₂—CH₂—CH₃, —COO—CH₂—CH₂—CH₂—CH₂—CH₃, —COO—CH—(CH₃)₃, —CO—NH—CH₂—COOH, —CO—NH—CH₂—CH₂—OCOCH₃, —CO—NH—CH₂—CH₂—OH, —CO—NH—CH₂—COO—CH₃,

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wherein R2 in formulae 4 and 5 is selected from the group consisting of

- —OH, —OCH₃, —OCO—CH₂—CH₂—CH₃, —OCO—CH₂—(CH₂)₉—CH₃, —OCO—CH₂—(CH₂)₁₃—CH₃, —OCO—CH—(CH₃)₃,

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Yet another embodiment of the invention provides a compound of general formula 1 predicted and tested for antipsychotic activity by the method of the present invention is representated by:

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wherein R1=COOCH3(methyl ester);

R2=H, OH, OCH3, OCH2CH2CH3,

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R3=H, OCO(CH2)10CH3, OCO(CH2)14CH3, OCO(CH)(CH3)3,

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In yet another embodiment of the present invention, the predicted log(nM) IC₅₀value of the compounds of general formula 1 is in the range of 3.154 to 4.589 showing antipsychotic activity and drug likeness similar to Clozapine.

In yet another embodiment of the present invention, training sets descriptors are selected from the group consisting of atom Count (all atoms), Bond Count (all bonds), Formal Charge, Conformation Minimum Energy (kcal/mole), Connectivity Index (order 0, standard), Dipole Moment (debye), Dipole Vector (debye), Electron Affinity (eV), Dielectric Energy (kcal/mole), Steric Energy (kcal/mole), Total Energy (Hartree), Group Count (aldehyde), Heat of Formation (kcal/mole), highest occupied molecular orbital (HOMO) Energy (eV), Ionization Potential (eV), Lambda Max Visible (nm), Lambda Max UV-Visible (nm), Log PLUMO Energy (eV), Molar Refractivity, Molecular Weight Polarizability, Ring Count (all rings), Size of Smallest Ring, Size of Largest Ring, Shape Index (basic kappa, order 1) and Solvent Accessibility Surface Area (angstrom square). In yet another embodiment of the present invention, known antipsychotic drugs are selected from the group consisting of Bepridil, Cisapride, Citalopram, Desipramine, Dolasetron, Droperidol, E-4031, Flecainide, Fluoxetine, Granisetron, Haloperidol, Imipramine, Mesoridazine, Prazosin, Quetiapine, Risperidone, Gatifloxacin, Terazosin, Thioridazine, Vesnarinone, Mefloquine, Sparfloxacin, Ziprasidone, Norastemizole, Tamsulosinc levofloxacin, Moxifloxacin, Cocaine, Clozapine, Doxazosin.

In yet another embodiment of the present invention, antipsychotic targets are selected from Dopamine D2 and Serotonin (5HT_2A) receptors.

In yet another embodiment of the present invention, the risk assessment includes mutagenicity, tumorogenicity, irritation and reproductive toxicity.

In yet another embodiment of the present invention, physiochemical properties are ClogP, solubility, drug likeness and drug score.

In yet another embodiment of the present invention, test compounds show >60% inhibition in amphetamine induced hyperactivity mice model at 25 mg/kg.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1: Multiple linear regression plot for yohimbine alkaloid derivatives showing comparison of QSAR model based predicted and experimental antipsychotic activities.

FIG. 2: Antipsychotic activity of isolated yohimbine alkaloids (K001 to K006) from the leaves of Rauwolfia tetraphylla.

FIG. 3: In-vitro antipsychotic activity of semi-synthetic derivatives (K001A to K001G) of α yohimbine wherein values are mean of three assays in each case.

FIG. 4: In-vivo antipsychotic activity of semi-synthetic derivatives (K001A to K001G) of α-yohimbine wherein values are mean of five animals in each group. % Inhibition calculated with respect to amphetamine induced hyperactivity and no EPS observed at any of the dose.

FIG. 5: In-vitro antipsychotic activity of semi-synthetic derivatives of α-yohimbine (K001A, K001C and K001F) at 12 to 100 μg concentrations.

FIG. 6: In-vivo antipsychotic activity of semi-synthetic derivatives of α-yohimbine (K001A, K001C and K001F) at 6.25 to 12.5 mg/kg concentrations.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides a computer aided method for predicting and modeling anti-psychotic activity of a test compound using virtual screening model. Molecular modeling and drug design to explore the anti-psychotic compound from derivatives of plant molecules, a quantitative structure activity relationship (QSAR) and molecular docking studies were performed. Theoretical results are in accord with the in vivo experimental data. Anti-psychotic activity was predicted through QSAR model developed by forward stepwise method of multiple linear regression using leave-one-out validation approach. Relationship correlating measure i.e., regression coefficient (r²) of developed QSAR model was 0.87 and predictive accuracy was 81%, refer by cross validation coefficient (rCV²=0.81). QSAR studies indicate that dipole vector Z (debye), steric energy (kcal/mole), ether group count, molar refractivity and shape index (basic kappa, order 3) correlates well with biological activity. Dipole vector, molar refractivity and shape index showed negative correlation with activity, while steric energy and ether group count showed positive. All the active derivatives showed compliance with Lipinski's rule of five for oral bioavailability and toxicity risk assessment parameters namely, mutagenicity, tumorogenicity, irritation and reproductive toxicity. Molecular docking studies also showed strong binding affinity to anti-psychotic receptors e.g., D2 dopamine and serotonin (5HT_2A) receptors.

For the development of a virtual screening prediction model for antipsychotic activity, potential anti-psychotic compounds are screened out from the library of plant molecules and their derivatives through quantitative structure activity relationship (QSAR), molecular docking and in silico ADMET studies. On the basis of binding affinity (docking score) possible anti-psychotic receptors were proposed as potential drug targets. For activity prediction, a multiple linear regression analysis based QSAR model was developed which successfully establishes the anti-psychotic activity of selected derivatives in accord with the experimental data. QSAR model also furnishes the activity dependent chemical descriptors and predicted the inhibitory concentration (IC₅₀) of derivatives to suggest the possible toxicity range. Relationship correlating measure for QSAR model was indicated by regression coefficient (r²), which was 0.87 and prediction accuracy of developed QSAR model referred by cross validation coefficient (rCV²) which was 0.81. Active derivatives followed the standard computational pharmacokinetic parameters (ADMET) of drug likeness and oral bioavailability. QSAR study indicate that dipole vector Z (debye), steric energy (kcal/mole), ether group count, molar refractivity and shape index (basic kappa, order 3) correlates well with anti-psychotic activity. All the active derivatives showed compliance with Lipinski's rule of five for oral bioavailability. Neurotransmitter such as dopamine-D₂and Serotonin (5HT_2A) are significantly, involved in psychotic behavior (Creese I, et al., 1976). Hence forth effect of test samples of yohimbine alkaloids and their semi-synthetic derivatives were tested on these two receptors using molecular docking experiment with the help of available crystal structure or homology model to further support the molecular interaction. Docking study also showed strong binding affinity to anti-psychotic receptors e.g., D2 dopamine receptor (PDB: 2HLB) and Serotonin (5HT_2A) (no crystal structure available, thus developed homology based 3D model) receptor. Finally, predicted results were correlated with in vitro and in vivo experimental data which were in complete agreement with the theoretical results.

This virtual screening and antipsychotic activity prediction model may be of immense importance in understanding mechanism and directing the molecular design of lead compound with improved anti-psychotic activity.

Present invention provides pharmaceutical usefulness of antipsychotic agents in an amount effective to control psychosis.

Present invention provides experimental support that yohimbine derivatives exhibit antipsychotic activity against dopaminergic-D₂and Serotonergic (5HT_2A) receptors as well as amphetamine induced hyperactive mouse model. 25 mg/kg concentrations of 17-O-acetyl-α-yohimbine (K001A) and 17-O-(3″)-nitrobenzoyl-α-yohimbine (K001C) showed >72% inhibition in amphetamine induced hyperactivity mice model.

Development of predictive QSAR model as a virtual screening tool for in vitro antipsychotic activity has also been described.

Virtual screening method for prediction of antipsychotic activity typically consists of following sub-steps:

1. Development of Quantitative Structure Activity Relationship (QSAR) Based Model

- i. Preparing training set of known antipsychotic drugs. (Table 34)
- ii. Calculations of chemical structural descriptors.
- iii. Multiple linear regression statistical analysis using forward stepwise validation approach.
- iv. Development of predictive QSAR models indicated in the form of derived multiple linear regression equations.
- v. Selection of statistically validated (high r²and rCV²) best predictive QSAR model for antipsychotic activity of Yohimbine derivatives.
- vi. Evaluation of selected QSAR model for predictive accuracy by using Test data set (known antipsychotic compounds not included in Training set). (Table 31)
- vii. Prediction of in vitro antipsychotic activity of known, unknown and novel compounds and their derivatives through developed QSAR model.

2. Virtual Screening for Target Binding Affinity Through Molecular Docking

- viii. Molecular docking study of active molecules predicted through developed QSAR model against human antipsychotic targets e.g. Dopamine D2 and Serotonin (5HT_2A) receptors.
- 3. Virtual Screening for ADME and Toxicity Risk Assessment
- ix. Evaluation of ADME properties of predicted active molecules for oral bioavailability and drug likeness.
- x. Toxicity risk assessment evaluation of active molecules predicted through developed QSAR model.

Example-1
Molecular Modeling, Energy Minimization and Docking

The molecular structures of yohimbine derivatives were constructed through Scigress Explorer v7.7.0.47 (formerly CaChe) (Fujitsu). The optimization of the cleaned molecules was done through MO-G computational application that computes and minimizes an energy related to the heat of formation. The MO-G computational application solves the Schrodinger equation for the best molecular orbital and geometry of the ligand molecules. The augmented Molecular Mechanics (MM2/MM3) parameter was used for optimizing the molecules up to its lowest stable energy state. This energy minimization is done until the energy change is less than 0.001 kcal/mol or else the molecules get updated almost 300 times. However, the chemical structures of known drugs were retrieved through the PubChem database of NCBI server, USA (www.pubchem.ncbi.nlm.nih.gov). Crystallographic 3D structures of target proteins were retrieved through Brookhaven protein/ligand databank (www.pdb.org). The valency and hydrogen bonding of the ligands as well as target proteins were subsequently satisfied through the Workspace module of Scigress Explorer software. Hydrogen atoms were added to protein targets for correct ionization and tautomeric states of amino acid residues such as His, Asp, Ser and Glu etc. Molecular docking of the drugs and the active derivatives with the anti-psychotic receptors was performed by using the Fast-Dock-Manager and Fast-Dock-Compute engines available with the Scigress Explorer. For automated docking of ligands into the active sites we used genetic algorithm with a fast and simplified Potential of Mean Force (PMF) scoring scheme (Muegge I., 2000; Martin C., 1999). PMF uses atom types which are similar to the empirical force-field's used in Mechanics and Dynamics. A minimization is performed by the Fast-Dock engine which uses a Lamarkian Genetic Algorithm (LGA) so that individuals adapt to the surrounding environment. The best fits are sustained through analyzing the PMF scores of each chromosome and assigning more reproductive opportunities to the chromosomes having lower scores. This process repeats for almost 3000 generations with 500 individuals and 100,000 energy evaluations. Other parameters were left to their default values. Structure based screening involves docking of candidate ligands into protein targets, followed by applying a PMF scoring function to estimate the likelihood that ligand will bind to the protein with high affinity or not (Martin C., 1999; Sanda et al., 2008).

Example-2
Selection of Chemical Descriptors for QSAR Modeling

Quantitative structure-activity relationship (QSAR) analysis is a mathematical procedure by which chemical structures of molecules is quantitatively correlated with a well defined parameter, such as biological activity or chemical reactivity. For example, biological activity can be expressed quantitatively as in the concentration of a substance required to give a certain biological response. Additionally, when physicochemical properties or structures are expressed by numbers, one can form a mathematical relationship or QSAR, between the two. The mathematical expression can then be used to predict the biological response of other chemical structures (Yadav et al., 2010). Before the novel compounds could be used as potential drugs, the prediction of toxicity/activity ensures the calculation of risk factor associated with the administration of that particular compound/drug. A QSAR model ultimately helps in predicting these important parameters e.g., IC₅₀or ED₅₀values. For identifying the anti-psychotic activity of the derivatives, QSAR study was performed. A total of 39 chemical descriptors and training data set of 30 anti-psychotic & other CNS (central nervous system) related drugs/compounds with activity were used for development of QSAR model. Inhibitory concentration (IC₅₀) was considered as the biological (antipsychotic) activity parameter of the compounds. Forward stepwise multiple linear regression mathematical expression was then used to predict the biological response of other derivatives.

Example-3
In Silico Screening: Compliance with Pharmacokinetic Properties (ADMET)

The ideal oral drug is one that is rapidly and completely absorbed from the gastrointestinal track, distributed specifically to its site of action in the body, metabolized in a way that does not instantly remove its activity, and eliminated in a suitable manner, without causing any harm. It is reported that around half of all drugs in development fail to make it to the market because of poor pharmacokinetic (PK) (Hodgson, 2001). The PK properties depend on the chemical properties of the molecule. PK properties such as absorption, distribution, metabolism, excretion and toxicity (ADMET) are important in order to determine the success of the compound for human therapeutic use (Voet & Voet, 2004; Ekins et al., 2005; Norinder & Bergstrom, 2006). Polar surface area considered as a primary determinant of fraction absorption (Stenberg et al., 2001). Low molecular weight of compound has been considered for oral absorption (Van de Waterbeemd et al., 2001). The distribution of the compound in the human body depends on factors such as blood-brain barrier (BBB), permeability, volume of distribution and plasma protein binding (Reichel & Begley, 1998), thus these parameters have been calculated for studied compounds. The octanol-water partition coefficient (LogP) has been implicated in the BBB penetration and permeability prediction, and so is the polar surface area (Pajouhesh & Lenz, 2005). It has been reported that excretion process which eliminates the compound from human body depends on the molecular weight and octanol-water partition coefficient (Lombardo et al., 2003). Rapid renal clearance is associated with small and hydrophilic compounds. The metabolism of most drugs that takes place in the liver is associated with large and hydrophobic compounds (Lombardo et al., 2003). Higher lipophilicity of compounds leads to increased metabolism and poor absorption, along with an increased probability of binding to undesired hydrophobic macromolecules, thereby increasing the potential for toxicity (Pajouhesh & Lenz, 2005). In spite of the some observed exceptions to Lipinski's rule, the property values of the vast majority (90%) of the orally active compounds are within their cut-off limits (Lipinski et al., 1997, 2001). Molecules violating more than one of these rules may have problems with bioavailability. For studying PK properties Lipinski's ‘Rule of Five’ screening was used so that to assess the drug likeness properties of active derivatives. Briefly, this rule is based on the observation that most orally administered drugs have a molecular weight (MW) of 500 or less, a LogP no higher than 5, five or fewer hydrogen bond donor sites and 10 or fewer hydrogen bond acceptor sites (N and O atoms).

Example 4
In Silico Screening: Compliance with Oral Bioavailability and Toxicity Risk Assessment Parameters

In addition, the oral bioavailability of active derivatives was assessed through topological polar surface area. We calculated the polar surface area (PSA) by using method based on the summation of tabulated surface contributions of polar fragments termed as topological PSA (TPSA) (ChemAxon-Marvinview 5.2.6:PSA plugin (Ertl et al., 2000). PSA is formed by polar atoms of a molecule. This descriptor was shown to correlate well with passive molecular transport through membranes and therefore, allows prediction of transport properties of drugs and has been linked to drug bioavailability. The percentage of the dose reaching the circulation is called the bioavailability. Generally, it has been seen that passively absorbed molecules with a PSA>140 Å²are thought to have low oral bioavailability (Norinder et al., 1999; Ertl et al., 2000). Besides, number of rotatable bonds is also a simple topological parameter used by researchers under extended Lipinki's rule of five as measure of molecular flexibility. It has been shown to be a very good descriptor of oral bioavailability of drugs (Veber et al., 2002). Rotatable bond is defined as any single non-ring bond, bounded to non-terminal heavy (i.e., non-hydrogen) atom. Amide C—N bonds are not considered because of their high rotational energy barrier. Moreover, some researchers also included sum of H-bond donors and H-bond acceptors as a secondary determinant of fraction absorption. The primary determinant of fraction absorption is polar surface area (Clark, 1999; Stenberg et al., 2001). According to extended rule the sum of H-bond donors and acceptors should be less then or equal to 12 or polar surface area should be less then or equal to 140 A², and number of rotatable bonds should be less then or equal to 10 (Veber et al., 2002). Calculations of other important ADME/T properties of studied compounds were performed through QikProp (QP), version 3.2, Schrodinger, LLC, New York, USA (2009). We screened all the active compounds through Jorgensen Rule of three (Shrodinger, 2009), which state that for orally available molecule, QP logS should be more then −5.7, QP PCaco should be more then 22 nm/s, number of primary metabolites should be less then 7. Moreover, toxicity risks (mutagenicity, tumorogenicity, irritation, reproduction) and associated physicochemical properties (ClogP, solubility, drug-likeness and drug-score) of compounds (G3-G13) were calculated by Osiris calculator (Parvez et al., 2010; Abdul Rauf et. al. 2010). Toxicity risks and physicochemical properties of compounds (G3-G13) were calculated through Osiris software (Parvez et al., 2010).

Example-5
Biological Activity Prediction Through QSAR Modeling

Structure activity relationship has been denoted by QSAR model showing significant activity-descriptors relationship and activity prediction accuracy. Only five chemical structural descriptors (2D and 3D structural properties) showed good correlation with antipsychotic activity (Table 1). A forward stepwise multiple linear regression QSAR model was developed using leave-one-out validation approach for the prediction of in vitro antipsychotic activity of organic compounds and its derivatives. Anti-psychotic drugs fit well into this correlation, which seems very reasonable one in the regression plot (FIG. 1). Relationship correlating measure (refer by regression coefficient r²) of QSAR model was 0.87 (87%) and predictive accuracy (refer by cross validation coefficient rCV²) was 0.81 (81%). QSAR study indicate that dipole vector Z (debye), steric energy (kcal/mole), ether group count, molar refractivity and shape index (basic kappa, order 3) correlates well with antipsychotic activity. Dipole vector Z, molar refractivity and shape index showed negative correlation, while steric energy and ether group count showed positive. The QSAR mathematical model equation derived through multiple linear regression method is given below showing good relationship between experimental activity i.e., in vitro inhibitory concentration (IC₅₀) (nM) and chemical descriptors. Predictive performance of best fit developed QSAR model was comparable to experimental antipsychotic activity.

QSAR model equation:

Predicted log IC₅₀(nM)=−0.124236×Dipole Vector Z(debye)(M)+0.0305374×Steric Energy(kcal/mole)(P)+1.0651×Group Count(ether)(V)−0.0639271×Molar Refractivity(AH)−0.380434×Shape Index(basic kappa,order 3)(AO)+9.12642

Antipsychotic Activity Prediction of Natural Yohimbine Alkaloids Through QSAR Modeling

Natural yohimbine alkaloids K001, K002, K003, K004A, K004B, K005 and K006 were subjected for the prediction of antipsychotic activity through QSAR modeling and the results showed that out of studied molecules and derivatives K001, K002, K003, K004A, K004B, K005 and K006, compound K001, K002, K004A and K004B indicate high antipsychotic activity comparable to Clozapine (Table 1). Later these theoretical results were found comparable to the experimental in vivo activity (FIG. 2) reported by us for these compounds ((Srivastava et. al. WO PCT/IN2010/000208). Besides, all the active compounds showed clearance of toxicity risk assessment parameters namely, mutagenicity, tumorogenicity, irritation, reproduction along with physicohemical properties related to drug likeness such as ClogP, solubility and drug-score. Moreover, all the active compounds showed high binding affinity to anti-psychotic receptors e.g., dopamine D2 receptor and serotonin (5HT_2A) receptor (Table 2-3). Besides, we also checked the compliance of compounds to Lipinski's rule-of-five for drug likeness (Table 24). Results indicate that active compounds followed most of the ADMET properties. Moreover, when we calculated the topological polar surface area (TPSA) of active compounds as chemical descriptor for passive molecular transport through membranes, results showed compliance with standard range i.e., TPSA>140 Å², thus indicate good oral bioavailability.

Example-6
Preparation of Synthetic Derivatives of α-Yohimbine (K001)

The various derivatives of α-yohimbine (K001) were prepared according to Formula 2 as given below:

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Example A

Dissolving α-yohimbine (K001) in dry pyridine (2 ml) and reacting it with acetic anhydride in 1:1.5 ratios along with 5 mg of 4-dimethyl amino pyridine (DMAP) for 16 hours at 40° C. After completion of the reaction, crushed ice was added to the reaction mixture and extracted the resultant mixture with chloroform followed by washing with water until neutralization. The product was purified by known method, which afforded 17-O-acetyl α-yohimbine (K001A) in 94% yield.

Example B

Dissolving α-yohimbine (K001) in dry dichloromethane (10 ml) and reacting it with 3,4,5 trimethoxy cinnamic acid in 1:2 ratio along with N,N′-Dicyclohexylcarbodiimide (45.3 mg) in presence of DMAP (4 mg) for 16 hours at a 40° C. After completion of the reaction, crushed ice was added to the reaction mixture and extracted the resultant mixture with chloroform followed by washing with water until neutralization. The product was purified by known method, which afforded 17-O-(3″,4″,5″)-trimethoxy cinnamoyl α-yohimbine (K001B) in 75% yield.

Example C

Dissolving K001 in dry dichloromethane (10 ml) and reacting it with desired acid chloride (such as 4-nitrobenzoyl chloride, cinnamoyl chloride and lauroyl chloride etc.) in 1:1.5 ratios along with 5 mg of 4-dimethyl amino pyridine (DMAP) for 16 hours at 40° C. After completion of the reaction, crushed ice was added to the reaction mixture and extracted the resultant mixture with chloroform followed by washing with water until neutralization. The product was purified by known method, which afforded the desired products 17-O-(4″)-nitrobenzoyl-α-yohimbine (K001E), 17-O-cinnamoyl α-yohimbine (K001F), 17-O-lauroyl α-yohimbine (K001G) in 87, 91 and 93% yields.

Example 7
Antipsychotic Activity Prediction of α-Yohimbine Derivatives Through QSAR Modeling

The α-yohimbine derivatives K001A, K001B, K001C, K001D, K001E, K001F and K001G, on QSAR activity prediction showed that derivatives K001A, K001C, K001E and K001F indicate high antipsychotic activity comparable to Clozapine (Table 4). However, compound K001C and K001E revealed high risk of mutagenicity under toxicity risk assessment studies, thus rejected. On the other hand, compound K001F indicate activity higher then Haloperidol (i.e. IC₅₀=1.5 nM), thus expected to be sensitive for strong early and late extrapyramidal side effects, thus not considered for further studies or derivatization. Predicted results were found comparable to experimental in vitro and in vivo activity (FIG. 3-4). Besides, active compound K001A showed compliance with physicohemical properties related to drug likeness such as ClogP, solubility and drug-score (Table 23). Moreover, active compounds K001A also showed high binding affinity to both anti-psychotic receptors e.g., dopamine D2 and serotonin (5HT_2A) (Table 5-6), thus considered for further derivatization. Further validation of active compound K001A for drug likeness was checked through Lipinski's rule-of-five (Lipinski et al., 2001), which was also found comparable to standard drugs. Results indicate that active compounds followed most of the ADMET properties. This helped in establishing the pharmacological activity of studied compounds for their use as potential antipsychotic lead. Moreover, when we calculated the topological polar surface area (TPSA) of active compounds as chemical descriptor for passive molecular transport through membranes, results showed compliance with standard range i.e., TPSA>140 Å², thus indicate oral bioavailability.

Example-8
In-Vitro and In-Vivo Antipsychotic Activity Evaluation of α-Yohimbine Derivatives

All the derivatives of α-yohimbine: 17-O-acetyl α-yohimbine (K001A), 17-O-(3″,4″,5″)-trimethoxy cinnamoyl α-yohimbine (K001B), 17-O-(3″)-nitrobenzoyl α-yohimbine (K001C), 17-O-benzoyl α-yohimbine (K001D), 17-O-(4″)-nitrobenzoyl-α-yohimbine (K001E), 17-O-cinnamoyl α-yohimbine (K001F), 17-O-lauryl α-yohimbine (K001G) as shown in Formula 2 were evaluated in-vitro and in-vivo for their antipsychotic potentials and the results are presented in the FIGS. 3 and 4 respectively. Although all the derivatives showed antipsychotic activity but the derivatives K001A, K001C, K001E, and K001F showed potential antipsychotic activity and were further evaluated for their antipsychotic potential in-vitro and in-vivo at lower doses and the results are presented in FIGS. 5 and 6 respectively.

Example-9
Preparation of Virtual Derivatives of Yohimbine Alkaloids

In order to get the potential antipsychotic agent, various virtual derivatives of yohimbine alkaloids, α-yohimbine (K001, Y series Y1 to Y100 of Formula 2 Table 27), reserpiline (K002, R series, R1 to R68 of Formula 3 Table 28), 11-demethoxyreserpiline (K004A, 11DR series, 11DR1 to 11DR21 of Formula 4 Table 29) and 10-demethoxyreserpiline (K004B, 10DR series, 10DR1 to 10DR59 of Formula 5 Table 30) were prepared.

embedded image

Example-10
Antipsychotic Activity Prediction of α-Yohimbine (K001) Derivatives Through QSAR Modeling

The QSAR modeling results showed that out of studied hundred derivatives (of which four derivatives broken) of K001, i.e., Y1 to Y100, compound Y69, Y61, Y64, Y73, Y68 and Y71 indicate very close antipsychotic activity and drug likeness properties similar to Clozapine (Table 7-8). However, compound Y52, Y1, Y75, Y3, Y51, Y2, Y74, Y96 and Y10 revealed moderate antipsychotic activity and druglikeness properties comparable to Clozapine. Lastly, compound Y58, Y63, Y82, Y76, Y5, Y32, Y97, Y86, Y40, Y14, Y77, Y41, Y25, Y100, Y33, Y78 showed high activity but low druglikeness due to strong early and late extrapyramidal side effects similar to Haloperidol. However, compound Y14 showed probability of irritation side effect under toxicity risk assessment studies thus rejected. Besides, active compounds showed compliance with physicohemical properties related to drug likeness such as ClogP, solubility and drug-score (Table 23). Moreover, all the active compounds (high, moderate and close) also showed high binding affinity to both anti-psychotic receptors e.g., dopamine D2 and serotonin (5HT_2A) (Table 9-10), thus considered as anti-psychotic lead molecules. Further validation of active compounds for drug likeness was checked through Lipinski's rule-of-five (Lipinski et al., 2001), which was also found comparable to standard drug Clozapine. Results indicate that active compounds followed most of the ADMET properties.

Predicted log IC50 and IC50 value of virtual derivatives of Yohimbane alkaloids and isolated Yohimbane alkaloids and semi-synthetic derivatives of α-yohimbine by virtual screening model is mentioned in table 33 and 32 respectively.

Example-11
Antipsychotic Activity Prediction of Reserpiline (K002, Formula 3) Derivatives Through Qsar Modeling

The QSAR modeling results showed that out of studied sixty eight derivatives of K002, i.e., R1 to R68, compound R40, R61, R58, R51, R68, R13, R12, R43, R62, R57, R41, R5, R16, R25, R32, R26, R14, R36, R18, R37, R1, R53, R33, R15, R10, R23, R49, R7, R6, R22, R63, R27, and R48 indicate very close antipsychotic activity and drug likeness properties similar to Clozapine (Table 11-12). However, compound R21, R28, R4, R24, R30, R30, R38, R20, R8, R11, R42, R19, R29, and R39 revealed moderate antipsychotic activity and druglikeness properties comparable to Clozapine. Lastly, compound R34, R35, R31, and R9 showed high activity but low druglikeness due to strong early and late extrapyramidal side effects similar to Haloperidol. Besides, active compounds showed compliance with physicohemical properties related to drug likeness such as ClogP, solubility and drug-score (Table 23). Moreover, the entire active compounds (high, moderate and close) showed binding affinity to anti-psychotic receptors e.g., dopamine D2 and serotonin (5HT_2A) (Table 13-14), thus considered as anti-psychotic lead molecules.

Example-12
Antipsychotic Activity Prediction of 11demethoxyreserpiline (K004A, Formula 4) Derivatives Through QSAR Modeling

The QSAR modeling results showed that out of studied twenty one derivatives of K004A, i.e., 11DR1 to 11DR21, compound 11DR3, 11DR2, 11DR1, 11DR12, 11DR14, 11DR18, 11DR13, 11DR16, 11DR10, and 11DR15 indicate very close antipsychotic activity and drug likeness properties similar to Clozapine (Table 15-16). However, compound 11DR8, 11DR5, 11DR4, 11DR6, 11DR11, 11DR20, 11DR21, 11DR7, 11DR19, and 11DR17 revealed moderate antipsychotic activity and drug likeness properties comparable to

Clozapine. Lastly, compound 11DR9 showed high activity but low drug likeness due to strong early and late extrapyramidal side effects similar to Haloperidol. Besides, active compounds showed compliance with physiochemical properties related to drug likeness such as ClogP, solubility and drug-score (Table 23). Moreover, the entire active compounds (high, moderate and close) showed binding affinity to anti-psychotic receptors e.g., dopamine D2 and serotonin (5HT_2A) (Table 17-18), thus considered as anti-psychotic lead molecules.

Example-13
Antipsychotic Activity Prediction of 10Demethoxyreserpiline (K004B, Formula 5) Derivatives Through QSAR Modeling

The QSAR modeling results showed that out of studied fifty nine derivatives of K004B, i.e., 10DR1 to 10DR59, compound 10DR22, 10DR3, 10DR40, 10DR41, 10DR45, 10DR33, 10DR25, 10DR12, 10DR16, 10DR13, 10DR32, 10DR37, 10DR18, 10DR36, 10DR43, 10DR14, and 10DR10 indicate very close antipsychotic activity and drug likeness properties similar to Clozapine (Table 19-20). However, compound 10DR26, 10DR59, 10DR15, 10DR5, 10DR46, 10DR4, 10DR6, 10DR11, 10DR21, 10DR38, 10DR48, 10DR27, 10DR20, 10DR7, 10DR53, 10DR29, 10DR8, 10DR28, 10DR52, 10DR24, and 10DR58 revealed moderate antipsychotic activity and druglikeness properties comparable to Clozapine. Lastly, compound 10DR17, 10DR42, 10DR23, 10DR19, 10DR30, 10DR39, and 10DR47 showed high activity but low druglikeness due to strong early and late extrapyramidal side effects similar to Haloperidol. Besides, active compounds showed compliance with physicohemical properties related to drug likeness such as ClogP, solubility and drug-score (Table 23). Moreover, all active compounds (high, moderate and close) showed binding affinity to anti-psychotic receptors e.g., dopamine D2 and serotonin (5HT_2A) (Table 21-22), thus considered as anti-psychotic lead molecules.

Example-14
Toxicity Risks Assessment, Drug Likeness and Drug Score of Yohimbine Alkaloids Derivatives

Now it is possible to predict toxicity risk parameter through Osiris calculator (Parvez et al., 2010; Abdul Rauf et. al. 2010). In the studied work, we screened all the studied compounds for toxicity risks parameters namely, mutagenicity, tumorogenicity, irritation, reproduction and quantitative data related to physicohemical properties namely, ClogP, solubility, drug-likeness and drug-score. The toxicity risk predictor locates fragments within a molecule which indicate a potential toxicity risk. From the data evaluated indicates that, all rejected compounds showed one or the more toxicity parameter such as mutagenicity and irritation side effect when run through the toxicity risk assessment system but as far as tumorogenicity and reproduction effects are concerned, all the compounds indicate no risk. The logP value is a measure of the compound's hydrophilicity. Low hydrophilicity and therefore high logP values may cause poor absorption or permeation. It has been shown for compounds to have a reasonable probability of being well absorb their logP value must not be greater than 5.0. On this basis, all the compounds are in acceptable limit. Similarly, the aqueous solubility (logS) of a compound significantly affects its absorption and distribution characteristics. Typically, a low solubility goes along with a bad absorption and therefore the general aim is to avoid poorly soluble compounds. Our estimated logS value is a unit stripped logarithm (base 10) of a compound's solubility measured in mol/liter. There are more than 80% of the drugs on the market have an (estimated) logS value greater than −4. On this basis, all the active compounds are in acceptable limit. Similarly, all the studied active compounds showed compliance with other drug likeness parameters e.g., Lipinski's rule, Jorgenson's rule, bioavailability etc. At last we have calculated overall drug-score for all the studied compounds and compared with that of standard antipsychotic compound Clozapine. The drug-score combines drug-likeness, ClogP, logS, molecular weight, and toxicity risks in one handy value in Table 23 that may be used to judge the compound's overall potential to qualify for a drug.

Example-15
In Vitro Antipsychotic Screening
Radioligand Receptor Binding Assay Using Multi Probe II Ex Robotics Liquid Handling System

Neurotransmitter such as dopamine-D₂and Serotonin (5HT_2A) are significantly, involved in psychotic behaviour (Creese I, et al., 1976). Hence forth effect of test samples of α-yohimbine semi-synthetic derivatives were tested on these two receptors using in vitro receptor binding assay with the help of specific radioligand.

Preparation of Crude Synaptic Membrane

Rat was killed by decapitation; Brain was removed and dissected the discrete brain regions in cool condition following the standard protocol (Glowinski and Iverson 1966). Crude synaptic membrane from corpus striatum and frontal cortex brain region was prepared separately following the procedure of Khanna et al 1994. Briefly, the brain region was weighed and homogenized in 19 volumes of 5 mM Tris—Hcl buffer (pH 7.4) (5% weight of tissue). The homogenate was centrifuged at 50,000×g for 20 minutes at 4° C. The supernatant was removed and the pellet was dispersed in same buffer pH 7.4, centrifuged at 50,000×g for 20 minutes at 4° C. again. This step helps in remaining endogenous neurotransmitter and also helps in neuronal cell lyses. The pellet obtained was finally suspended in same volume of 40 mM Tris—HCI Buffer (pH 7.4) and used as a source of receptor for in vitro receptor binding screening of the samples for Dopaminergic and Serotonergic (5HT_2A) receptor. Protein estimation was carried out following the method of Lowry et al 1951.

Receptor Binding Assay

In vitro receptor binding assay for dopamine-D₂and Serotonin (5HT_2A) was carried out in 96 well multi screen plate (Millipore, USA) using specific radioligands 3H-Spiperone for DAD2 and 3H-Ketanserin for 5HT_2Aand synaptic membrane prepared from corpus striatal and frontal cortex region of brain as source of receptor detail discussed in Table 25 following the method of Khanna et al. (1994). Reaction mixture of total 250 μl was prepared in triplicate in 96 well plates as detail given in Table 26. The reaction mixture were mixed thoroughly and incubated for 15 min. at 37° C. After incubation of 15 min. the content of each reaction was filtered under vacuum manifold attached with liquid handling system. Washed twice with 250 μl cold tris—HCI buffer, dried for 16 hours, 60 μl scintillation fluid (Microscint ‘O’, Packard, USA) was added to each well followed by counting of radio activity in terms of count per minute (CPM) on plate counter (Top Count—NXT, Packard, USA). Percent inhibition of receptor binding was calculated in presence and absence of test sample.

$% Inhibition in binding = \frac{Binding in presence of test sample}{Total binding obtained in absence of test sample} \times 100$

The inhibition potential of various semi-synthetic derivatives on the binding of 3H-Spiperone to corpus striatal and 3H-Ketanserin to frontocortical membranes were in-vitro screened and IC₅₀values were determined.

Example-16
In Vivo Antipsychotic Screening

In order to assess the antipsychotic potential of semi-synthetic derivatives of yohimbine alkaloids, amphetamine induced hyper activity mouse model was used following the method of Szewczak et at (1987). Adult Swiss mice of either sex (25±2 g body weight) obtained from the Indian Institute of Toxicology Research (IITR), Lucknow, India animal-breeding colony were used throughout the experiment. The animals were housed in plastic polypropylene cages under standard animal house conditions with a 12 hours light/dark cycle and temperature of 25±2° C. The animals had adlibitum access to drinking water and pellet diet (Hindustan Lever Laboratory Animal Feed, Kolkata, India). The Animal Care and Ethics Committee of IITR approved all experimental protocols applied to animals.

Antipsychotic Activity

The mice randomly grouped in batches of seven animals per group. The basal motor activity (distance traveled) of each mouse was recorded individually using automated activity monitor (TSE, Germany). After basal activity recording, a group of seven animals were challenged with amphetamine [5.5 mg/kg, intra peritoneal (i.p) dissolved in normal saline]. After 30 min. amphetamine injection, motor activity was recorded for individual animal for 5 min. In order to assess the anti-psychotic activity of semi-synthetic derivatives of α-yohimbine, already acclimatized animals were pre-treated with test sample (suspended in 2% gum acacia at a dose of 25, 12.5, 6.25 mg/kg given orally by gavage. One hour after sample treatment, each mouse were injected 5.5 mg/kg amphetamine i.p. 30 minutes after amphetamine treatment, motor activity was recorded of individual mouse for 5 min.

The difference in motor activity as indicated by distance traveled in animals with amphetamine alone treated and animals with samples plus amphetamine challenge was recorded as inhibition in hyper activity caused by amphetamine and data presented as percent inhibition in amphetamine induced hyperactivity.

Example-17
Human Dose Calculation

The minimum dose at which an antipsychotic semi-synthetic derivative showed >60% inhibition in amphetamine induced hyperactivity mice model was taken for human dose calculation.

The human dose of antipsychotic is 1/12 of the mice dose. Taking 60 Kg as an average weight of a healthy human, human doses for semi-synthetic derivatives of α-yohimbine were calculated as shown below.

$Human dose = \frac{M^{*} \times 60^{@}}{12^{$}}$

- M*Dose in amphetamine induced hyperactivity mice model
- @Average weight of a healthy human
- ^$Human dose is 1/12 of the mice

In FIG. 5, K001A and K001C at 25 mg/Kg showed >60% inhibition in amphetamine induced hyperactivity mice model. Hence the human dose of K001A and K001C will be

$\frac{25 \times 60}{12} = 125 mg$

TABLE 1

Comparison of experimental and predicted in vitro activity (IC50 (M) data calculated through

developed QSAR model based on correlated chemical descriptors of yohimbane alkaloids.

Steric
Group

Shape Index

Chemical
Dipole Vector
Energy
Count
Molar
(basic kappa,
Predicted
Experimental

Sample
Z (debye)
(kcal/mole)
(ether)
Refractivity
order 3)
log IC50 (nM)
log IC₅₀(nM)

Haloperidol
−1.456
23.252
0
1.2.592
393.948
1.271
1.5

Clozapine
−0.669
95.173
0
96.773
3.52
4.59
5.12

K001
0.88
58.703
0
98.572
2.951
3.386

K002
−1.028
43.611
3
111.435
3.665
5.263

K003
−1.132
36.673
2
104.972
3.353
4.531

K004 A
0.972
54.061
2
104.972
3.353
4.801

K004 B
−0.788
35.173
2
104.972
3.353
4.443

K005
0.577
48.461
3
111.435
3.665
5.212

K006
−0.618
40.86
1
98.509
2.951
4.096

Experimental log IC50 value of Haloperidol and Clozapine are just used for comparison purpose only.

TABLE 2

Details of binding affinity of Antipsychotic derivative and its

binding pocked residue docked on D2 dopamine receptor

(PDB ID: 2HLB)

Docking
Binding pocket residues (4 Å)

energy
(hydrogen bonded residues are

S. No
Ligand
(Kcal/mol)
highlighted in bold)

1
K001
−60.157
TRP-5, PHE-8, LEU-9.

2
K002
−60.473
SER-1, VAL-3, THR-4, TRP-5, PHE-8,

LEU-9, GLU-11.

3
K003
−61.651
TRP-5, PHE-8, LEU-9, ASP-12.

4
K004 A
−58.624
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,

GLU-11.

5
K004 B
−61.672
VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

6
K005
−68.706
TRP-5, PHE-8, LEU-9.

7
K006
−58.794
TRP-5, PHE-8, LEU-9.

TABLE 3

Details of binding affinity of Antipsychotic derivative and its

binding pocked residue docked on Serotonin receptor (5HT_2A)

(developed homology based 3D model)

Docking
Binding pocket residues (4 Å)

energy
(hydrogen bonded residues are

S. No
Ligand
(Kcal/mol)
highlighted in bold)

1
K001
−51.946
VAL-174, PHE-178, ILE-181, LYS-182,

lys-246, PHE-253, LEU-254, VAL-256,

VAL-257

2
K002
−39.336
LEU-170, VAL-174, TYR-177, PHE-178,

ILE-181, LYS-246, ILE-250, PHE-253,

LEU-254, VAL-256, VAL-257

3
K003
−47.854
LEU-170, THR-171, VAL-174, PHE-178,

ILE-181, LYS-182, LYS-246, ILE-250,

PHE-253, VAL-256, VAL-257, CYS-260

4
K004 A
−23.786
PHE-218, VAL-247, ILE-250, VAL-298,

LEU-301, VAL-302, TYR-303, THR-304,

ARG-311

5
K004 B
−25.82
PHE-218, ILE-250, LEU-254, MET-258,

LEU-294, VAL-298, LEU-301, VAL-302,

TYR-303, THR-304, ARG-311

6
K005
−18.162
PHE-218, VAL-247, ILE-250, LEU-254,

MET-258, LEU-294, VAL-298, LEU-301,

VAL-302, TYR-303, THR-304, ARG-311

7
K006
−25.319
PHE-218, VAL-298, LEU-301, VAL-302,

TYR-303, THR-304, ARG-311

TABLE 4

Comparison of experimental and predicted in vitro activity (IC50) data calculated through developed

QSAR model based on correlated chemical descriptors of yohimbine (K001) derivatives

Steric
Group

Shape Index

Chemical
Dipole Vector
Energy
Count
Molar
(basic kappa,
Predicted
Experimental

Sample
Z (debye)
(kcal/mole)
(ether)
Refractivity
order 3)
log IC50 (nM)
log IC₅₀(nM)

Haloperidol
−1.456
23.252
0
1.2.592
393.948
1.271
1.5

Clozapine
−0.669
95.173
0
96.773
3.52
4.59
5.12

K001
0.88
58.703
0
98.572
2.951
3.386

K001 A
−0.23
63.288
0
107.724
3.755
2.773

K001 B
−2.945
57.497
3
157.529
6.497
1.901

K001 C
−26.675
67.389
0
135.554
5.254
3.834

K001 D
−2.737
66.746
0
127.896
4.608
1.576

K001 E
−3.62
69.571
0
135.554
5.254
1.036

K001 F
−0.997
56.628
0
138.14
5.406
0.092

K001 G
−1.163
89.91
1
154.004
7.088
0.54

TABLE 5

Details of binding affinity of Antipsychotic derivative and its

binding pocked residue docked on D2 dopamine receptor

(PDB ID: 2HLB)

Docking
Binding pocket residues (4 Å)

energy
(hydrogen bonded residues are

S. No
Ligand
(Kcal/mol)
highlighted in bold)

1
K001
−60.157
TRP-5, PHE-8, LEU-9.

2
K001 A
−63.771
SER-1, VAL-3, TRP-5, PHE-8,

LEU-9.

3
K001 B
−103.988
SER-1, VAL-3, TRP-5, PHE-8,

LEU-9, GLU-11

4
K001 C
−71.776
SER-1, VAL-3, THR-4, TRP-5,

PHE-8, LEU-9, GLU-11.

5
K001 D
−75.797
SER-1, VAL-3, THR-4, TRP-5,

PHE-8, LEU-9, GLU-11.

6
K001 E
−34.621
SER-1, VAL-3, TRP-5, PHE-8,

LEU-9, GLU-11.

7
K001 F
−76.36
THR-4, TRP-5, TYR-6, ASP-7.

8
K001 G
−90.677
SER-1, VAL-3, TRP-5, PHE-8,

LEU-9, GLU-11.

TABLE 6

Details of binding affinity of Antipsychotic derivative and its binding pocked residue

docked on Serotonin receptor (5HT_2A) (developed homology based 3D model)

Binding pocket

A. A residue

Docking
residues(4 Å) (hydrogen
Atoms of Ligand
involved in
Length of
No. of

S.

energy
bonded residues are
involved in
Docking
hydrogen
Hydrogen

No
Ligand
(Kcal/mol)
highlighted in bold)
Docking
interaction
bond (Å)
Bond (H)*

1
K001
+
—
—
—
—
—

2
K001 A
−64.529
PHE-218, ILE-250, LEU-
—
—
—
—

254, MET-258, LEU-294,

ALA-297, VAL-298, LEU-

301, VAL-302

3
K001 B
−74.38
ASN-15, VAL-18, LEU-39,
—
—
—
—

ALA-40, ASP-43, PHE-81,

SER-85, LEU-89, ILE-92,

VAL-251, PHE-252, LEU-

254, PHE-255, TRP-259,

TYR-293, SER-295, SER-

296, ASN-299, PRO-300,

VAL302, TYR-303, THR-

304, LEU-305, TYR-310,

PHE-314

4
K001 C
−90.25
PHE-218, ILE-250, LEU-
—
—
—
—

254, MET-258, LEU-294,

VAL-298, LEU-301, VAL-

302, TYR-303, ARG-311

5
K001 D
−77.182
VAL-7, LEU-10, VAL-257,
—
—
—
—

ILE-250, LEU-254, MET-

258, LEU-294, VAL-298,

LEU-301, VAL-302, TYR-

303 ARG-311

6
K001 E
−19.551
LEU-3, VAL-7, ILE-8, MET-
H5240-O75
THR-11
2.082
1

51, LEU-254, MET-258,

TRP-290, ILE-291, TYR-

293, LEU-294, SER-296,

ALA-297, VAL-298,

7
K001 F
−87.239
PHE-167, LEU-170, VAL-
—
—
—
—

174, TYR-177, PHE-178,

ILE-181, ILE-222, LYS-

246, PHE-253, VAL-256,

VAL257, CYS-260, ILE-

264,

8
K001 G
−82.704
THR-32, PHE-35, LEU-36,
—
—
—
—

LEU-39, ALA-42, ASP-43,

LEU-46, PHE-81, ALA-84,

SER-85, ILE-86, HIS-88,

LEU-89, ILE-92, SER-93,

ARG-96, ARG-108, TYR-

177, CYS-245, LEU-248,

VAL-251, PHE-252, LEU-

254, PHE-255, TRP-259,

GLY-292, TYR-293, SER-

295, SER-296, VAL-298,

ASN-299, LEU-305

TABLE 7

Predicted Antipsychotic activity of α-yohimbine derivatives

S. No.
Compound Name
Pred. log IC50 (nM)
Pred. IC50 (nM)

(1)
Y1
3.748
5597.58

(2)
Y2
2.878
755.09

(3)
Y3
3.062
1153.45

(4)
Y4
0.353
2.25

(5)
Y5
1.876
75.16

(6)
Y6
0.06
1.15

(7)
Y7
0.358
2.28

(8)
Y8
0.553
3.57

(9)
Y9
0.402
2.52

(10)
Y10
2.095
124.45

(11)
Y11
0.208
1.61

(12)
Y12
1.202
15.92

(13)
Y13
1.228
16.90

(14)
Y14
1.635
43.15

(15)
Y15
1.097
12.50

(16)
Y16
0.885
7.67

(17)
Y17
−0.012
0.97

(18)
Y18
1.407
25.53

(19)
Y19
0.083
1.21

(20)
Y20
−0.043
0.91

(21)
Y21
0.479
3.01

(22)
Y22
1.367
23.28

(23)
Y23
0.094
1.24

(24)
Y24
−0.437
0.37

(25)
Y25
1.534
34.20

(26)
Y26
−0.41
0.39

(27)
Y27
0.789
6.15

(28)
Y28
0.644
4.41

(29)
Y29
−0.208
0.62

(30)
Y30
0.367
2.33

(31)
Y31
−0.745
0.18

(32)
Y32
1.818
65.77

(33)
Y33
1.476
29.92

(34)
Y34
−1.187
0.07

(35)
Y35
−0.696
0.20

(36)
Y36
0.476
2.99

(37)
Y37
0.785
6.10

(38)
Y38
0.708
5.11

(39)
Y39
−0.717
0.19

(40)
Y40
1.641
43.75

(41)
Y41
1.612
40.93

(42)
Y42
−0.279
0.53

(43)
Y43
1.014
10.33

(44)
Y44
−0.751
0.1.8

(45)
Y45
0.857
7.19

(46)
Y46
0.365
2.32

(47)
Y47
0.057
1.14

(48)
Y48
0.34
2.19

(49)
Y49
−0.269
0.54

(50)
Y50
0.998
9.95

(51)
Y51
2.904
801.68

(52)
Y52
3.917
8260.38

(53)
Y53
1.11
12.88

(54)
Y54
0.513
3.26

(55)
Y55
−0.376
0.42

(56)
Y56
−0.827
0.15

(57)
Y57
−1.984
0.01

(58)
Y58
1.985
96.61

(59)
Y60
−0.763
0.17

(60)
Y61
4.803
63533.09

(61)
Y62
−0.921
0.12

(62)
Y63
1.945
88.10

(63)
Y64
4.539
34593.94

(64)
Y65
0.663
4.60

(65)
Y66
−0.4
0.40

(66)
Y67
−0.778
0.17

(67)
Y68
4.523
33342.64

(68)
Y69
4.807
64120.96

(69)
Y70
−1.002
0.10

(70)
Y71
4.517
32885.16

(71)
Y72
−0.861
0.14

(72)
Y73
4.529
33806.48

(73)
Y74
2.814
651.63

(74)
Y75
3.712
5152.29

(75)
Y76
1.878
75.51

(76)
Y77
1.623
41.98

(77)
Y78
1.445
27.86

(78)
Y79
1.161
14.49

(79)
Y80
1.33
21.38

(80)
Y81
0.365
2.32

(81)
Y82
1.923
83.75

(82)
Y83
0.966
9.25

(83)
Y84
0.81
6.46

(84)
Y85
0.797
6.27

(85)
Y86
1.707
50.93

(86)
Y87
1.065
11.61

(87)
Y88
1.191
15.52

(88)
Y89
0.502
3.18

(89)
Y90
0.572
3.73

(90)
Y93
0.502
3.18

(91)
Y95
0.812
6.49

(92)
Y96
2.339
218.27

(93)
Y97
1.78
60.26

(94)
Y98
−0.398
0.40

(95)
Y99
1.119
13.15

(96)
Y100
1.492
31.05

TABLE 8

Predicted Antipsychotic activity of α-yohimbine derivatives

Compd
Activity
Status

Y69
4.807
Close activity and drug likeness

Y61
4.803
similar to Clozapine

Y64
4.539

Y73
4.529

Y68
4.523

Y71
4.517

Y52
3.917
Moderate activity and drug likeness

Y1
3.748
then Clozapine

Y75
3.712

Y3
3.062

Y51
2.904

Y2
2.878

Y74
2.814

Y96
2.339

Y10
2.095

Y58
1.985
High activity but low drug likeness

Y63
1.945
due to high extrapyramidal symptoms

Y82
1.923
similar to Haloperidol

Y76
1.878

Y5
1.876

Y32
1.818

Y97
1.78

Y86
1.707

Y40
1.641

Y148*
1.635

Y77
1.623

Y41
1.612

Y25
1.534

Y100
1.492

Y33
1.476

Y78
1.445

*Irritation

TABLE 9

Details of binding affinity of α-yohimbine derivatives and its

binding pocked residue docked on dopamine D2 receptor (PDB ID: 2HLB)

Binding pocket

A. A residue

Docking
residues(4 Å) (hydrogen
Atoms of Ligand
involved in
Length of
No. of

S.

energy
bonded residues are
involved in
Docking
hydrogen
Hydrogen

No
Ligand
(Kcal/mol)
highlighted in bold)
Docking
interaction
bond (Å)
Bond (H)*

1.
Y1
−62.361
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

2.
Y2
−61.625
VAL-3, TRP-5, PHE-8, LEU-9
—
—
—
—

3.
Y3
+
—
—
—
—
—

4.
Y4
−56.135
VAL-3, THR-4, TRP-5, PHE-8, LEU-9
—
—
—
—

5.
Y5
−29.992
TRP-5, PHE-8, LEU-9
—
—
—
—

6.
Y6
−66.561
SER-1, VAL-3, TRP-5, ASP-7, PHE-8,
—
—
—
—

LEU-9, GLU-11

7.
Y7
−69.439
VAL-3, THR-4, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

8.
Y8
−65.497
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

9.
Y9
+
—
—
—
—
—

10.
Y10
+
—
—
—
—
—

11.
Y11
−69.537
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

12.
Y12
−68.453
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

13.
Y13
−64.254
VAL-3, THR-4, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

14.
Y14
−9.781
SER-1, VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

15.
Y15
−65.324
VAL-3, THR-4, TRP-5, PHE-8, LEU-9,
—
—
—
—

16.
Y16
−66.462
SER-1, ARG-2, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

17.
Y17
−61.195
SER-1, VAL-3, THR-4, TRP-5, ASP-7,
—
—
—
—

PHE-8, GLU-11

18.
Y18
+
—
—
—
—
—

19.
Y19
−61.895
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11,

20.
Y20
−55.434
SER-1, VAL-3, TYR-6, ASP-7, PHE-8,
—
—
—
—

MET-10, GLU-11

21.
Y21
−60.017
SER-1, VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

22.
Y22
−65.909
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

23.
Y23
−66.311
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

24.
Y24
−70.978
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

25.
Y25
−53.796
SER-1, VAL-3, TYR-6, ASP-7, PHE-8,
—
—
—
—

MET-10, GLU-11

26.
Y26
−70.139
SER-1, VAL-3, THR-4, TRP-5, ASP-7,
—
—
—
—

PHE-8, MET-10, GLU-11

27.
Y27
−67.464
SER-1, VAL-3, THR-4, TRP-5, ASP-7,
H59-O2854
GLU-11
1.969
1

PHE-8, LEU-9, GLU-11

28.
Y28
−51.885
SER-1, VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

29.
Y29
−62.368
TRP-5, PHE-8, LEU-9,
—
—
—
—

30.
Y30
−66.209
SER-1, VAL-3, THR-4, TRP-5, ASP-7,
—
—
—
—

PHE-8, GLU-11

31.
Y31
−66.25
SER-1, ARG-2, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

32.
Y32
−65.332
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

33.
Y33
−60.23
VAL-3, THR-4, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

34.
Y34
−76.54
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

35.
Y35
−64.371
VAL-3, THR-4, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

36.
Y36
−55.672
SER-1, VAL-3, ASP-7, PHE-8, MET-10,
—
—
—
—

GLU-11

37.
Y37
−64.218
SER-1, VAL-3, THR-4, ASP-7, PHE-8,
—
—
—
—

GLU-11

38.
Y38
+
—
—
—
—
—

39.
Y39
−69.431
SER-1, ARG-2, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

40.
Y40
−48.727
SER-1, VAL-3, THR-4, TYR-6, ASP-7.
—
—
—
—

41.
Y41
−62.264
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

42.
Y42
−61.929
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

43.
Y43
−57.496
VAL-3, TRP-5, PHE-8, LEU-9, GLU-11
—
—
—
—

44.
Y44
−62.146
VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

45.
Y45
−66.132
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

46.
Y46
−64.544
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

47.
Y47
−40.518
VAL-3, THR-4, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

48.
Y48
−49.712
VAL-3, THR-4, TRP-5, PHE-8, LEU-9,
—
—
—
—

49.
Y49
−56.505
SER-1, ARG-2, VAL-3, THR-4, TRP-5,
—
—
—
—

ASP-7, PHE-8, GLU-11

50.
Y50
−63.351
VAL-3, THR-4, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

51.
Y51
−89.968
ARG-2, VAL-3, THR-4, TRP-5, TYR-6,
—
—
—
—

ASP-7,

52.
Y52
−76.155
THR-4, TRP-5, TYR-6, ASP-7.
—
—
—
—

53.
Y53
−75.042
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

54.
Y54
−70.542
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

55.
Y55
−75.21
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

56.
Y56
−86.514
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

57.
Y57
−73.805
SER-1, TRP-5, PHE-8, LEU-9, GLU-11
—
—
—
—

58.
Y58
−81.94
VAL-3, THR-4, TRP-5, TYR-6, ASP-7,
—
—
—
—

59.
Y60
−63.811
ARG-2, VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9,

60.
Y61
−56.749
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

61.
Y62
−70.328
VAL-3, TRP-5, PHE-8, LEU-9, GLU-11
—
—
—
—

62.
Y63
−66.032
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

63.
Y64
−59.312
THR-4 TRP-5, TYR-6, ASP-7
—
—
—
—

64.
Y65
−63.064
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

65.
Y66
−82.837
SER-1, VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9,

66.
Y67
−80.545
VAL-3, THR-4, TRP-5, PHE-8, LEU-9
—
—
—
—

67.
Y68
−61.815
THR-4,, TRP-5, TYR-6, ASP-7
—
—
—
—

68.
Y69
−64.747
THR-4, TRP-5, TYR-6, ASP-7,
—
—
—
—

69.
Y70
−82.067
THR-4, TYR-6, ASP-7,, MET-10, GLU-11
H67-O2811,
TYR-6,
2.081,
2

H68-2819
ASP-7
1.970

70.
Y71
−60.827
THR-4, TRP-5, TYR-6, ASP-7
—
—
—
—

71.
Y72
−49.618
VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

72.
Y73
−61.032
THR-4, TRP-5, TYR-6, ASP-7
—
—
—
—

73.
Y74
−78.512
THR-4, TRP-5, TYR-6, ASP-7, MET-10,
—
—
—
—

GLU-11

74.
Y75
−69.276
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

75.
Y76
−72.747
THR-4, TRP-5, TYR-6, ASP-7,, MET-10
—
—
—
—

76.
Y77
+
—
—
—
—
—

77.
Y78
−55.621
SER-1, VAL-3, TYR-6, ASP-7, MET-10
—
—
—
—

78.
Y79
−73.119
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

79.
Y80
−56.108
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9,

80.
Y81
−74.071
SER-1, VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

81.
Y82
−64.819
VAL-3, THR-4, TRP-5, PHE-8, LEU-9,
—
—
—
—

ASP-12

82.
Y83
−80.42
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

83.
Y84
−75.188
SER-1, ARG-2, VAL-3, TRP-5, ASP-7,
—
—
—
—

PHE-8, LEU-9, GLU-11

84.
Y85
−69.754
SER-1, VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9,

85.
Y86
−75.272
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

86.
Y87
−70.373
SER-1, VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

87.
Y88
−78.238
THR-4, TRP-5, TYR-6, ASP-7, MET-10
—
—
—
—

88.
Y89
−75.968
SER-1, VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

89.
Y90
−68.038
SER-1, VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11, ASP-12

90.
Y93
−29.958
VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

91.
Y95
−76.438
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

92.
Y96
−76.993
THR-4, TRP-5, TYR-6, ASP-7.
—
—
—
—

93.
Y97
−65.088
VAL-3, TRP-5, PHE-8, LEU-9, GLU-11
—
—
—
—

94.
Y98
−75.825
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

95.
Y99
−83.905
SER-1, VAL-3, THR-4, TRP-5, ASP-7,
—
—
—
—

PHE-8, LEU-9, GLU-11

96.
Y100
−73.24
SER-1, ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

TABLE 10

Details of α-yohimbine derivatives which showed binding affinity and their binding

pocked residue docked on Serotonin receptor (5HT2A) (developed homology based 3D model)

Atoms of
A. A residue

Docking
Binding pocket residues(4 Å)
Ligand
involved in
Length of
No. of

S.

energy
(hydrogen bonded residues are
involved in
Docking
hydrogen
Hydrogen

No
Ligand
(Kcal/mol)
highlighted in bold)
Docking
interaction
bond (Å)
Bond (H)*

1
Y1
−62.361
LEU-3, VAL-7, LEU-254, MET-
—
—
—
—

258, VAL-287, TRP-290, ILE-291,

LEU-294, VAL-298, LEU-301.

2
Y2
−61.625
PHE-218, LYS-246, VAL-247, ILE-
—
—
—
—

250, LEU-294, VAL-298, LEU-301,

VAL-302, TYR-303.

3
Y6
−66.561
LEU-170, VAL-174, PHE-253,
—
—
—
—

VAL-256, VAL-257, CYS-260,

PRO-261, ILE-264,

4
Y7
−69.439
PHE-218, LYS-246, VAL-247, ILE-
—
—
—
—

250, LEU-254, VAL-298, LEU-301,

VAL-302, TYR-303, THR-304,

ARG-311.

5
Y12
−68.453
LEU-3, VAL-7, LEU-254, MET-
—
—
—
—

258, VAL-287, TRP-290, ILE-291,

LEU-294, VAL-298, LEU-301.

6
Y26
−70.139
PHE-218, VAL-247, ILE-250,
—
—
—
—

LEU-254, MET-258, LEU-294,

VAL-298, LEU-301, VAL-302,

TYR-303. THR-304,

7
Y44
−62.146
PHE-218, LYS-246, ILE-250,
—
—
—
—

LEU-254, MET-258, LEU-294,

VAL-298, LEU-301, VAL-302,

TYR-303. THR-304,.

8
Y52
−75.21
PHE-218, VAL-247, ILE-250,
—
—
—
—

LEU-254, LEU-294, VAL-298,

LEU-301, VAL-302, TYR-303.

THR-304,

9
Y55
−86.514
ILE-250, LEU-254, LEU-294, VAL-
—
—
—
—

298, LEU-301, VAL-302, TYR-303.

10
Y56
−81.94
LEU-174, VAL-174, PHE-178, ILE-
—
—
—
—

181, LYS-182, CYS-245, LYS-246,

GLY-249, ILE-250, PHE-253, VAL-

256, VAL-257, CYS-260, PRO-

261, ILE-264,

11
D58
−63.811
VAL-7, PHE-218, ILE-250, LEU-
—
—
—
—

254, MET-258,, LEU-294, VAL-

298, LEU-301. VAL-302,

12
Y60
−62.361
PHE-218, LYS-246, VAL-247,
—
—
—
—

ILE-250, LEU-254, LEU-294, VAL-

298, LEU-301, VAL-302, TYR-303.

THR-304,

13
Y 61
−56.749
PHE-167, LEU-170, THR-171,
—
—
—
—

VAL-174, PHE-253, VAL-256,

VAL-257, CYS-260, ILE-264.

14
Y64
−59.312
LEU-170, VAL-174, PHE-178, ILE-
—
—
—
—

181, LYS-182, PHE-253, VAL-

256, VAL-257, CYS-260,

15
Y68
−61.815
PHE-167, LEU-170, THR-171,
—
—
—
—

VAL-174, PHE-178, PHE-253,

VAL-256, VAL-257, CYS-260, ILE-

264.

16
Y69
−64.747
PHE-167, LEU-170, THR-171,
—
—
—
—

VAL-174, PHE-178, PHE-25e3,

VAL-256, VAL-257, CYS-260, ILE-

264.

17
Y70
−82.067
PHE-218, LYS-246, ILE-250, LEU-
—
—
—
—

254, MET-258, LEU-294, VAL-

298, LEU-301, VAL-302, TYR-303.

THR-304

18
Y71
−60.827
LEU-170, VAL-174, PHE-178, ILE-
—
—
—
—

181, LYS-182, PHE-253, VAL-

256, VAL-257,

19
Y73
−61.032
LEU-170, VAL-174, PHE-178, ILE-
—
—
—
—

181, LYS-182, PHE-253, VAL-

256, VAL-257,

20
Y74
−78.512
PHE-218, LYS-246, VAL-247 ILE-
—
—
—
—

250, LEU-254, MET-258, LEU-

294, VAL-298, LEU-301, VAL-302,

TYR-303. THR-304

21
Y75
−69.276
PHE-218, LYS-246, ILE-250, LEU-
—
—
—
—

254, LEU-294, VAL-298, LEU-

301, VAL-302, TYR-303. THR-304

22
Y78
−55.621
LEU-3, THR-4, VAL-7, MET-51,
—
—
—
—

LEU-254, MET-258, TRP-290,

ILE-291, TYR-293, LEU-294, ALA-

297, VAL-298, LEU-301,

23
Y83
−80.42
LEU-170, VAL-174, PHE-178,
—
—
—
—

PHE-253, VAL-256, VAL-257,

PRO-261, ILE-264,

24
Y84
−75.188
LEU-3, THR-4, VAL-7, MET-51,
H5133-
TRP-90
2.005
1

LEU-254, MET-258, TRP-290,
O2246

ILE-291, TYR-293, LEU-294, VAL-

298, LEU-301,

25
Y86
−75.272
LEU-170, VAL-174, PHE-178, ILE-
—
—
—
—

182, LYS-182, PHE-253, VAL-

256, VAL-257, CYS-260, PRO-

261, ILE-264

26
Y96
−76.993
PHE-218, VAL-247 ILE-250, LEU-
—
—
—
—

254, MET-258, LEU-294, VAL-

298, LEU-301, VAL-302, THR-304

TABLE 11

Predicted Antipsychotic activity of risperidone derivatives

Compound
Pred. log
Pred.

S. No.
Name
IC50 (nM)
IC50(nM)

1
R1
3.477
2999.16

2
R2
5.695
495450.19

3
R4-
2.894
783.43

4
R5
3.913
8184.65

5
R6
3.189
1545.25

6
R7
3.198
1577.61

7
R8
2.727
533.33

8
R9
1.658
45.50

9
R10
3.295
1972.42

10
R11
2.7
501.19

11
R12
4.262
18281.00

12
R13
4.276
18879.91

13
R14
3.704
5058.25

14
R15
3.332
2147.83

15
R16
3.871
7430.19

16
R18
3.604
4017.91

17
R19
2.517
328.85

18
R20
2.733
540.75

19
R21
2.906
805.38

20
R22
3.184
1527.57

21
R23
3.24
1737.80

22
R24
2.887
770.90

23
R25
3.854
7144.96

24
R26
3.713
5164.16

25
R27
3.087
1221.80

26
R28
2.905
803.53

27
R29
2.392
246.60

28
R30
2.882
762.08

29
R31
1.66
45.71

30
R32
3.716
5199.96

31
R33
3.434
2716.44

32
R34
1.979
95.28

33
R35
1.844
69.82

34
R36
3.67
4677.35

35
R37
3.548
3531.83

36
R38
2.815
653.13

37
R39
2.299
199.07

38
R40
5.259
181551.57

39
R41
3.948
8871.56

40
R42
2.582
381.94

41
R43
4.218
16519.62

42
R44
7.424
26546055.62

43
R45
9.458
2870780582.02

44
R47
5.972
937562.01

45
R48
3.033
1078.95

46
R49
3.22
1659.59

47
R50
25.443
Out of range

48
R51
4.441
27605.78

49
R52
17.384
Out of range

50
R53
3.442
2766.94

51
R54
15.771
Out of range

52
R55
1.27
18.62

53
R56
0.21
1.62

54
R57
3.968
9289.66

55
R58
4.543
34914.03

56
R59
18.704
Out of range

57
R60
26.078
Out of range

58
R61
4.838
68865.23

59
R62
4.121
13212.96

60
R63
3.094
1241.65

61
R64
15.049
Out of range

62
R65
1.432
27.04

63
R66-
12.075
Out of range

64
R67
17.601
Out of range

65
R68
4.302
20044.72

TABLE 12

Predicted Antipsychotic activity of active riserpinine derivatives

Compd
Activity
Status

R49
3.22
Close activity and drug likeness

R7
3.198
similar to Clozapine

R6
3.189

R22
3.184

R63
3.094

R27
3.087

R48
3.033

R21
2.906
Moderate activity and druglikeness

R28
2.905
then Clozapine

R4
2.894

R24
2.887

R30
2.882

R30
2.882

R38
2.815

R20
2.733

R8
2.727

R11
2.7

R42
2.582

R19
2.517

R29
2.392

R39
2.299

R34
1.979
High activity but low druglikeness

R35
1.844
dur to high extrapyramidal symptoms

R31
1.66
similar to Haloperidol

R9
1.658

TABLE 13

Details of binding affinity of risperidone derivative and its binding

pocked residue docked on Dopamine D2 receptor: (PDB ID: 2HLB)

Docking energy
Binding pocket residues(4 Å) (hydrogen

S. No
Ligand
(Kcal/mol)
bonded residues are highlighted in bold)

1
R1
−57.257
SER-1, VAL-3, THR- 4, TRP-5, PHE-8, GLU-11

2
R2
−69.166
SER-1, VAL-3, THR- 4, TRP-5, PHE-8, LEU-9, GLU-11

3
R4
−64.415
VAL-3, TRP-5, PHE-8, LEU-9

4
R5
−68.626
THR- 4, TRP-5, TYR-6, ASP-7, MET- 10, GLU- 11

5
R6
−78.129
ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

6
R7
−73.308
SER-1, VAL-3, THR- 4, TRP-5, PHE-8, LEU-9, GLU-11

7
R8
−51.754
SER-1, ARG-2, VAL-3, THR- 4, TYR-6, ASP-7, PHE-8, GLU-11

8
R9
−66.593
SER-1, VAL-3, THR- 4, TRP-5, ASP-7, PHE-8, LEU-9, MET- 10,

GLU-11

9
R10
−68.53
ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

10
R11
−63.635
SER-1, VAL-3, THR- 4, TRP-5, ASP-7, PHE-8, LEU-9, GLU-11

11
R12
−59.29
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

12
R13
−73.589
SER-1, VAL-3, THR- 4, TRP-5, PHE-8, LEU-9, GLU-11

13
R14
−67.478
SER-1, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

14
R15
−68.461
SER-1, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

15
R16
−58.394
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

16
R18
−51.141
SER-1, VAL-3, THR-4, TRP-5, ASP-7, PHE-8, GLU-11

17
R19
−58.32
SER-1, VAL-3, THR-4, TRP-5, ASP-7, PHE-8, GLU-11

18
R20
−68.987
SER-1, VAL-3, THR-4, TRP-5, PHE-8, LEU-9, GLU-11

19
R21
−68.301
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

20
R22
−64.974
VAL-3, THR-4, TRP-5, TYR-6, ASP-7,

21
R23
−72.472
VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

22
R24
−77.404
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

23
R25
−60.435
TRP-5, PHE-8, LEU-9

24
R26
−77.841
VAL-3, THR-4, TRP-5, PHE-8, LEU-9

25
R27
−70.436
VAL-3, TRP-5, PHE-8, LEU-9

26
R28
−59.733
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

27
R29
−66.103
SER-1, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

28
R30
−59.664
SER-1, VAL-3, THR-4, TRP-5, ASP-7, PHE-8, LEU-9, GLU-11

29
R31
−67.961
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9

30
R32
−60.701
SER-1, VAL-3, THR-4, TRP-5, PHE-8, LEU-9, GLU-11

31
R33
−62.66
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9

32
R34
−61.825
SER-1, VAL-3, TRP-5, PHE-8, GLU-11

33
R35
−59.14
ARG-2, VAL-3, THR- 4, TRP-5, PHE-8, LEU-9, GLU-11

34
R36
−62.484
VAL-3, THR-4, TRP-5, PHE-8, LEU-9

35
R37
−66.094
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

36
R38
−46.689
TRP-5, PHE-8, LEU-9, GLU-11

37
R39
−77.679
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

38
R40
−65.642
SER-1, ARG-2, VAL-3, THR-4, TRP-5, PHE-8, LEU-9, GLU-11

39
R41
−53.354
SER-1, VAL-3, THR-4, TRP-5, PHE-8, LEU-9, GLU-11

40
R42
−63.746
SER-1, VAL-3, THR-4, TRP-5, PHE-8, LEU-9, GLU-11

41
R43
−69.228
VAL-3, TRP-5, PHE-8, LEU-9

42
R44
−67.006
SER-1, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

43
R45
−70.496
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

44
R47
−70.007
ARG-2, VAL-3, TRP-5, PHE-8, LEU-9

45
R48
−68.35
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

46
R49
−73.165
SER-1, VAL-3, THR-4, TRP-5, PHE-8, LEU-9, GLU-11

47
R50
−74.755
SER-1, VAL-3, THR-4, TRP-5, ASP-7, PHE- 8, MET- 10, GLU-

11

48
R51
−67.105
SER-1, VAL-3, THR-4, TRP-5, PHE-8, LEU-9, GLU-11

49
R52
−83.198
SER-1, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

50
R53
−84.867
SER-1, ARG-2, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

51
R54
−99.516
SER-1, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

52
R55
−67.386
SER-1, VAL-3, TRP-5, ASP-7, PHE-8, GLU-11

53
R56
−59.88
SER-1, VAL-3, THR-4, TRP-5, TYR- 6, ASP-7, PHE-8, MET- 10,

GLU-11

54
R57
−78.352
SER-1, ARG-2, VAL-3, THR-4, TRP-5, PHE-8, LEU-9

55
R58
−64.778
SER-1, VAL-3, THR- 4, TRP-5, PHE-8, GLU-11

56
R59
−75.029
SER-1, VAL-3, THR- 4, TRP-5, PHE-8, LEU-9, GLU-11

57
R60
−71.309
SER-1, ARG-2, VAL-3, THR- 4, ASP-7, PHE-8, GLU-11

58
R61
−59.475
TRP-5, PHE-8, LEU-9, GLU-11

59
R62
−80.136
SER-1, VAL-3, THR- 4, TRP-5, PHE-8, LEU-9, GLU-11

60
R63
−95.228
SER-1, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11

61
R64
−59.228
VAL-3, THR-4, TYR-6, ASP-7, MET- 10, GLU- 11

62
R65
−82.799
SER-1, VAL-3, THR- 4, TRP-5, ASP-7, PHE-8, LEU-9, GLU-11

63
R66-
−81.759
SER-1, ARG-2, VAL-3, TRP-5, TYR-6, ASP-7, PHE-8, MET- 10,

GLU- 11

64
R67
−86.806
SER-1, VAL-3, TRP-5, PHE-8, LEU-9, GLU-11, ASP- 12

65
R68
−61.144
TRP-5, PHE-8, LEU-9, GLU-11

TABLE 14

Details of binding affinity of risperidone derivatives and its binding pocked residue

docked on Serotonin receptor (5HT_2A) (developed homology based 3D model)

Docking energy
Binding pocket residues(4 Å) (hydrogen

S. No
Ligand
(Kcal/mol)
bonded residues are highlighted in bold)

1
R1
−57.257
PHE-218, LYS-246, VAL- 247, ILE- 250, VAL-298, LEU-301,

VAL-302, TYR- 303, THR- 304, ARG- 311

2
R2
−69.166
VAL- 174, PHE- 253, VAL- 256, VAL- 257, CYS- 260, PRO- 261,

ILE- 264

3
R8
−51.754
ILE- 250, PHE- 253, LEU- 254, MET- 258, LEU- 294, VAL- 298,

LEU- 301, VAL- 302

4
R11
−63.635
LEU- 3, VAL- 7, LEU- 254, VAL - 257, MET- 258, TRP-290, ILE-

291, LEU- 294, VAL- 298, LEU- 301

5
R12
−59.29
PHE-218, LYS-246, VAL- 247, ILE- 250, LEU- 254, VAL- 298,

LEU- 301, VAL-302, TYR- 303, THR- 304, ARG- 311

6
R18
−51.141
PHE-218, LYS-246, VAL- 247, ILE- 250, LEU- 254, VAL- 298,

LEU- 301, VAL-302, TYR- 303, THR- 304, ARG- 311

7
R22
−64.974
VAL- 247, ILE- 250, PHE- 253, LEU- 254, VAL - 257, VAL- 298,

LEU- 301, VAL-302, TYR- 303 THR- 304

8
R25-
−60.435
ILE- 250, LEU- 254, MET- 258, LEU- 294, VAL- 298, LEU- 301,

VAL- 302, TYR- 303, ARG- 311

9
R28
−59.733
PHE-218, LYS-246, VAL- 247, ILE- 250, LEU- 254, VAL - 257,

MET- 258, LEU- 294, VAL- 298, LEU- 301, VAL- 302, TYR- 303

10
R30
−59.664
PHE-218, VAL- 247, ILE- 250, LEU- 254, VAL - 257, MET- 258,

LEU- 294, VAL- 298, LEU- 301, VAL- 302, TYR- 303

11
R31
−67.961
VAL- 247, ILE- 250, PHE- 253, LEU- 254, VAL - 257, MET- 258,

LEU- 294, VAL- 298, LEU- 301, VAL- 302, TYR- 303, THR- 304

12
R32
−60.701
PHE-218, LYS-246, VAL- 247, ILE- 250, LEU- 254, LEU- 294,

VAL- 298, LEU- 301, VAL- 302, TYR- 303, THR- 304, ARG- 311

13
R34
−61.825
PHE-218, ILE- 250, PHE- 253, LEU- 254, VAL - 257, MET- 258,

LEU- 294, ALA-297, VAL- 298, LEU- 301, VAL- 302, TYR- 303,

THR- 304

14
R37
−66.094
PHE-218, VAL- 247, ILE- 250, PHE- 253, LEU- 254, VAL - 257,

VAL- 298, LEU- 301, VAL- 302, TYR- 303, THR- 304

15
R49
−73.165
PHE-218, LYS-246, VAL- 247, ILE- 250, LEU- 254, MET 258,

LEU- 294, VAL- 298, LEU- 301, VAL- 302, TYR- 303, THR- 304,

16
R51
−67.105
ILE- 250, LEU- 254, MET 258, LEU- 294, VAL- 298, LEU- 301,

VAL- 302, TYR- 303, ARG-311

17
R61
−59.475
LEU- 10, PHE-218, LYS-246, VAL- 247, ILE- 250, LEU- 294,

ALA- 297,, VAL- 298, LEU- 301, VAL- 302, TYR- 303, THR-

304,

18
R67
−86.806
VAL- 7, ILE- 250, LEU- 254, MET 258, ILE- 291, LEU- 294, VAL-

298, LEU- 301, VAL- 302, TYR- 303

TABLE 15

Predicted Antipsychotic activity of K004A derivatives

Compound
Pred. log
Pred.

S. No.
Name
IC50 (nM)
IC50 (nM)

1
11DR1
3.76
5754.40

2
11DR2
4.018
10423.17

3
11DR3
4.589
38815.04

4
11DR4
2.681
479.73

5
11DR5
2.843
696.63

6
11DR6
2.575
375.84

7
11DR7
2.178
150.66

8
11DR8
2.962
916.22

9
11DR9
1.515
32.73

10
11DR10
3.261
1823.90

11
11DR11
2.568
369.83

12
11DR12
3.692
4920.40

13
11DR13
3.438
2741.57

14
11DR14
3.559
3622.43

15
11DR15
3.154
1425.61

16
11DR16
3.359
2285.60

17
11DR17
2.082
120.78

18
11DR18
3.465
2917.43

19
11DR19
2.125
133.35

20
11DR20
2.393
247.17

21
11DR21
2.275
188.36

22
11DR23
2.219
165.58

23
11DR24
2.295
197.24

24
11DR25
3.729
5357.97

25
11DR26
2.439
274.79

26
11DR27
2.469
294.44

27
11DR28
2.131
135.21

28
11DR29
1.854
71.45

29
11DR32
3.377
2382.32

30
11DR34
1.58
38.02

31
11DR35
1.142
13.87

32
11DR36
2.821
662.22

33
11DR37
2.715
518.80

34
11DR38
3.104
1270.57

35
11DR39
1.052
11.27

36
11DR40
4.026
10616.96

37
11DR41
3.879
7568.33

38
11DR42
2.388
244.34

39
11DR43
2.895
785.24

40
11DR44
0.945
8.81

41
11DR45
3.331
2142.89

42
11DR45
3.331
2142.89

43
11DR46
2.147
140.28

44
11DR47
0.838
6.89

45
11DR48
1.672
46.99

46
11DR49
1.672
46.99

47
11DR50
3.297
1981.53

48
11DR51
2.482
303.39

49
11DR52
1.888
77.27

50
11DR53
1.97
93.33

51
11DR54-
0.633
4.30

52
11DR55
−0.669
0.21

53
11DR56
−2.278
0.01

54
11DR57
1.898
79.07

55
11DR58
2.383
241.55

56
11DR59
1.654
45.08

57
11DR60
2.208
161.44

58
11DR61
5.578
378442.58

59
11DR62
5.281
190985.33

TABLE 16

Predicted Antipsychotic activity of active K004A derivatives:-

COMPD
ACTIVITY
STATUS

11DR3
4.589
Close activity and drug likeness

11DR2
4.018
similar to Clozapine

11DR1
3.76

11DR12
3.692

11DR14
3.559

11DR18
3.465

11DR13
3.438

11DR16
3.359

11DR10
3.261

11DR15
3.154

11DR8
2.962
Moderate activity and druglikeness

11DR5
2.843
then Clozapine

11DR4
2.681

11DR6
2.575

11DR11
2.568

11DR20
2.393

11DR21
2.275

11DR7
2.178

11DR19
2.125

11DR17
2.082

11DR9-KOO4a
1.515
high activity but low drug likeness

to high extrapyramidal symptoms

similar to Haloperidol

TABLE 17

Details of binding affinity of K001A derivative and its binding

pocked residue docked on Dopamine D2 receptor (PDB ID: 2HLB)

Atoms of
A. A residue

Docking
Binding pocket residues(4 Å)
Ligand
involved in
Length of
No. of

S.

energy
(hydrogen bonded residues are
involved in
Docking
hydrogen
Hydrogen

No
Ligand
(Kcal/mol)
highlighted in bold)
Docking
interaction
bond (Å)
Bond (H)*

1
11DR1
−61.795
VAL-3, THR-4, TRP-
—
—
—
—

5, PHE-8, LEU-9

2
11DR2
−72.819
THR-4, TRP-5, TYR-
—
—
—
—

6, ASP-7

3
11DR3
−69.717
THR-4, TRP-5, TYR-
—
—
—
—

6, ASP-7

4
11DR4
−65.299
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9, GLU-11

5
11DR5
−63.64
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9, GLU-11

6
11DR6
−71.869
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-9

7
11DR7
−59.719
SER-1, ARG-2, VAL-
—
—
—
—

3, TRP-5, PHE-8, LEU-9

8
11DR8
−66.139
SER-1, ARG-2, VAL-
—
—
—
—

3, THR-4, TRP-5, PHE-

8, LEU-9, GLU-11

9
11DR9
−63.576
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-

9, GLU-11

10
11DR10
−61.781
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-9

11
11DR11
−47.804
VAL-3, THR-4, TYR-
—
—
—
—

4, TYR-6, ASP-7, MET-

10, GLU-11

12
11DR12
−68.987
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9, GLU-11

13
11DR13
−63.547
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9, GLU-11

14
11DR14
−58.85
VAL-3, THR-4, TRP-
—
—
—
—

5, PHE-8, LEU-9

15
11DR15
−52.104
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, GLU-11

16
11DR16
−62.946
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-

9, GLU-11

17
11DR17
−67.259
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9, GLU-11

18
11DR18
−53.191
SER-1, ARG-2, VAL-
—
—
—
—

3, TRP-5, PHE-8, LEU-

9, GLU-11

19
11DR19
−63.166
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9, GLU-11

20
11DR20
−63.154
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-9

21
11DR21
−64.436
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-9

22
11DR22
−62.243
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-9

23
11DR23
−59.626
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-9

24
11DR24
−72.687
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-9

25
11DR25
−64.582
VAL-3, THR-4, TRP-
—
—
—
—

5, PHE-8, LEU-9

26
11DR26
−69.857
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9, GLU-11

27
11DR27
−64.334
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-

9, GLU-11

28
11DR28
−64.689
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-

9, GLU-11

29
11DR29
−63.593
VAL-3, TRP-5, PHE-
—
—
—
—

8, LEU-9

30
11DR32
−67.877
SER-1, ARG-2, VAL-
—
—
—
—

3, THR-4, TRP-5, PHE-

8, LEU-9

31
110R34
−77.701
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-

9, GLU-11

32
11DR35
−72.083
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9

33
11DR36
−62.834
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9, GLU-11

34
11DR37
−53.372
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9

35
11DR38
−68.041
THR-4, TRP-5, TYR-
H58-
ASP7
2.149
1

6, ASP-7, MET-10
O2819

36
11DR39
−75.011
SER-1, ARG-2, VAL-
—
—
—
—

3, THR-4, TRP-5, PHE-

8, LEU-9

37
11DR40
−62.832
THR-4, TYR-6, ASP-7
—
—
—
—

38
11DR41
−51.854
SER-1, VAL-3, THR-4,
—
—
—
—

TRP-5, PHE-8, LEU-

9, GLU-11

39
11DR42
−72.925
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9, GLU-11

40
11DR43
−65.248
SER-1, ARG-2, VAL-3,
—
—
—
—

THR-4, TRP-5, PHE-

8, LEU-9

41
11DR44
−76.496
THR-4, TRP-5, TYR-
—
—
—
—

6, ASP-7

42
11DR45
−67.26
SER-1, VAL-3, THR-4,
—
—
—
—

TRP-5, PHE-8, LEU-

9, GLU-11

43
11DR46
−58.619
VAL-3, THR-4, TRP-
—
—
—
—

5, PHE-8, LEU-9

44
11DR47
−85.046
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-

9, GLU-11

45
11DR48
−55.769
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-9

46
11DR49
−81.656
SER-1, ARG-2, VAL-
—
—
—
—

3, TRP-5, PHE-8, LEU-

9, GLU-11

47
11DR50
−75.126
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, ASP-7, PHE-

8, LEU-9, GLU-11

48
11DR51
−79.976
THR-4, TRP-5, TYR-
—
—
—
—

6, ASP-7

49
11DR52
−96.417
SER-1, VAL-3, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

50
11DR53
−93.452
SER-1, VAL-3, THR-4,
—
—
—
—

TRP-5, PHE-8, LEU-

9, GLU-11

51
11DR54
−80.383
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, GLU-11

52
11DR55
−75.878
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-9

53
11DR56
−70.113
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, ASP-7, PHE-

8, LEU-9, GLU-11

54
11DR57
−82.35
SER-1, ARG-2, VAL-
—
—
—
—

3, THR-4, TRP-5, PHE-

8, LEU-9, GLU-11

55
11DR58
−65.203
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-

9, GLU-11

56
11DR59
−97.025
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9, GLU-

11, ASP-12

57
11DR60
−81.147
THR-4, TRP-5, TYR-
—
—
—
—

6, ASP-7, LEU-9, MET-10

58
11DR61
−71.392
SER-1, VAL-3, TRP-
—
—
—
—

5, PHE-8, LEU-9, GLU-11

59
11DR62
−80.729
SER-1, VAL-3, THR-
—
—
—
—

4, TRP-5, PHE-8, LEU-

9, GLU-11

TABLE 18

Details of binding affinity of K001A derivatives and its binding pocked residue

docked on Serotonin receptor (5HT_2A) (developed homology based 3D model)

Atoms of
A. A residue

Docking
Binding pocket residues(4 Å)
Ligand
involved in
Length of
No. of

S.

energy
(hydrogen bonded residues are
involved in
Docking
hydrogen
Hydrogen

No
Ligand
(Kcal/mol)
highlighted in bold)
Docking
interaction
bond (Å)
Bond (H)*

1
11DR1
−6.079
PHE-167, LEU-170, THR-
—
—
—
—

171, VAL-174, VAL-

256, VAL-257, CYS-

260, PRO-261, ILE-264

2
11DR2
−17.064
PHE-218, ILE-250, LEU-
—
—
—
—

254, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

3
11DR3
−16.508
ILE-250, LEU-254, MET-
—
—
—
—

258, LEU-294, VAL-

302, TYR-303

4
11DR7
−20.691
ILE-250, LEU-254, MET-
—
—
—
—

258, LEU-294, VAL-

298, LEU-301, VAL-

302, TYR-303

5
11DR9
−2.499
ILE-250, LEU-254, MET-
—
—
—
—

258, LEU-294, VAL-

298, LEU-301, VAL-

302, TYR-303, THR-

303, THR-304, ARG-311

6
11DR10
−21.213
PHE-218, VAL-247, ILE-
H5124-
VAL-302
2.166
1

250, LEU-254, LEU-
O332

294, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

7
11DR11
−8.217
ILE-250, LEU-254, LEU-
—
—
—
—

294, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

8
11DR12
−10.814
LEU-10, LEU-254, MET-
—
—
—
—

258, LEU-294, ALA-

297, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

9
11DR13
−6.947
ILE-250, LEU-254, LEU-
—
—
—
—

298, LEU-301, VAL-

302, TYR-303

10
11DR14
−1.591
ILE-250, LEU-254, LEU-
—
—
—
—

294, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

11
11DR16
−5.436
LEU-170, VAL-174, ILE-
—
—
—
—

250, PHE-253, LEU-

254, VAL-256, VAL-

257, CYS-260, PRO-

261, ILE-264

12
11DR18
−11.896
PHE-218, LYS-246, VAL-
—
—
—
—

247, ILE-250, LEU-

254, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

13
11DR20
−0.43
PHE-218, LYS-246, VAL-
—
—
—
—

247, ILE-250, LEU-

294, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

14
11DR21
−6.473
ILE-250, PHE-253, LEU-
—
—
—
—

254, LEU-294, VAL-

298, LEU-301, VAL-

302, TYR-303

15
11DR22
−6.754
PHE-218, ALA-244, LYS-
—
—
—
—

246, VAL-247, LEU-

248, GLY-249, ILE-

250, VAL-251, PHE-

252, PHE-253, LEU-

254, PHE-255, VAL-

256, VAL-257, MET-

258, LEU-294, SER-

295, ALA-297, VAL-

298, ASN-299, PRO-

300, LEU-301, VAL-

302, TYR-303, THR-

304, LEU-305, LYS-

308, ARG-311

16
11DR23
−2.36
VAL-247, ILE-250, PHE-
H5130-
VAL-302
2.197
1

253, LEU-254, VAL-
O2332

257, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

17
11DR25
−26.013
PHE-218, LYS-246, VAL-
—
—
—
—

247, ILE-250, LEU-

294, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

18
11DR27
−14.701
PHE-218, LYS-246, VAL-
H5129-
VAL-302
2.028
1

247, ILE-250, PHE-
O2332

253, LEU-254, VAL-

257, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304

19
11DR29
−17.329
PHE-218, LYS-246, VAL-

247, ILE-250, LEU-

294, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

20
11DR32
−20.914
PHE-218, LYS-246, VAL-
H5127-
VAL-302
1.911
1

247, ILE-250, LEU-
O2332

294, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

21
11DR37
−2.174
PHE-218, LYS-246, VAL-
—
—
—
—

247, ILE-250, LEU-

254, LEU-294, VAL-

298, LEU-301, VAL-

302, TYR-303, THR-304

22
11DR40
−16.613
PHE-218, LYS-246, VAL-
—
—
—
—

247, ILE-250, LEU-

254, LEU-294, VAL-

298, LEU-301, VAL-

302, TYR-303, THR-

304, ARG-311

23
11DR41
−1.019
PHE-218, LYS-246, VAL-
—
—
—
—

247, ILE-250, LEU-

254, LEU-294, VAL-

298, LEU-301, VAL-

302, TYR-303, THR-

304, ARG-311

24
11DR44
−15.899
VAL-7, LEU-10, ILE-
—
—
—
—

250, LEU-254, LEU-

294, VAL-298, LEU-

301, VAL-302, TYR-303

25
11DR45
−15.568
ILE-250, LEU-254, LEU-
—
—
—
—

294, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304, ARG-311

26
11DR51
−12.337
PHE-218, ILE-250, LEU-
—
—
—
—

254, MET-258, LEU-

294, VAL-298, LEU-

301, VAL-302, TYR-

303, ARG-311

27
11DR52
−11.411
ILE-250, PHE-253, LEU-
—
—
—
—

254, VAL-256, VAL-

257, VAL-298, LEU-

301, VAL-302

28
11DR53
−18.745
PHE-218, LYS-246, VAL-
—
—
—
—

247, ILE-250, PHE-

243, LEU-254, VAL-

298, LEU-301, VAL-

302, TYR-303, THR-

304, ARG-311

29
11DR58
−4.16
PHE-218, LYS-246, VAL-
—
—
—
—

247, ILE-250, LEU-

294, VAL-298, LEU-

301, VAL-302, TYR-

303, THR-304

30
11DR60
−11.966
PHE-218, ILE-250, LEU-
—
—
—
—

254, MET-258, LEU-

294, VAL-298, LEU-

301, VAL-302, TYR-

303, ARG-311

TABLE 19

Predicted antipsychotic activity of K004B derivatives

Compound
Pred. log
Pred.

S. No.
Name
IC50 (nM)
IC50 (nM)

1
10DR1
3.6
3981.07

2
10DR2
4.037
10889.30

3
10DR3
4.491
30974.19

4
10DR4
2.618
414.95

5
10DR5
2.724
529.66

6
10DR6
2.582
381.94

7
10DR7
2.195
156.68

8
10DR8
2.149
140.93

9
10DR9
1.148
14.06

10
10DR10
3.12
1318.26

11
10DR11
2.484
304.79

12
10DR12
3.525
3349.65

13
10DR13
3.374
2365.92

14
10DR14
3.122
1324.34

15
10DR15
2.753
566.24

16
10DR16
3.509
3228.49

17
10DR17
1.972
93.76

18
10DR18
3.183
1524.05

19
10DR19
1.826
66.99

20
10DR20
2.264
183.65

21
10DR21
2.456
285.76

22
10DR22
Failed
#VALUE!

23
10DR23
1.903
79.98

24
10DR24
2.072
118.03

25
10DR25
3.585
3845.92

26
10DR26
2.966
924.70

27
10DR27
2.335
216.27

28
10DR28
2.104
127.06

29
10DR29
2.168
147.23

30
10DR30
1.788
61.38

31
10DR31
1.364
23.12

32
10DR32
3.274
1879.32

33
10DR33
3.626
4226.69

34
10DR34
1.147
14.03

35
10DR35
1.091
12.33

36
10DR36
3.174
1492.79

37
10DR37
3.207
1610.65

38
10DR38
2.388
244.34

39
10DR39
1.618
41.50

40
10DR40
4.009
10209.39

41
10DR41
3.993
9840.11

42
10DR42
1.935
86.10

43
10DR43
3.161
1448.77

44
10DR44
1.053
11.30

45
10DR45
3.863
7294.58

46
10DR46
2.715
518.80

47
10DR47
1.513
32.58

48
10DR48
2.341
219.28

49
10DR49
0.982
9.59

50
10DR50
9.397
2494594726.94

51
10DR52
2.083
121.06

52
10DR53
2.175
149.62

53
10DR54
1.451
28.25

54
10DR55
0.571
3.72

55
10DR56
−0.757
0.17

56
10DR57
−2.565
0.00

57
10DR58
2.024
105.68

58
10DR59
2.96
912.01

59
10DR60
1.246
17.62

60
10DR61
5.725
530884.44

61
10DR62
5.718
522396.19

TABLE 20

Predicted antipsychotic activity of active K004B derivatives

COMPD
ACTIVITY
STATUS

10DR52
2.083
Moderate activity and druglikeness

10DR4

text missing or illegible when filed

then Clozapine

10DR5
2.724

10DR6
2.582

10DR7
2.195

10DR8

text missing or illegible when filed

10DR15
2.753

10DR20
2.264

10DR21

text missing or illegible when filed

10DR24
2.072

10DR26
2.966

10DR27
2.335

10DR28
2.104

10DR29
2.168

10DR48
2.341

10DR53
2.175

10DR58
2.024

10DR59
2.96

10DR38
2.388

10DR11
2.484

10DR15
2.753

10DR46
2.715

10DR1
3.6
Close activity and drug likeness

10DR10
3.12
similar to Clozapine

10DR12

text missing or illegible when filed

10DR13
3.374

10DR14

text missing or illegible when filed

10DR16

10DR18
3.183

10DR2 text missing or illegible when filed

10DR32
3.274

10DR33
3.626

10DR3 text missing or illegible when filed

3.174

10DR37
3.207

10DR4 text missing or illegible when filed

10DR4

10DR30
1.788
High activity but low druglikeness

10DR31
1.364
dur to high extrapyramidal symptoms

10DR34
1.147
similar to Haloperidol

10DR35
1.091

10DR39
1.618

10DR42
1.935

10DR44
1.053

10DR47
1.513

10DR49
0.982

text missing or illegible when filed

indicates data missing or illegible when filed

TABLE 21

Details of binding affinity of K001B derivative and its binding

pocked residue docked on dopamine D2 receptor (PDB ID: 2HLB)

Atoms of
A. A residue

Docking
Binding pocket residues(4 Å)
Ligand
involved in
Length of
No. of

S.

energy
(hydrogen bonded residues are
involved in
Docking
hydrogen
Hydrogen

No
Ligand
(Kcal/mol)
highlighted in bold)
Docking
interaction
bond (Å)
Bond (H)*

1
10DR1
−54.256
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, GLU-11

2
10DR2
−59.485
SER-1, ARG-2, VAL-3, THR-4,
—
—
—
—

TRP-5, PHE-8, LEU-9, GLU-11

3
10DR3
−60.806
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

4
10DR4
−61.648
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

5
10DR5
−54.421
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

6
10DR6
−66.344
ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9,

7
10DR7
−55.317
ARG-2, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9,

8
10DR8
−69.016
VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

9
10DR9
−67.036
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

10
10DR10
−52.208
TRP-5, PHE-8, LEU-9,
—
—
—
—

11
10DR11
−63.164
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

12
10DR12
−57.867
THR-4, TRP-5, TYR-6, ASP-7.
—
—
—
—

13
10DR13
−49.082
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

14
10DR14
−58.552
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

15
10DR15
−60.199
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

16
10DR16
−57.114
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

17
10DR17
−53.508
TRP-5, PHE-8, LEU-9,
—
—
—
—

18
10DR18
−59.959
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

19
10DR19
−62.664
VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

20
10DR20
−58.49
TRP-5, PHE-8, LEU-9,
—
—
—
—

21
10DR21
−57.242
TRP-5, PHE-8, LEU-9,
—
—
—
—

22
10DR22
−60.864
TRP-5, PHE-8, LEU-9,
—
—
—
—

23
10DR23
−61.553
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

24
10DR24
−71.77
ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9,

25
10DR25
−56.196
, TRP-5, PHE-8, LEU-9,
—
—
—
—

26
10DR26
−71.503
VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9,

27
10DR27
−60.27
VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

28
10DR28
−52.616
VAL-3, THR-4, TYR-6, ASP-7
—
—
—
—

29
10DR29
−63.877
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

30
10DR30
−59.435
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

31
10DR31
−51.715
VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

32
10DR32
−57.668
ARG-2, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9,

33
10DR33
−62.921
SER-1, ARG-2, VAL-3, TRP-5,
—
—
—
—

PHE-8, LEU-9,

34
10DR34
−74.696
VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9,

35
10DR35
−69.426
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9,

36
10DR36
−66.647
SER-1, ARG-2, VAL-3, TRP-5,
—
—
—
—

PHE-8, LEU-9,

37
10DR37
−52.032
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

38
10DR38
−63.825
VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

GLU-11

39
10DR39
−62.321
ARG-2, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9.

40
10DR40
−59.813
VAL-3, THR-4, TYR-6, ASP-7.
H51-
ASP-7
1.803
1

O2818

41
10DR41
−48.192
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

42
10DR42
−60.415
TRP-5, PHE-8, LEU-9,
—
—
—
—

43
10DR43
−63.265
TRP-5, PHE-8, LEU-9,
—
—
—
—

44
10DR44
−62.356
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

45
10DR45
−57.073
VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9,

46
10DR46
−55.968
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

47
10DR47
−72.195
TRP-5, PHE-8, LEU-9,
—
—
—
—

48
10DR48
−61.966
VAL-3, TRP-5, PHE-8, LEU-9,
—
—
—
—

49
10DR49
−73.055
TRP-5, PHE-8, LEU-9,
—
—
—
—

50
10DR50
−92.213
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

51
10DR52
−72.794
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

PHE-8, LEU-9, GLU-11

52
10DR53
−74.686
SER-1, VAL-3, TRP-5, ASP-7,
—
—
—
—

PHE-8, LEU-9, GLU-11

53
10DR54
−70.084
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

54
10DR55
−71.383
TRP-5, TYR-6, ASP-7.
—
—
—
—

55
10DR56
−77.099
SER-1, VAL-3, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

56
10DR57
−71.858
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

ASP-7, PHE-8, LEU-9, GLU-11

57
10DR58
−92.598
THR-4, TRP-5, TYR-6, ASP-7,,
—
—
—
—

LEU-9, MET-10,

58
10DR59
−71.793
SER-1, ARG-2, VAL-3, THR-4,
—
—
—
—

TRP-5, PHE-8, LEU-9, GLU-11

59
10DR60
−70.685
VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9,

60
10DR61
−78.893
VAL-3, THR-4, TRP-5, PHE-8,
—
—
—
—

LEU-9, GLU-11

61
10DR62
−59.384
SER-1, VAL-3, THR-4, TRP-5,
—
—
—
—

ASP-7, PHE-8, GLU-11

TABLE 22

Details of binding affinity of K001B derivatives and its binding pocked residue

docked on Serotonin receptor (5HT_2A) (developed homology based 3D model)

Docking energy
Binding pocket residues(4 Å) (hydrogen

S. No
Ligand
(Kcal/mol)
bonded residues are highlighted in bold)

1
10DR1
−18.993
PHE-218, ILE-250, LEU-254, VAL-298, LEU-301, VAL-302,

TYR-303, THR-304, ARG-311

2
10DR2
−34.042
LEU-170, VAL-174, PHE-178, PHE-253, VAL-256, VAL-257,

CYS-260, ILE-264,

3
10DR3
−17.39
PHE-218, ILE-250, LEU-254, VAL-298, LEU-301, VAL-302,

TYR-303, THR-304, ARG-311.

4
10DR5
−18.799
PHE-218, ILE-250, LEU-254, MET-258, LEU-294, VAL-298,

LEU-301, VAL-302, TYR-303, ARG-311

5
10DR6
−17.605
PHE-218, LYS-246, VAL-247, ILE-250, PHE-253, LEU-254,

VAL-257, VAL-298, LEU-301, VAL-302,

6
10DR10
−12.088
PHE-218, LYS-246, VAL-247, ILE-250, VAL-298, LEU-301,

VAL-302, TYR-303, THR-304,

7
10DR11
−12.499
ILE-250, LEU-254, MET-258, LEU-294, VAL-298, LEU-301,

VAL-302, TYR-303, ARG-311

8
10DR12
−14.863
PHE-218, VAL-247, ILE-250, LEU-254, VAL-298, LEU-301,

VAL-302, TYR-303, THR-304, ARG-311

9
10DR15
−15.743
PHE-218, VAL-247, ILE-250, LEU-254, MET-258, LEU-294,

VAL-298, LEU-301, VAL-302, TYR-303, THR-304, ARG-311

10
10DR18
−27.8
LEU-170, VAL-174, PHE-178, ILE-181, LYS-182, LYS-246,

ILE-250, PHE-253, LEU-254, VAL-256, VAL-257,

11
10DR21
−9.594
PHE-218, ILE-250, LEU-254, LEU-294, VAL-298, LEU-301,

VAL-302, TYR-303, ARG-311

12
10DR22
−15.776
PHE-218, ILE-250, PHE-253, LEU-254, VAL-298, LEU-301,

VAL-302,

13
10DR25
−14.016
PHE-218, LYS-246, VAL-247, ILE-250, VAL-298, LEU-301,

VAL-302, TYR-303, THR-304,

14
10DR32
−18.85
PHE-218, LYS-246, VAL-247, ILE-250, PHE-253, LEU-254,

VAL-257, VAL-298, LEU-301, VAL-302, THR-304,

15
10DR37
−9.008
PHE-218, LYS-246, VAL-247, ILE-250, VAL-298, LEU-301,

VAL-302, TYR-303, THR-304,

16
10DR39
−13.033
VAL-7, ILE-250, PHE-253, LEU-254, MET-258, LEU-294,

VAL-298, LEU-301, VAL-302.

17
10DR41
−12.992
PHE-218, LYS-246, VAL-247, ILE-250, PHE-253, LEU-254

VAL-298, LEU-301, VAL-302, THR-304,

18
10DR42
−21.486
PHE-218, ILE-250, LEU-254, VAL-298, LEU-301, VAL-302,

TYR-303, THR-304, ARG-311,

19
10DR44
−12.497
PHE-218, VAL-247, ILE-250, PHE-253, LEU-254, VAL-298,

LEU-301, VAL-302, TYR-303, THR-304, ARG-311,

20
10DR45
−17.724
PHE-218, VAL-247, ILE-250, LEU-254, VAL-298, LEU-301,

VAL-302, TYR-303, THR-304, ARG-311,

21
10DR48
−45.775
VAL-174, PHE-178, PHE-253, LEU-254, VAL-256, VAL-257,

CYS-260, PRO-261, ILE-264,

22
10DR49
−13.453
ILE-250, LEU-254, MET-258, ILE-291, LEU-294, VAL-298,

LEU-301, VAL-302, TYR-303, THR-304,

23
10DR52
−12.663
ILE-250, LEU-254, MET-258, TRP-290, ILE-291, LEU-294,

VAL-298, LEU-301, VAL-302, TYR-303,

24
10DR58
−16.669
VAL-7, LEU-10, PHE-218, LYS-246, VAL-247, ILE-250, LEU-

294, VAL-298, LEU-301, VAL-302. TYR-303, THR-304.

25
10DR60
−10.881
LEU-10, PHE-218, LYS-246, VAL-247, ILE-250, LEU-294, LEU-

301, VAL-302. TYR-303, THR-304, ARG-311.

26
10DR62
−4.427
VAL-7, LEU-254, MET-258, TRP-290, ILE-291, LEU-294, VAL-

298, LEU-301, VAL-302.

TABLE 23

Toxicity Risks Assessment, drug likeness and drug score of Yohimbane alkaloids derivatives

Toxicity risks

MUT
TUMO
IRRI
REP
Parameters
Drug Likeness

Compound
(Mutagencity)
Tumorogencity
(Irritation)
(Reproduction)
MW
CLP
S
D-L
D-S

Yohimbine
No Risk
No Risk
No Risk
No Risk
354
2.44
−3.06
1.0
0.72

Halopreidol
No Risk
No Risk
No Risk
No Risk
373
5.41
−4.55
7.59
0.51

Clozapine
No Risk
No Risk
No Risk
No Risk
326
3.0
−3.74
8.7
0.79

Risperidone
No Risk
No Risk
No Risk
No Risk
410
3.37
−4.32
4.43
0.66

Ziprasidone
High Risk
No Risk
No Risk
No Risk
412
2.46
−3.89
8.71
0.44

KOO1
No Risk
No Risk
No Risk
No Risk
354
2.44
−3.06
1.0
0.72

KOO1A
No Risk
No Risk
No Risk
No Risk
396
2.93
−3.47
0.99
0.66

KOO1B
No Risk
No Risk
No Risk
No Risk
574
4.22
−5.07
1.63
0.37

KOO1C
High Risk
No Risk
No Risk
No Risk
503
4.28
−5.1
−5.62
0.14

KOO1D
No Risk
No Risk
No Risk
No Risk
458
4.41
−4.64
0.94
0.46

KOO1E
High Risk
No Risk
No Risk
No Risk
503
4.28
−5.1
−13.69
0.14

KOO1F
No Risk
No Risk
No Risk
No Risk
484
4.53
−5.01
−2.56
0.2

KOO1G
No Risk
No Risk
No Risk
No Risk
522
7.97
−6.19
−19.0
0.12

KOO6
No Risk
No Risk
No Risk
No Risk
352
2.2
−3.14
2.28
0.8

KOO3
No Risk
No Risk
No Risk
No Risk
382
2.09
−3.16
2.51
0.79

KOO5
No Risk
No Risk
No Risk
No Risk
412
1.98
−3.18
2.9
0.77

KOO2
No Risk
No Risk
No Risk
No Risk
412
1.98
−3.18
2.9
0.77

KOO4A
No Risk
No Risk
No Risk
No Risk
382
2.09
−3.16
2.51
0.79

KOO4B
No Risk
No Risk
No Risk
No Risk
382
2.09
−3.16
2.51
0.79

Y1
No Risk
No Risk
No Risk
No Risk
354
2.45
−3.21
3.04
0.81

Y2
No Risk
No Risk
No Risk
No Risk
396
2.94
−3.61
3.09
0.74

Y3
No Risk
No Risk
No Risk
No Risk
410
3.4
−3.89
3.86
0.69

Y4
No Risk
No Risk
No Risk
No Risk
467
3.32
−4.26
2.69
0.6

Y5
No Risk
No Risk
No Risk
No Risk
501
4.4
−5.13
4.31
0.45

Y6
No Risk
No Risk
Medium Risk
No Risk
505
5.12
−5.85
4.39
0.28

Y7
No Risk
No Risk
No Risk
No Risk
549
5.2
−5.95
2.26
0.3

Y8
No Risk
No Risk
No Risk
No Risk
485
4.29
−4.93
4.05
0.49

Y9
No Risk
No Risk
No Risk
No Risk
507
6.14
−5.53
−14.1
0.16

Y10
No Risk
No Risk
No Risk
No Risk
437
3.82
−4.18
4.22
0.62

Y11
No Risk
No Risk
High Risk
No Risk
480
5.69
−5.12
−10.9
0.11

Y12
No Risk
No Risk
No Risk
No Risk
438
4.23
−4.42
−0.84
0.38

Y13
No Risk
No Risk
High Risk
No Risk
452
4.63
−4.47
1.54
0.39

Y14
No Risk
No Risk
High Risk
No Risk
452
4.76
−4.58
−3.29
0.16

Y15
No Risk
No Risk
High Risk
No Risk
466
5.22
−4.85
−6.48
0.13

Y16
No Risk
No Risk
No Risk
No Risk
452
4.38
−4.53
−22.5
0.27

Y17
No Risk
No Risk
No Risk
No Risk
483
1.5
−3.47
5.14
0.69

Y18
No Risk
No Risk
No Risk
No Risk
467
2.41
−3.76
0.68
0.57

Y19
No Risk
No Risk
No Risk
No Risk
468
0.5
−3.27
−1.95
0.41

Y20
No Risk
No Risk
No Risk
No Risk
496
0.52
−3.31
−1.59
0.41

Y21
No Risk
No Risk
No Risk
No Risk
497
1.08
−3.24
−4.24
0.35

Y22
Medium Risk
No Risk
No Risk
High Risk
485
2.28
−4.18
2.52
0.16

Y23
No Risk
No Risk
No Risk
No Risk
517
−0.84
−3.15
1.38
0.61

Y25
No Risk
No Risk
No Risk
No Risk
453
2.01
−3.38
−0.91
0.47

Y26
No Risk
No Risk
No Risk
No Risk
519
1.54
−3.32
−1.43
0.39

Y27
No Risk
No Risk
No Risk
No Risk
495
3.21
−4.19
−5.3
0.3

Y28
No Risk
No Risk
No Risk
No Risk
465
4.57
−4.72
3.34
0.5

Y30
No Risk
No Risk
No Risk
No Risk
499
2.33
−3.9
1.47
0.58

Y31
No Risk
No Risk
No Risk
No Risk
529
3.4
−4.48
−3.08
0.28

Y32
No Risk
No Risk
No Risk
No Risk
469
1.04
−3.2
1.29
0.65

Y33
No Risk
No Risk
No Risk
No Risk
497
1.86
−3.63
−3.72
0.34

Y34
No Risk
No Risk
No Risk
No Risk
568
3.47
−5.0
−1.06
0.28

Y36
No Risk
No Risk
No Risk
No Risk
545
3.1
−4.18
−0.57
0.37

Y37
No Risk
No Risk
No Risk
No Risk
481.0
2.92
−3.78
−1.45
0.39

Y38
No Risk
No Risk
High Risk
No Risk
479
4.5
−4.55
2.28
0.29

Y40
No Risk
No Risk
No Risk
No Risk
425
1.94
−3.13
4.77
0.78

Y41
No Risk
No Risk
No Risk
No Risk
439
2.35
−3.51
4.74
0.73

Y43
No Risk
No Risk
No Risk
No Risk
497
1.85
−3.49
1.93
0.63

Y44
No Risk
No Risk
No Risk
No Risk
559
3.38
−4.48
3.09
0.49

Y45
No Risk
No Risk
No Risk
No Risk
453
2.0
−3.24
1.13
0.65

Y46
No Risk
No Risk
No Risk
No Risk
509
3.67
−4.32
4.07
0.54

Y47
No Risk
No Risk
No Risk
No Risk
529
3.39
−4.34
4.72
0.54

Y48
No Risk
No Risk
No Risk
No Risk
525
527
−6.32
3.78
0.31

Y50
No Risk
No Risk
No Risk
No Risk
526
5.64
−6.26
3.06
0.29

TABLE 24

Screening of yohimbane alkaloids derivatives through Lipinski rule of five

Group

Rule
Molec-

Chemical
Molec-

Group
Count
Group
Atom
Atom
of 5
ular

H-bond
H-bond

Sample
ular

Count
(sec-
Count
Count
Count
viola-
weight >
LogP >
donors >
acceptors >

Name
Weight
Log P
(amine)
amine)
(hydroxyl)
(nitrogen)
(oxygen)
tions
500
5
5
10

10DR1
368.432
1.774
0
1
1
2
4
0
0
0
0
0

10DR2
354.405
1.742
0
1
1
2
4
0
0
0
0
0

10DR3
368.432
1.774
0
1
0
2
4
0
0
0
0
0

10DR4
439.553
2.058
0
2
1
3
4
0
0
0
0
0

10DR5
473.571
2.584
0
2
0
3
4
0
0
0
0
0

10DR6
477.99
3.355
0
2
0
3
3
0
0
0
0
0

10DR7
522.44
3.629
0
2
0
3
3
1
0.045
0
0
0

10DR8
457.571
2.932
0
2
0
3
3
0
0
0
0
0

10DR9
479.661
3.948
0
2
0
3
3
0
0
0
0
0

10DR10
409.527
1.966
0
2
0
3
3
0
0
0
0
0

10DR11
452.592
3.805
0
1
0
2
4
0
0
0
0
0

10DR12
410.512
2.561
0
1
0
2
4
0
0
0
0
0

10DR13
424.539
3.019
0
1
0
2
4
0
0
0
0
0

10DR14
424.539
3.013
0
1
0
2
4
0
0
0
0
0

10DR15
438.566
3.409
0
1
0
2
4
0
0
0
0
0

10DR16
424.539
2.639
0
1
0
2
4
0
0
0
0
0

10DR17
455.51
0.773
0
2
1
3
6
0
0
0
0
0

10DR18
439.51
1.235
0
2
0
3
5
0
0
0
0
0

10DR19
482.578
0.605
1
2
0
4
5
0
0
0
0
0

10DR20
482.535
−0.25
0
2
0
4
6
0
0
0
0
0

10DR21
483.52
0.615
0
2
0
3
7
0
0
0
0
0

10DR22
470.562
1.018
0
2
0
3
5
0
0
0
0
0

10DR23
497.547
0.867
0
2
0
3
7
0
0
0
0
0

10DR24
496.562
0.002
0
2
0
4
6
0
0
0
0
0

10DR25
425.483
0.697
0
2
0
3
5
0
0
0
0
0

10DR26
505.572
0.361
0
3
0
5
5
1
0.011
0
0
0

10DR27
481.591
2.502
0
2
0
3
5
0
0
0
0
0

10DR28
481.591
2.43
0
2
0
3
5
0
0
0
0
0

10DR29
496.605
1.001
1
2
0
4
5
0
0
0
0
0

10DR30
499.624
1.222
0
2
0
3
5
0
0
0
0
0

10DR31
515.608
2.92
0
2
0
3
5
1
0.031
0
0
0

10DR32
455.51
0.449
0
2
1
3
6
0
0
0
0
0

10DR33
469.536
0.862
0
2
1
3
6
0
0
0
0
0

10DR34
554.644
2.229
0
3
0
4
5
1
0.109
0
0
0

10DR35
531.607
2.636
0
2
1
3
6
1
0.063
0
0
0

10DR36
467.564
2.106
0
2
0
3
5
0
0
0
0
0

10DR37
453.537
0.841
0
2
0
3
5
0
0
0
0
0

10DR38
467.564
1.254
0
2
0
3
5
0
0
0
0
0

10DR39
515.608
2.431
0
2
0
3
5
1
0.031
0
0
0

10DR40
411.5
0.712
0
2
1
3
4
0
0
0
0
0

10DR41
425.527
1.125
0
2
1
3
4
0
0
0
0
0

10DR42
473.571
2.302
0
2
1
3
4
0
0
0
0
0

10DR43
483.563
0.894
0
2
1
3
6
0
0
0
0
0

10DR44
501.624
3.312
0
2
1
3
4
1
0.003
0
0
0

10DR45
395.5
1.498
0
2
0
3
3
0
0
0
0
0

10DR46
495.617
2.534
0
2
0
3
5
0
0
0
0
0

10DR47
529.635
2.952
0
2
0
3
5
1
0.059
0
0
0

10DR48
512.435
3.873
0
2
0
3
3
1
0.025
0
0
0

10DR49
541.43
4.506
0
1
0
2
5
1
0.083
0
0
0

10DR50
562.618
2.712
0
1
0
2
8
1
0.125
0
0
0

10DR52
438.522
2.581
0
1
0
2
5
0
0
0
0
0

10DR53
517.537
3.423
0
1
0
3
7
1
0.035
0
0
0

10DR54
531.564
3.356
0
1
0
3
7
1
0.063
0
0
0

10DR55
498.577
3.878
0
1
0
2
5
0
0
0
0
0

10DR56
550.737
5.752
0
1
0
2
5
2
0.101
1
0
0

10DR57
606.844
7.337
0
1
0
2
5
2
0.214
1
0
0

10DR58
502.566
3.217
0
1
0
2
6
1
0.005
0
0
0

10DR59
452.549
3.413
0
1
0
2
5
0
0
0
0
0

10DR60
497.549
3.506
0
1
0
3
5
0
0
0
0
0

10DR61
530.574
0.31
0
1
4
2
9
2
0.061
0
0
1

10DR62
530.574
0.31
0
1
4
2
9
2
0.061
0
0
1

11DR1
368.432
1.774
0
1
1
2
4
0
0
0
0
0

11DR2
354.405
1.742
0
1
1
2
4
0
0
0
0
0

11DR3
368.432
1.774
0
1
0
2
4
0
0
0
0
0

11DR4
439.553
2.058
0
2
1
3
4
0
0
0
0
0

11DR5
473.571
2.584
0
2
0
3
4
0
0
0
0
0

11DR6
477.99
3.355
0
2
0
3
3
0
0
0
0
0

11DR7
522.44
3.629
0
2
0
3
3
1
0.045
0
0
0

11DR8
457.571
2.932
0
2
0
3
3
0
0
0
0
0

11DR9
479.661
3.948
0
2
0
3
3
0
0
0
0
0

11DR10
409.527
1.966
0
2
0
3
3
0
0
0
0
0

11DR11
452.592
3.805
0
1
0
2
4
0
0
0
0
0

11DR12
410.512
2.561
0
1
0
2
4
0
0
0
0
0

11DR13
424.539
3.019
0
1
0
2
4
0
0
0
0
0

11DR14
424.539
3.013
0
1
0
2
4
0
0
0
0
0

11DR15
438.566
3.409
0
1
0
2
4
0
0
0
0
0

11DR16
424.539
2.639
0
1
0
2
4
0
0
0
0
0

11DR17
455.51
0.773
0
2
1
3
6
0
0
0
0
0

11DR18
439.51
1.235
0
2
0
3
5
0
0
0
0
0

11DR19
482.578
0.605
1
2
0
4
5
0
0
0
0
0

11DR20
482.535
−0.25
0
2
0
4
6
0
0
0
0
0

11DR21
483.52
0.615
0
2
0
3
7
0
0
0
0
0

11DR22
470.562
1.018
0
2
0
3
5
0
0
0
0
0

11DR23
497.547
0.867
0
2
0
3
7
0
0
0
0
0

11DR24
496.562
0.002
0
2
0
4
6
0
0
0
0
0

11DR25
425.483
0.697
0
2
0
3
5
0
0
0
0
0

11DR26
505.572
0.361
0
3
0
5
5
1
0.011
0
0
0

11DR27
481.591
2.502
0
2
0
3
5
0
0
0
0
0

11DR28
481.591
2.43
0
2
0
3
5
0
0
0
0
0

11DR29
496.605
1.001
1
2
0
4
5
0
0
0
0
0

11DR32
455.51
0.449
0
2
1
3
6
0
0
0
0
0

11DR34
554.644
2.229
0
3
0
4
5
1
0.109
0
0
0

11DR35
531.607
2.636
0
2
1
3
6
1
0.063
0
0
0

11DR36
467.564
2.106
0
2
0
3
5
0
0
0
0
0

11DR37
453.537
0.841
0
2
0
3
5
0
0
0
0
0

11DR38
467.564
1.254
0
2
0
3
5
0
0
0
0
0

11DR39
515.608
2.431
0
2
0
3
5
1
0.031
0
0
0

11DR40
411.5
0.712
0
2
1
3
4
0
0
0
0
0

11DR41
425.527
1.125
0
2
1
3
4
0
0
0
0
0

11DR42
473.571
2.302
0
2
1
3
4
0
0
0
0
0

11DR43
483.563
0.894
0
2
1
3
6
0
0
0
0
0

11DR44
545.634
2.668
0
2
1
3
6
1
0.091
0
0
0

11DR45
439.51
0.729
0
2
0
3
5
0
0
0
0
0

11DR46
495.617
2.534
0
2
0
3
5
0
0
0
0
0

11DR47
529.635
2.952
0
2
0
3
5
1
0.059
0
0
0

11DR48
512.435
3.873
0
2
0
3
3
1
0.025
0
0
0

11DR49
541.43
4.506
0
1
0
2
5
1
0.083
0
0
0

11DR50
562.618
2.712
0
1
0
2
8
1
0.125
0
0
0

11DR51
438.522
2.581
0
1
0
2
5
0
0
0
0
0

11DR52
517.537
3.423
0
1
0
3
7
1
0.035
0
0
0

11DR53
531.564
3.356
0
1
0
3
7
1
0.063
0
0
0

11DR54
498.577
3.878
0
1
0
2
5
0
0
0
0
0

11DR55
550.737
5.752
0
1
0
2
5
2
0.101
1
0
0

11DR56
606.844
7.337
0
1
0
2
5
2
0.214
1
0
0

11DR57
502.566
3.217
0
1
0
2
6
1
0.005
0
0
0

11DR58
452.549
3.413
0
1
0
2
5
0
0
0
0
0

11DR59
497.549
3.506
0
1
0
3
5
0
0
0
0
0

11DR60
502.566
3.217
0
1
0
2
6
1
0.005
0
0
0

11DR61
530.574
0.31
0
1
4
2
9
2
0.061
0
0
1

11DR62
530.574
0.31
0
1
4
2
9
2
0.061
0
0
1

R1
384.431
1.489
0
1
2
2
5
0
0
0
0
0

R2
398.458
1.521
0
1
0
2
5
0
0
0
0
0

R4
469.58
1.805
0
2
1
3
5
0
0
0
0
0

R5
503.597
2.332
0
2
0
3
5
1
0.007
0
0
0

R6
508.016
3.102
0
2
0
3
4
1
0.016
0
0
0

R7
552.467
3.376
0
2
0
3
4
1
0.105
0
0
0

R8
487.597
2.679
0
2
0
3
4
0
0
0
0
0

R9
509.687
3.695
0
2
0
3
4
1
0.019
0
0
0

R10
439.553
1.714
0
2
0
3
4
0
0
0
0
0

R11-
482.619
3.553
0
1
0
2
5
0
0
0
0
0

R12
440.538
2.308
0
1
0
2
5
0
0
0
0
0

R13
454.565
2.766
0
1
0
2
5
0
0
0
0
0

R14
454.565
2.76
0
1
0
2
5
0
0
0
0
0

R15
468.592
3.156
0
1
0
2
5
0
0
0
0
0

R16
454.565
2.386
0
1
0
2
5
0
0
0
0
0

R18
469.536
0.982
0
2
0
3
6
0
0
0
0
0

R19
512.605
0.352
1
2
0
4
6
1
0.025
0
0
0

R20
512.561
−0.502
0
2
0
4
7
2
0.025
0
0
1

R21
513.546
0.362
0
2
0
3
8
2
0.027
0
0
1

R22
500.589
0.765
0
2
0
3
6
1
0.001
0
0
0

R23
527.573
0.614
0
2
0
3
8
2
0.055
0
0
1

R24
526.588
−0.251
0
2
0
4
7
2
0.053
0
0
1

R25
455.51
0.444
0
2
0
3
6
0
0
0
0
0

R26-
535.599
0.108
0
3
0
5
6
2
0.071
0
0
1

R27
511.617
2.25
0
2
0
3
6
1
0.023
0
0
0

R28
511.617
2.177
0
2
0
3
6
1
0.023
0
0
0

R29
526.631
0.748
1
2
0
4
6
1
0.053
0
0
0

R30
529.65
0.969
0
2
0
3
6
1
0.059
0
0
0

R31
545.634
2.668
0
2
0
3
6
1
0.091
0
0
0

R32
485.536
0.196
0
2
1
3
7
0
0
0
0
0

R33
499.563
0.609
0
2
1
3
7
0
0
0
0
0

R35
561.633
2.383
0
2
1
3
7
1
0.123
0
0
0

R36
497.59
1.853
0
2
0
3
6
0
0
0
0
0

R37
483.563
0.589
0
2
0
3
6
0
0
0
0
0

R38
497.59
1.002
0
2
0
3
6
0
0
0
0
0

R39-
545.634
2.178
0
2
0
3
6
1
0.091
0
0
0

R40
441.526
0.46
0
2
1
3
5
0
0
0
0
0

R41
455.553
0.873
0
2
1
3
5
0
0
0
0
0

R42
503.597
2.049
0
2
1
3
5
1
0.007
0
0
0

R43
513.589
0.641
0
2
1
3
7
1
0.027
0
0
0

R44
531.65
3.06
0
2
1
3
5
1
0.063
0
0
0

R45
469.536
0.476
0
2
0
3
6
0
0
0
0
0

R47
559.661
2.699
0
2
0
3
6
1
0.119
0
0
0

R48
542.461
3.62
0
2
0
3
4
1
0.085
0
0
0

R49
571.456
4.253
0
1
0
2
6
1
0.143
0
0
0

R50
592.644
2.459
0
1
0
2
9
2
0.185
0
0
1

R51
468.549
2.329
0
1
0
2
6
0
0
0
0
0

R52
547.563
3.171
0
1
0
3
8
2
0.095
0
0
1

R53
561.59
3.103
0
1
0
3
8
2
0.123
0
0
1

R54
528.604
3.625
0
1
0
2
6
1
0.057
0
0
0

R55
580.763
5.499
0
1
0
2
6
2
0.162
1
0
0

R56
622.843
6.688
0
1
0
2
6
2
0.246
1
0
0

R57
532.592
2.964
0
1
0
2
7
1
0.065
0
0
0

R58
482.575
3.16
0
1
0
2
6
0
0
0
0
0

R59
571.456
4.253
0
1
0
2
6
1
0.143
0
0
0

R60
592.644
2.459
0
1
0
2
9
2
0.185
0
0
1

R61
468.549
2.329
0
1
0
2
6
0
0
0
0
0

R62
547.563
3.171
0
1
0
3
8
2
0.095
0
0
1

R63
561.59
3.103
0
1
0
3
8
2
0.123
0
0
1

R64
528.604
3.625
0
1
0
2
6
1
0.057
0
0
0

R65
580.763
5.499
0
1
0
2
6
2
0.162
1
0
0

R66
636.87
7.084
0
1
0
2
6
2
0.274
1
0
0

R67
532.592
2.964
0
1
0
2
7
1
0.065
0
0
0

R68
482.575
3.16
0
1
0
2
6
0
0
0
0
0

Y1
340.421
2.011
0
1
1
2
3
0
0
0
0
0

Y2
382.458
2.14
0
1
0
2
4
0
0
0
0
0

Y3
396.485
2.769
0
1
0
2
4
0
0
0
0
0

Y4
453.58
2.424
0
2
1
3
4
0
0
0
0
0

Y5
487.597
2.951
0
2
0
3
4
0
0
0
0
0

Y6
492.016
3.722
0
2
0
3
3
0
0
0
0
0

Y7
536.467
3.996
0
2
0
3
3
1
0.073
0
0
0

Y8
471.598
3.299
0
2
0
3
3
0
0
0
0
0

Y9
493.688
4.315
0
2
0
3
3
0
0
0
0
0

Y10
423.554
2.333
0
2
0
3
3
0
0
0
0
0

Y11
466.619
4.172
0
1
0
2
4
0
0
0
0
0

Y12
424.539
2.928
0
1
0
2
4
0
0
0
0
0

Y13
438.566
3.386
0
1
0
2
4
0
0
0
0
0

Y14
438.566
3.38
0
1
0
2
4
0
0
0
0
0

Y15
452.592
3.776
0
1
0
2
4
0
0
0
0
0

Y16
438.566
3.006
0
1
0
2
4
0
0
0
0
0

Y17
469.536
1.14
0
2
1
3
6
0
0
0
0
0

Y18
453.537
1.601
0
2
0
3
5
0
0
0
0
0

Y19
496.605
0.972
1
2
0
4
5
0
0
0
0
0

Y20
496.562
0.117
0
2
0
4
6
0
0
0
0
0

Y21
497.547
0.982
0
2
0
3
7
0
0
0
0
0

Y22
485.597
1.402
0
2
0
3
5
0
0
0
0
0

Y23
511.574
1.234
0
2
0
3
7
1
0.023
0
0
0

Y24
510.589
0.369
0
2
0
4
6
1
0.021
0
0
0

Y25
439.51
1.064
0
2
0
3
5
0
0
0
0
0

Y26
519.599
0.728
0
3
0
5
5
1
0.039
0
0
0

Y27
495.617
2.869
0
2
0
3
5
0
0
0
0
0

Y28
495.617
2.797
0
2
0
3
5
0
0
0
0
0

Y29
510.632
1.368
1
2
0
4
5
1
0.021
0
0
0

Y30
513.651
1.589
0
2
0
3
5
1
0.027
0
0
0

Y31
529.635
3.287
0
2
0
3
5
1
0.059
0
0
0

Y32
469.536
0.816
0
2
1
3
6
0
0
0
0
0

Y33
483.563
1.229
0
2
1
3
6
0
0
0
0
0

Y34
568.671
2.596
0
3
0
4
5
1
0.137
0
0
0

Y35
545.634
3.003
0
2
1
3
6
1
0.091
0
0
0

Y36
481.591
2.473
0
2
0
3
5
0
0
0
0
0

Y37
467.564
1.208
0
2
0
3
5
0
0
0
0
0

Y38
481.591
1.621
0
2
0
3
5
0
0
0
0
0

Y39
529.635
2.798
0
2
0
3
5
1
0.059
0
0
0

Y40
425.527
1.079
0
2
1
3
4
0
0
0
0
0

Y41
439.553
1.492
0
2
1
3
4
0
0
0
0
0

Y42
487.597
2.669
0
2
1
3
4
0
0
0
0
0

Y43
497.59
1.261
0
2
1
3
6
0
0
0
0
0

Y44
515.651
3.679
0
2
1
3
4
1
0.031
0
0
0

Y45
453.537
1.096
0
2
0
3
5
0
0
0
0
0

Y46
509.644
2.901
0
2
0
3
5
1
0.019
0
0
0

Y47
543.661
3.319
0
2
0
3
5
1
0.087
0
0
0

Y48
526.461
4.24
0
2
0
3
3
1
0.053
0
0
0

Y49
526.461
4.24
0
2
0
3
3
1
0.053
0
0
0

Y50
513.419
5.089
0
1
0
2
4
2
0.027
1
0
0

Y51
534.608
3.295
0
1
0
2
7
1
0.069
0
0
0

Y52
386.921
3.013
0
1
0
2
2
0
0
0
0
0

Y53
489.527
4.007
0
1
0
3
6
0
0
0
0
0

Y54
489.527
4.007
0
1
0
3
6
0
0
0
0
0

Y55
470.567
4.461
0
1
0
2
4
0
0
0
0
0

Y56
522.726
6.335
0
1
0
2
4
2
0.045
1
0
0

Y57
534.824
8.446
0
1
0
2
2
2
0.07
1
0
0

Y58
474.555
3.801
0
1
0
2
5
0
0
0
0
0

Y60
559.661
3.035
0
2
1
3
6
1
0.119
0
0
0

Y61
280.412
3.595
0
1
0
2
0
0
0
0
0
0

Y62
543.661
3.319
0
2
0
3
5
1
0.087
0
0
0

Y63
469.536
0.816
0
2
1
3
6
0
0
0
0
0

Y64
280.412
3.595
0
1
0
2
0
0
0
0
0
0

Y65
483.563
0.873
0
2
1
3
6
0
0
0
0
0

Y66
545.634
3.003
0
2
1
3
6
1
0.091
0
0
0

Y67
529.635
3.287
0
2
0
3
5
1
0.059
0
0
0

Y68
280.412
3.595
0
1
0
2
0
0
0
0
0
0

Y69
280.412
3.595
0
1
0
2
0
0
0
0
0
0

Y70
545.634
3.038
0
2
1
3
6
1
0.091
0
0
0

Y71
280.412
3.595
0
1
0
2
0
0
0
0
0
0

Y72
503.597
2.909
0
2
2
3
5
1
0.007
0
0
0

Y73
280.412
3.595
0
1
0
2
0
0
0
0
0
0

Y74
396.485
2.967
0
1
0
2
4
0
0
0
0
0

Y75
368.432
2.593
0
1
0
2
4
0
0
0
0
0

Y76
424.539
3.363
0
1
0
2
4
0
0
0
0
0

Y77
438.566
3.527
0
1
0
2
4
0
0
0
0
0

Y78
438.566
3.593
0
1
0
2
4
0
0
0
0
0

Y79
452.592
3.989
0
1
0
2
4
0
0
0
0
0

Y80
438.566
4.028
0
1
0
2
4
0
0
0
0
0

Y81
468.549
2.36
0
1
0
2
6
0
0
0
0
0

Y82
441.564
2.366
0
1
0
2
4
0
0
0
0
0

Y83
454.522
1.964
0
1
0
2
6
0
0
0
0
0

Y84
453.537
1.099
0
1
0
3
5
0
0
0
0
0

Y85
453.58
2.098
1
1
0
3
4
0
0
0
0
0

Y86
432.564
2.806
0
2
0
4
2
0
0
0
0
0

Y87
452.592
3.924
0
1
0
2
4
0
0
0
0
0

Y88
452.592
3.924
0
1
0
2
4
0
0
0
0
0

Y89
467.607
2.495
1
1
0
3
4
0
0
0
0
0

Y90
470.626
2.77
0
1
0
2
4
0
0
0
0
0

Y93
502.609
4.129
0
1
1
2
5
1
0.005
0
0
0

Y95
482.575
2.489
0
1
0
2
6
0
0
0
0
0

Y96
426.511
1.798
0
1
1
2
5
0
0
0
0
0

Y97
440.538
2.36
0
1
1
2
5
0
0
0
0
0

Y98
502.609
3.482
0
1
1
2
5
1
0.005
0
0
0

Y99
560.689
3.917
0
1
0
2
6
1
0.121
0
0
0

Y100
454.522
2.063
0
1
0
2
6
0
0
0
0
0

K005
412.485
1.553
0
1
0
2
5
0
0
0
0
0

K002
412.485
1.553
0
1
0
2
5
0
0
0
0
0

K004 A
382.458
1.805
0
1
0
2
4
0
0
0
0
0

K004 B
382.458
1.805
0
1
0
2
4
0
0
0
0
0

K006
352.432
2.058
0
1
0
2
3
0
0
0
0
0

K003
382.458
1.805
0
1
0
2
4
0
0
0
0
0

K001
354.448
2.043
0
1
1
2
3
0
0
0
0
0

K001 A
396.485
2.172
0
1
0
2
4
0
0
0
0
0

K001 B
574.672
3.735
0
1
0
2
7
1
0.149
0
0
0

K001 C
504.562
2.618
0
1
1
3
6
1
0.009
0
0
0

K001 D
458.556
4.085
0
1
0
2
4
0
0
0
0
0

K001 E
504.562
2.618
0
1
1
3
6
1
0.009
0
0
0

K001 F
484.594
4.493
0
1
0
2
4
0
0
0
0
0

K001 G
522.77
6.699
0
1
0
2
3
2
0.046
1
0
0

TABLE 25

Details of radioligands, competitors and brain regions

involved in the assay of neurotransmitter receptors

Sl. no.
Receptor
Brain Region
Radioligand
Competitor

1.
Dopamine
Corpus striatum

³H-Spiperone
Haloperidol

(DA) - D2

(1 × 10⁻⁹M)
(1 × 10⁻⁶M)

2.
Serotonin
Frontal cortex

³H-Ketanserin
Cinanserin

(5HT) -2A

(1.5 × 10⁻⁹M)
(1 × 10⁻⁵M)

TABLE 26

Details of buffer, competitors and MAP-1597 extracts/alkaloids

added in the multiwell plates

Tris

Buffer

Receptor
(40 mM)
Radio-
Mem-
Compet-
Sam-
Total

Binding
pH 7.4
ligand
brane
itor
ples
volume

Total
160 μl
40 μl
50 μl
—
—
250 μl

Binding

Compet-
140 μl
40 μl
50 μl
20 μl
—
250 μl

itors

Binding
140 μl
40 μl
50 μl
—
20 μl
250 μl

with test

(20 μg)

sample

Incubation was carried out in a final volume of 250 μl.

TABLE 27

representative compounds of formula 2

embedded image

R1
R2

Y1
—COOH
—OH

Y2
—COOH
—OCOCH₃

Y3
—COOH
—OCOCH₂CH₃

Y4

embedded image

—OCOCH₃

Y5

embedded image

—OCOCH₃

Y6

embedded image

—OCOCH₃

Y7

embedded image

—OCOCH₃

Y8

embedded image

—OCOCH₃

Y9
—CO—NH—CH₂—(CH₂)₆—CH₃
—OCOCH₃

Y10
—CO—NH—CH₂—CH₂—CH₃
—OCOCH₃

Y11
—COO—CH₂—(CH₂)₄—CH₃
—OCOCH₃

Y12

embedded image

—OCOCH₃

Y13

embedded image

—OCOCH₃

Y14
—COO—CH₂—CH₂—CH₂—CH₃
—OCOCH₃

Y15
—COO—CH₂—CH₂—CH₂—CH₂—CH₃
—OCOCH₃

Y16
—COO—CH—(CH₃)₃
—OCOCH₃

Y17

embedded image

—OCOCH₃

Y18

embedded image

—OCOCH₃

Y19

embedded image

—OCOCH₃

Y20

embedded image

—OCOCH₃

Y21

embedded image

—OCOCH₃

Y22

embedded image

—OCOCH₃

Y23

embedded image

—OCOCH₃

Y24

embedded image

—OCOCH₃

Y25
—CO—NH—CH₂—COOH
—OCOCH₃

Y26

embedded image

—OCOCH₃

Y27

embedded image

—OCOCH₃

Y28

embedded image

—OCOCH₃

Y29

embedded image

—OCOCH₃

Y30

embedded image

—OCOCH₃

Y31

embedded image

—OCOCH₃

Y32

embedded image

—OCOCH₃

Y33

embedded image

—OCOCH₃

Y34

embedded image

—OCOCH₃

Y35

embedded image

—OCOCH₃

Y36

embedded image

—OCOCH₃

Y37
—CO—NH—CH₂—CH₂—OCOCH₃
—OCOCH₃

Y38

embedded image

—OCOCH₃

Y39

embedded image

—OCOCH₃

Y40
—CO—NH—CH₂—CH₂—OH
—OCOCH₃

Y41

embedded image

—OCOCH₃

Y42

embedded image

—OCOCH₃

Y43

embedded image

—OCOCH₃

Y44

embedded image

—OCOCH₃

Y45
—CO—NH—CH₂—COO—CH₃
—OCOCH₃

Y46

embedded image

—OCOCH₃

Y47

embedded image

—OCOCH₃

Y48

embedded image

—OCOCH₃

Y49

embedded image

—OCOCH₃

Y50
—COOH

embedded image

Y51
—COOH

embedded image

Y52
—COOH
—O—CH₂—CH₂—CO—Cl

Y53
—COOH

embedded image

Y54
—COOH

embedded image

Y55
—COOH

embedded image

Y56
—COOH
—OCO—CH₂—(CH₂)₉—CH₃

Y57
—COOH
—OCO—CH₂—(CH₂)₁₃—CH₃

Y58
—COOH

embedded image

Y59
—COOH
—OCO—CH—(CH₃)₃

Y60

embedded image

—OCOCH₃

Y61
—CONH—CH₂—COO—CH₃
—OCOCH₃

Y62

embedded image

—OCOCH₃

Y63

embedded image

—OCOCH₃

Y64
—CONH—CH₂—COOH
—OCOCH₃

Y65

embedded image

—OCOCH₃

Y66

embedded image

—OCOCH₃

Y67

embedded image

—OCOCH₃

Y68
—CONH—CH₂—CH₂—OCOCH₃
—OCOCH₃

Y69

embedded image

—OCOCH₃

Y70

embedded image

—OCOCH₃

Y71

embedded image

—OCOCH₃

Y72

embedded image

—OCOCH₃

Y73
—CONH—CH₂—CH₂—OH
—OCOCH₃

Y74
—COOH
—OCO—COO—CH₂—CH₃

Y75
—COOH
—OCO—CO—OH

Y76
—COO—CH₃

embedded image

Y77
—COO—CH₃

embedded image

Y78
—COO—CH₃
—OCO—CH₂—CH₂—CH₂—CH₃

Y79
—COO—CH₃
—OCO—CH₂—CH₂—CH₂—CH₂—CH₃

Y80
—COO—CH₃
—OCO—CH—(CH₃)₃

Y81
—COO—CH₃
—OCO—CH₂—CH₂—CH₂—COOH

Y82
—COO—CH₃
—OCO—CH₂—CH₂—SH

Y83
—COO—CH₃
—OCO—CH₂—CH₂—COOH

Y84
—COO—CH₃
—OCO—CH₂—CH₂—CONH₂

Y85
—COO—CH₃
—OCO—CH₂—CH₂—CH₂—CH₂—NH₂

Y86
—COOCH₃

embedded image

Y87
—COOCH₃

embedded image

Y88
—COOCH₃

embedded image

Y89
—COOCH₃
—OCO—CH₂—(CH₂)₄—NH₂

Y90
—COOCH₃
—OCO—CH₂—CH₂—CH₂—S—CH₃

Y91
—COOCH₃

embedded image

Y92
—COOCH₃

embedded image

Y93
—COOCH₃

embedded image

Y94
—COOCH₃
—OCO—CH₂—CH₂—OCO—CH₃

Y95
—COOCH₃

embedded image

Y96
—COOCH₃
—OCO—CH₂—CH₂—OH

Y97
—COOCH₃

embedded image

Y98
—COOCH₃

embedded image

Y99
—COOCH₃

embedded image

Y100
—COOCH₃
—OCO—CH₂—COO—CH₃

TABLE 28

representative compounds of formula 3

embedded image

R1
R2
R3

R1
—COOCH₃
—OH
—OH

R2
—COOH
—OCH₃
—OCH₃

R3
—COOH
—OH
—OH

R4

embedded image

—OCH₃
—OCH₃

R5

embedded image

—OCH₃
—OCH₃

R6

embedded image

—OCH₃
—OCH₃

R7

embedded image

—OCH₃
—OCH₃

R8

embedded image

—OCH₃
—OCH₃

R9
—CO—NH—CH₂—(CH₂)₆—CH₃
—OCH₃
—OCH₃

R10
—CO—NH—CH₂—CH₂—CH₃
—OCH₃
—OCH₃

R11
—COO—CH₂—(CH₂)₄—CH₃
—OCH₃
—OCH₃

R12

embedded image

—OCH₃
—OCH₃

R13

embedded image

—OCH₃
—OCH₃

R14
—COO—CH₂—CH₂—CH₂—CH₃
—OCH₃
—OCH₃

R15
—COO—CH₂—CH₂—CH₂—CH₂—CH₃
—OCH₃
—OCH₃

R16
—COO—CH—(CH₃)₃
—OCH₃
—OCH₃

R17

embedded image

—OCH₃
—OCH₃

R18

embedded image

—OCH₃
—OCH₃

R19

embedded image

—OCH₃
—OCH₃

R20

embedded image

—OCH₃
—OCH₃

R21

embedded image

—OCH₃
—OCH₃

R22

embedded image

—OCH₃
—OCH₃

R23

embedded image

—OCH₃
—OCH₃

R24

embedded image

—OCH₃
—OCH₃

R25
—CO—NH—CH₂—COOH
—OCH₃
—OCH₃

R26

embedded image

—OCH₃
—OCH₃

R27

embedded image

—OCH₃
—OCH₃

R28

embedded image

—OCH₃
—OCH₃

R29

embedded image

—OCH₃
—OCH₃

R30

embedded image

—OCH₃
—OCH₃

R31

embedded image

—OCH₃
—OCH₃

R32

embedded image

—OCH₃
—OCH₃

R33

embedded image

—OCH₃
—OCH₃

R34

embedded image

—OCH₃
—OCH₃

R35

embedded image

—OCH₃
—OCH₃

R36

embedded image

—OCH₃
—OCH₃

R37
—CO—NH—CH₂—CH₂—OCOCH₃
—OCH₃
—OCH₃

R38

embedded image

—OCH₃
—OCH₃

R39

embedded image

—OCH₃
—OCH₃

R40
—CO—NH—CH₂—CH₂—OH
—OCH₃
—OCH₃

R41

embedded image

—OCH₃
—OCH₃

R42

embedded image

—OCH₃
—OCH₃

R43

embedded image

—OCH₃
—OCH₃

R44

embedded image

—OCH₃
—OCH₃

R45
—CO—NH—CH₂—COO—CH₃
—OCH₃
—OCH₃

R46

embedded image

—OCH₃
—OCH₃

R47

embedded image

—OCH₃
—OCH₃

R48

embedded image

—OCH₃
—OCH₃

R49
—COOCH₃

embedded image

—OCH₃

R50
—COOCH₃

embedded image

—OCH₃

R51
—COOCH₃
—OCO—CH₂—CH₂—CH₃
—OCH₃

R52
—COOCH₃

embedded image

—OCH₃

R53
—COOCH₃

embedded image

—OCH₃

R54
—COOCH₃

embedded image

—OCH₃

R55
—COOCH₃
—OCO—CH₂—(CH₂)₉—CH₃
—OCH₃

R56
—COOCH₃
—OCO—CH₂—(CH₂)₁₂—CH₃
—OCH₃

R57
—COOCH₃

embedded image

—OCH₃

R58
—COOCH₃
—OCO—CH—(CH₃)₃
—OCH₃

R59
—COOCH₃

embedded image

—OCH₃

R60
—COOCH₃
—OCH₃

embedded image

R61
—COOCH₃
—OCH₃
—OCO—CH₂—CH₂—CH₃

R62
—COOCH₃
—OCH₃

embedded image

R63
—COOCH₃
—OCH₃

embedded image

R64
—COOCH₃
—OCH₃

embedded image

R65
—COOCH₃
—OCH₃
—OCO—CH₂—(CH₂)₉—CH₃

R66
—COOCH₃
—OCH₃
—OCO—CH₂—(CH₂)₁₃—CH₃

R67
—COOCH₃
—OCH₃

embedded image

R68
—COOCH₃
—OCH₃
—OCO—CH—(CH₃)₃

TABLE 29

representative compounds of formula 4

embedded image

R1
R2

11DR1
—COOCH₃
—OH

11DR2
—COOH
—OH

11DR3
—COOH
—OCH₃

11DR4

embedded image

—OCH₃

11DR5

embedded image

—OCH₃

11DR6

embedded image

—OCH₃

11DR7

embedded image

—OCH₃

11DR8

embedded image

—OCH₃

11DR9
—CO—NH—CH₂—(CH₂)₆—CH₃
—OCH₃

11DR10
—CO—NH—CH₂—CH₂—CH₃
—OCH₃

11DR11
—COO—CH₂—(CH₂)₄—CH₃
—OCH₃

11DR12

embedded image

—OCH₃

11DR13

embedded image

—OCH₃

11DR14
—COO—CH₂—CH₂—CH₂—CH₃
—OCH₃

11DR15
—COO—CH₂—CH₂—CH₂—CH₂—CH₃
—OCH₃

11DR16
—COO—CH—(CH₃)₃
—OCH₃

11DR17

embedded image

—OCH₃

11DR18

embedded image

—OCH₃

11DR19

embedded image

—OCH₃

11DR20

embedded image

—OCH₃

11DR21

embedded image

—OCH₃

11DR22

embedded image

—OCH₃

11DR23

embedded image

—OCH₃

11DR24

embedded image

—OCH₃

11DR25
—CO—NH—CH₂—COOH
—OCH₃

11DR26

embedded image

—OCH₃

11DR27

embedded image

—OCH₃

11DR28

embedded image

—OCH₃

11DR29

embedded image

—OCH₃

11DR30

embedded image

—OCH₃

11DR31

embedded image

—OCH₃

11DR32

embedded image

—OCH₃

11DR33

embedded image

—OCH₃

11DR34

embedded image

—OCH₃

11DR36

embedded image

—OCH₃

11DR37
—CO—NH—CH₂—CH₂—OCOCH₃
—OCH₃

11DR38

embedded image

—OCH₃

11DR39

embedded image

—OCH₃

11DR40
—CO—NH—CH₂—CH₂—OH
—OCH₃

11DR41

embedded image

—OCH₃

11DR42

embedded image

—OCH₃

11DR43

embedded image

—OCH₃

11DR44

embedded image

—OCH₃

11DR45
—CO—NH—CH₂—COO—CH₃
—OCH₃

11DR46

embedded image

—OCH₃

11DR47

embedded image

—OCH₃

11DR48

embedded image

—OCH₃

11DR49
—COOCH₃

embedded image

11DR50
—COOCH₃

embedded image

11DR51
—COOCH₃
—OCO—CH₂—CH₂—CH₃

11DR52
—COOCH₃

embedded image

11DR53
—COOCH₃

embedded image

11DR54
—COOCH₃

embedded image

11DR55
—COOCH₃
—OCO—CH₂—(CH₂)₉—CH₃

11DR56
—COOCH₃
—OCO—CH₂—(CH₂)₁₃—CH₃

11DR57
—COOCH₃

embedded image

11DR58
—COOCH₃
—OCO—CH—(CH₃)₃

11DR59
—COOCH₃

embedded image

11DR60
—COOCH₃

embedded image

11DR61
—COOCH₃

embedded image

11DR62
—COOCH₃

embedded image

TABLE 30

representative compounds of formula 5

embedded image

R1
R2

10DR1
—COOCH₃
—OH

10DR2
—COOH
—OH

10DR3
—COOH
—OCH₃

10DR4

embedded image

—OCH₃

10DR5

embedded image

—OCH₃

10DR6

embedded image

—OCH₃

10DR7

embedded image

—OCH₃

10DR8

embedded image

—OCH₃

10DR9
—CO—NH—CH₂—(CH₂)₆—CH₃
—OCH₃

10DR10
—CO—NH—CH₂—CH₂—CH₃
—OCH₃

10DR11
—COO—CH₂—(CH₂)₄—CH₃
—OCH₃

10DR12

embedded image

—OCH₃

10DR13

embedded image

—OCH₃

10DR14
—COO—CH₂—CH₂—CH₂—CH₃
—OCH₃

10DR15
—COO—CH₂—CH₂—CH₂—CH₂—CH₃
—OCH₃

10DR16
—COO—CH—(CH₃)₃
—OCH₃

10DR17

embedded image

—OCH₃

10DR18

embedded image

—OCH₃

10DR19

embedded image

—OCH₃

10DR20

embedded image

—OCH₃

10DR21

embedded image

—OCH₃

10DR22

embedded image

—OCH₃

10DR23

embedded image

—OCH₃

10DR24

embedded image

—OCH₃

10DR25
—CO—NH—CH₂—COOH
—OCH₃

10DR26

embedded image

—OCH₃

10DR27

embedded image

—OCH₃

10DR28

embedded image

—OCH₃

10DR29

embedded image

—OCH₃

10DR30

embedded image

—OCH₃

10DR31

embedded image

—OCH₃

10DR32

embedded image

—OCH₃

10DR33

embedded image

—OCH₃

10DR34

embedded image

—OCH₃

10DR36

embedded image

—OCH₃

10DR37
—CO—NH—CH₂—CH₂—OCOCH₃
—OCH₃

10DR38

embedded image

—OCH₃

10DR39

embedded image

—OCH₃

10DR40
—CO—NH—CH₂—CH₂—OH
—OCH₃

10DR41

embedded image

—OCH₃

10DR42

embedded image

—OCH₃

10DR43

embedded image

—OCH₃

10DR44

embedded image

—OCH₃

10DR45
—CO—NH—CH₂—COO—CH₃
—OCH₃

10DR46

embedded image

—OCH₃

10DR47

embedded image

—OCH₃

10DR48

embedded image

—OCH₃

10DR49
—COOCH₃

embedded image

10DR50
—COOCH₃

embedded image

10DR52
—COOCH₃
—OCO—CH₂—CH₂—CH₃

10DR53
—COOCH₃

embedded image

10DR54
—COOCH₃

embedded image

10DR55
—COOCH₃

embedded image

10DR56
—COOCH₃
—OCO—CH₂—(CH₂)₉—CH₃

10DR57
—COOCH₃
—OCO—CH₂—(CH₂)₁₃—CH₃

10DR58
—COOCH₃

embedded image

10DR59
—COOCH₃
—OCO—CH—(CH₃)₃

10DR60
—COOCH₃

embedded image

10DR61
—COOCH₃

embedded image

10DR62
—COOCH₃

embedded image

TABLE 31

Test data set for antipsychotic compound

Test data set for antipsychotic compound

Pred. log
Exp.

S. No.
Compound Name
IC50 (nM)
IC50 (nM)

1.
Astemizole
−0.897
−0.05

2.
Domperidone
1.124
2.21

3.
Loratadine
2.188
2.24

4.
Spironolactone
3.782
4.36

5.
Canrenoic acid
3.495
5.02

6.
Ketoconazole
4.043
3.28

TABLE 32

Predicted logIC50 and IC50 value of isolated

Yohimbane alkaloids and semi-synthetic derivatives

of α-yohimbine by virtual screening model

Test compounds
Pred log
Pred.

Name
IC50 (nM)
IC50 (nM)

K005
5.212
162929.60

K002
5.263
183231.44

K004a
4.801
63241.19

K004b
4.443
27733.20

K006
4.096
12473.84

K003
4.531
33962.53

K001
3.386
2432.20

K001A
2.773
592.93

K001B
1.901
79.62

K001C
3.834
6823.39

K001D
1.576
37.67

K001E
1.036
10.86

K001F
0.092
1.24

K001G
0.54
3.47

TABLE 33

Predicted logIC50 and IC50 value of virtual derivatives

of Yohimbane alkaloids by virtual screening model

Test compounds
Pred log
Pred.

Name
IC50 (nM)
IC50 (nM)

Y1
3.748
5597.58

Y2
2.878
755.09

Y3
3.062
1153.45

Y4
0.353
2.25

Y5
1.876
75.16

Y6
0.06
1.15

Y7
0.358
2.28

Y8
0.553
3.57

Y9
0.402
2.52

Y10
2.095
124.45

Y11
0.208
1.61

Y12
1.202
15.92

Y13
1.228
16.90

Y14
1.635
43.15

Y15
1.097
12.50

Y16
0.885
7.67

Y17
−0.012
0.97

Y18
1.407
25.53

Y19
0.083
1.21

Y20
−0.043
0.91

Y21
0.479
3.01

Y22
1.367
23.28

Y23
0.094
1.24

Y24
−0.437
0.37

Y25
1.534
34.20

Y26
−0.41
0.39

Y27
0.789
6.15

Y28
0.644
4.41

Y29
−0.208
0.62

Y30
0.367
2.33

Y31
−0.745
0.18

Y32
1.818
65.77

Y33
1.476
29.92

Y34
−1.187
0.07

Y35
−0.696
0.20

Y36
0.476
2.99

Y37
0.785
6.10

Y38
0.708
5.11

Y39
−0.717
0.19

Y40
1.641
43.75

Y41
1.612
40.93

Y42
−0.279
0.53

Y43
1.014
10.33

Y44
−0.751
0.18

Y45
0.857
7.19

Y46
0.365
2.32

Y47
0.057
1.14

Y48
0.34
2.19

Y49
−0.269
0.54

Y50
0.998
9.95

Y51
2.904
801.68

Y52
3.917
8260.38

Y53
1.11
12.88

Y54
0.513
3.26

Y55
−0.376
0.42

Y56
−0.827
0.15

Y57
−1.984
0.01

Y58
1.985
96.61

Y60
−0.763
0.17

Y61
4.803
63533.09

Y62
−0.921
0.12

Y63
1.945
88.10

Y64
4.539
34593.94

Y65
0.663
4.60

Y66
−0.4
0.40

Y67
−0.778
0.17

Y68
4.523
33342.64

Y69
4.807
64120.96

Y70
−1.002
0.10

Y71
4.517
32885.16

Y72
−0.861
0.14

Y73
4.529
33806.48

Y74
2.814
651.63

Y75
3.712
5152.29

Y76
1.878
75.51

Y77
1.623
41.98

Y78
1.445
27.86

Y79
1.161
14.49

Y80
1.33
21.38

Y81
0.365
2.32

Y82
1.923
83.75

Y83
0.966
9.25

Y84
0.81
6.46

Y85
0.797
6.27

Y86
1.707
50.93

Y87
1.065
11.61

Y88
1.191
15.52

Y89
0.502
3.18

Y90
0.572
3.73

Y93
0.502
3.18

Y95
0.812
6.49

Y96
2.339
218.27

Y97
1.78
60.26

Y98
−0.398
0.40

Y99
1.119
13.15

Y100
1.492
31.05

R1-KOO2
3.477
2999.16

R2-KOO2
5.695
495450.19

R4-KOO2
2.894
783.43

R5-KOO2
3.913
8184.65

R6-KOO2
3.189
1545.25

R7-KOO2
3.198
1577.61

R8-KOO2
2.727
533.33

R9-KOO2
1.658
45.50

R10-KOO2
3.295
1972.42

R11-KOO2
2.7
501.19

R12-KOO2
4.262
18281.00

R13-KOO2
4.276
18879.91

R14-KOO2
3.704
5058.25

R15-KOO2
3.332
2147.83

R16-KOO2
3.871
7430.19

R18-KOO2
3.604
4017.91

R19-KOO2
2.517
328.85

R20-KOO2
2.733
540.75

R21-KOO2
2.906
805.38

R22-KOO2
3.184
1527.57

R23-KOO2
3.24
1737.80

R24-KOO2
2.887
770.90

R25-KOO2
3.854
7144.96

R26-KOO2
3.713
5164.16

R27-KOO2
3.087
1221.80

R28-KOO2
2.905
803.53

R29-KOO2
2.392
246.60

R30-KOO2
2.882
762.08

R30-KOO2
2.882
762.08

R31-KOO2
1.66
45.71

R32-KOO2
3.716
5199.96

R33-KOO2
3.434
2716.44

R34-KOO2
1.979
95.28

R35-KOO2
1.844
69.82

R36-KOO2
3.67
4677.35

R37-KOO2
3.548
3531.83

R38-KOO2
2.815
653.13

R39-KOO2
2.299
199.07

R40-KOO2
5.259
181551.57

R41-KOO2
3.948
8871.56

R42-KOO2
2.582
381.94

R43-KOO2
4.218
16519.62

R44-KOO2
7.424
26546055.62

R45-KOO2
9.458
2870780582.02

R47-KOO2
5.972
937562.01

R48-KOO2
3.033
1078.95

R49-KOO2
3.22
1659.59

R50-KOO2
25.443
—

R51-KOO2
4.441
27605.78

R52-KOO2
17.384
—

R53-KOO2
3.442
2766.94

R54-KOO2
15.771
—

R55-KOO2
1.27
18.62

R56-KOO2
0.21
1.62

R57-KOO2
3.968
9289.66

R58-KOO2
4.543
34914.03

R59-KOO2
18.704
—

R60-KOO2
26.078
—

R61-KOO2
4.838
68865.23

R62-KOO2
4.121
13212.96

R63-KOO2
3.094
1241.65

R64-KOO2
15.049
—

R64-KOO2
15.049
—

R65-KOO2
1.432
27.04

R66-KOO2
12.075
—

R67-KOO2
17.601
—

R68-KOO2
4.302
20044.72

11DR1-KOO4a
3.76
5754.40

11DR2-KOO4a
4.018
10423.17

11DR3-KOO4a
4.589
38815.04

11DR4-KOO4a
2.681
479.73

11DR5-KOO4a
2.843
696.63

11DR6-KOO4a
2.575
375.84

11DR7-KOO4a
2.178
150.66

11DR8-KOO4a
2.962
916.22

11DR9-KOO4a
1.515
32.73

11DR10-KOO4a
3.261
1823.90

11DR11-KOO4a
2.568
369.83

11DR12-KOO4a
3.692
4920.40

11DR13-KOO4a
3.438
2741.57

11DR14-KOO4a
3.559
3622.43

11DR15-KOO4a
3.154
1425.61

11DR16-KOO4a
3.359
2285.60

11DR17-KOO4a
2.082
120.78

11DR18-KOO4a
3.465
2917.43

11DR19-KOO4a
2.125
133.35

11DR20-KOO4a
2.393
247.17

11DR21-KOO4a
2.275
188.36

11DR23-KOO4a
2.219
165.58

11DR24-KOO4a
2.295
197.24

11DR25-KOO4a
3.729
5357.97

11DR26-KOO4a
2.439
274.79

11DR27-KOO4a
2.469
294.44

11DR28-KOO4a
2.131
135.21

11DR29-KOO4a
1.854
71.45

11DR32-KOO4a
3.377
2382.32

11DR34-KOO4a
1.58
38.02

11DR35-KOO4a
1.142
13.87

11DR36-KOO4a
2.821
662.22

11DR37-KOO4a
2.715
518.80

11DR38-KOO4a
3.104
1270.57

11DR39-KOO4a
1.052
11.27

11DR40-KOO4a
4.026
10616.96

11DR41cdx-KOO4a
3.879
7568.33

11DR42-KOO4a
2.388
244.34

11DR43cdx-KOO4a
2.895
785.24

11DR44-KOO4a
0.945
8.81

11DR45-KOO4a
3.331
2142.89

11DR45-KOO4a
3.331
2142.89

11DR46-KOO4a
2.147
140.28

11DR47-KOO4a
0.838
6.89

11DR48-KOO4a
1.672
46.99

11DR49-KOO4a
1.672
46.99

11DR50-KOO4a
3.297
1981.53

11DR51-KOO4a
2.482
303.39

11DR52-KOO4a
1.888
77.27

11DR53-KOO4a
1.97
93.33

11DR54-KOO4a
0.633
4.30

11DR55-KOO4a
−0.669
0.21

11DR56-KOO4a
−2.278
0.01

11DR57-KOO4a
1.898
79.07

11DR58-KOO4a
2.383
241.55

11DR59-KOO4a
1.654
45.08

11DR60-KOO4a
2.208
161.44

11DR61-KOO4a
5.578
378442.58

11DR62-KOO4a
5.281
190985.33

10DR3-KOO4b
4.491
30974.19

10DR4-KOO4b
2.618
414.95

10DR5-KOO4b
2.724
529.66

10DR6-KOO4b
2.582
381.94

10DR7-KOO4b
2.195
156.68

10DR8-KOO4b
2.149
140.93

10DR9-KOO4b
1.148
14.06

10DR10cdx-KOO4b
3.12
1318.26

10DR11-KOO4b
2.484
304.79

10DR12-KOO4b
3.525
3349.65

10DR13-KOO4b
3.374
2365.92

10DR14-KOO4b
3.122
1324.34

10DR15-KOO4b
2.753
566.24

10DR16-KOO4b
3.509
3228.49

10DR17-KOO4b
1.972
93.76

10DR18-KOO4b
3.183
1524.05

10DR19-KOO4b
1.826
66.99

10DR20-KOO4b
2.264
183.65

10DR21-KOO4b
2.456
285.76

10DR22-KOO4b
Failed
—

10DR23-KOO4b
1.903
79.98

10DR24-KOO4b
2.072
118.03

10DR25-KOO4b
3.585
3845.92

10DR26-KOO4b
2.966
924.70

10DR27-KOO4b
2.335
216.27

10DR28-KOO4b
2.104
127.06

10DR29-KOO4b
2.168
147.23

10DR30-KOO4b
1.788
61.38

10DR31-KOO4b
1.364
23.12

10DR32-KOO4b
3.274
1879.32

10DR33-KOO4b
3.626
4226.69

10DR34-KOO4b
1.147
14.03

10DR35-KOO4b
1.091
12.33

10DR36-KOO4b
3.174
1492.79

10DR37-KOO4b
3.207
1610.65

10DR38-KOO4b
2.388
244.34

10DR39-KOO4b
1.618
41.50

10DR40-KOO4b
4.009
10209.39

10DR41cdx-KOO4b
3.993
9840.11

10DR42-KOO4b
1.935
86.10

10DR43cdx-KOO4b
3.161
1448.77

10DR44-KOO4b
1.053
11.30

10DR45-KOO4b
3.863
7294.58

10DR46-KOO4b
2.715
518.80

10DR47-KOO4b
1.513
32.58

10DR48-KOO4b
2.341
219.28

10DR49-KOO4b
0.982
9.59

10DR50-KOO4b
9.397
2494594726.94

10DR52-KOO4b
2.083
121.06

10DR53-KOO4b
2.175
149.62

10DR54-KOO4b
1.451
28.25

10DR55-KOO4b
0.571
3.72

10DR56-KOO4b
−0.757
0.17

10DR57-KOO4b
−2.565
0.00

10DR58-KOO4b
2.024
105.68

10DR59-KOO4b
2.96
912.01

10DR60-KOO4b
1.246
17.62

10DR61-KOO4b
5.725
530884.44

10DR62-KOO4b
5.718
522396.19

TABLE 34

Training data set for known anti psychotic drug

Atom
Bond
Conformation
Connectiv-
Connectiv-
Connectiv-

Exp.
Exp.
Count
Count
Minimum
ity Index
ity Index
ity Index

IC50
logIC50
(all
(all
Energy
(order 0,
(order 1,
(order 2,

Chemical Sample
(nM)
(nM)
atoms)
bonds)
(kcal/mole)
standard)
standard)
standard)

CID 2351 bepridil
25.7
1.41
61.00
63
−11.486
18.899
13.22
11.263

CID 2769_cisapride
44.67
1.65
61
63
−157.685
23.087
15.405
13.489

CID_2771_citalopram
3981
3.6
45
47
−2.506
17.156
11.548
10.469

CID 2995_desipramine
1380.38
3.14
42
44
42.493
13.786
9.898
8.154

CID 3148 dolasetron
5884
3.77
44
48
−77.022
16.259
11.687
11.128

CID 3168_droperidol
32.36
1.51
50
53
−54.58
19.51
13.614
12.208

CID 3185E 4031
18.19
1.26
55
57
−74.001
20.148
13.299
12.901

CID 3356 flecainide
3890.4
3.59
48
49
−409.699
20.786
13.034
13.36

CID 3386 Fluoxetine
5513.5
3.741
40
41
−149.92
16.002
10.503
9.62

CID 3510 Granisetron
3715.3
3.57
47
50
13.163
15.974
11.131
10.35

first
CID_3559_Haloperidol
31.62
1.5
49
51
−94.323
18.571
12.46
11.482

generation

CID 3696_imipramine
3388.4
3.53
45
47
40.267
14.656
10.254
8.983

CID 4078 mesoridazine
316.22
2.5
52
55
21.746
18.096
12.631
11.448

CID_4893_prazosin
1584.8
3.2
49
52
−55.482
19.673
13.601
12.019

Second
CID_5002_quetiapine
5754.3
3.76
52
55
2.362
18.476
13.348
11.278

generation

Second
CID_5073 risperidone
147.91
2.17
57
61
−36.404
20.665
14.597
13.386

generation

CID 5379 gatifloxacin
128220
5.108
49
52
132.373
19.292
12.918
12.139

CID 5401 terazosin
17882
4.252
53
56
−103.21
19.673
13.601
12.019

first
CID 5452_thioridazine
33.11
1.52
51
54
43.813
17.225
12.258
10.718

generation

CID 5663 vesnarinone
1047.1
3.02
54
57
−105.129
20.38
14.084
12.455

CID 40692 Mefloquine
5623.4
3.75
42
44
317.643
19.113
12.087
12.687

CID 60404 sparfloxacin
17882.7
4.252
50
53
−144.414
20.326
13.201
12.991

Second
CID_60854_ziprasidone
125.89
2.1
49
53
17.859
19.087
13.67
12.613

generation

CID 123018 norastemizole
27.54
1.44
45
48
22.075
16.355
11.793
10.469

CID 129211 tamsulosin
104710
5.02
56
57
−138.227
20.571
13.346
12.039

CID 149096 levofloxacin
912010
5.96
46
49
−157.466
18.585
12.38
11.937

CID 152946 moxifloxacin
128820
5.11
53
57
−133.613
20.284
13.99
13.144

CID 446220 cocaine
7244.3
3.86
43
45
−136.937
15.69
10.613
9.43

Second
CID_450907_clozapine
131820
5.12
42
45
88.832
15.811
11.204
10.302

generation

CID_6604102_doxazosin
588.84
2.77
58
62
−96.578
22.949
16.067
14.352

Dipole
Dipole
Dipole
Dipole
Electron
Dielectric
Steric

Moment
Vector X
Vector Y
Vector Z
Affinity
Energy
Energy

Chemical Sample
(debye)
(debye)
(debye)
(debye)
(eV)
(kcal/mole)
(kcal/mole)

CID 2351 bepridil
1.144
1.106
−0.203
0.032
−0.166
0.234
64.463

CID 2769_cisapride
3.244
2.437
−1.014
1.896
0.146
−0.798
39.365

CID_2771_citalopram
3.038
−1.088
2.514
1.345
0.859
−0.483
36.916

CID 2995_desipramine
1.05
0.269
−1.005
0.143
−0.288
−0.253
44.619

CID 3148 dolasetron
5.333
−0.84
4.863
−2.032
0.333
−0.798
56.126

CID 3168_droperidol
1.195
0.655
1.017
−0.177
0.731
−0.694
30.825

CID 3185E 4031
5.517
−2.955
−0.914
−4.406
0.738
−1.27
61.056

CID 3356 flecainide
4.224
−3.212
−0.308
−2.666
0.778
−0.721
48.491

CID 3386 Fluoxetine
3.202
0.39
−1.363
2.787
0.372
−0.299
22.929

CID 3510 Granisetron
4.413
−1.82
−2.638
3.036
0.658
−0.51
59.522

first
CID_3559_Haloperidol
3.392
−0.24
3.08
−1.456
0.706
−0.528
23.252

generation

CID 3696_imipramine
1.086
−0.885
0.014
−0.651
−0.295
−0.244
51.566

CID 4078 mesoridazine
1.475
−0.354
0.039
1.471
0.688
−0.718
63.033

CID_4893_prazosin
5.87
2.471
−1.088
3.384
0.779
−0.856
6.941

Second
CID_5002_quetiapine
1.466
−0.19
1.235
0.674
0.708
−0.49
90.114

generation

Second
CID_5073 risperidone
5.572
0.918
1.352
−5.329
0.857
−0.763
36.796

generation

CID 5379 gatifloxacin
5.349
−0.009
−2.568
4.965
1.003
−0.921
92.125

CID 5401 terazosin
5.075
−1.236
4.705
0.842
0.78
−0.817
6.829

first
CID 5452_thioridazine
3.091
1.511
−1.671
1.798
0.418
−0.395
63.155

generation

CID 5663 vesnarinone
3.376
−0.578
−2.126
2.571
0.262
−0.842
34.734

CID 40692 Mefloquine
7.079
7.079
−0.176
0.008
1.891
−0.53
70.831

CID 60404 sparfloxacin
5.767
2.786
4.501
2.349
0.813
−0.875
87.331

Second
CID_60854_ziprasidone
3.542
0.989
−2.805
1.875
0.787
−0.686
72.375

generation

CID 123018 norastemizole
1.768
−1.145
−1.296
−0.393
0.49
−0.538
−7.979

CID 129211 tamsulosin
6.579
6.326
−0.074
−0.553
0.602
−1.235
41.895

CID 149096 levofloxacin
7.629
5.451
2.582
−3.314
0.776
1.03
78.148

CID 152946 moxifloxacin
6.024
−3.166
1.283
−5.836
0.858
−0.822
81.531

CID 446220 cocaine
1.678
0.826
−1.481
−0.327
0.383
−0.497
37.521

Second
CID_450907_clozapine
2.432
−2.249
0.54
−0.669
1.181
−0.381
95.173

generation

CID_6604102_doxazosin
4.263
1.954
2.178
1.266
0.782
−0.849
17.986

Group

Total
Group
Group
Count
Group
Group
Group
Group

Energy
Count
Count
(sec-
Count
Count
Count
Count

Chemical Sample
(Hartroe)
(amide)
(amine)
amine)
(carbonyl)
(ether)
(hydroxyl)
(methyl)

CID_2351_bepridil
−189.05
0
0
0
0
1
0
2

CID_2769_cisapride
−253.823
1
1
1
0
3
0
2

CID_2771_citalopram
−172.667
0
0
0
0
1
0
2

CID_2995_desipramine
−134.069
0
0
1
0
0
0
1

CID_3148_dolasetron
−174.767
0
0
1
1
0
0
0

CID_3168_droperidol
−205.407
1
0
1
1
0
0
0

CID_3185E-4031
−208.972
0
0
1
1
0
0
2

CID_3356_flecainide
−263.835
1
0
2
0
2
0
0

CID_3386_Fluoxetine
−178.863
0
0
1
0
1
0
1

CID_3510_Granisetron
−165.181
1
0
1
0
0
0
2

first
CID_3559_Haloperidol
−196.262
0
0
0
1
0
1
0

generation

CID_3696_imipramine
−141.195
0
0
0
0
0
0
2

CID_4078 mesoridazine
−184.673
0
0
0
0
0
0
2

CID_4893_ prazosin
−212.954
0
1
0
0
3
0
2

Second
CID_5002_quetiapine
−195.115
0
0
0
0
1
1
0

generation

Second
CID_5073 risperidone
−223.915
0
0
0
0
0
0
1

generation

CID_5379_gatifloxacin
−213.552
0
0
1
1
1
0
2

CID_5401_ terazosin
−216.509
0
1
0
0
3
0
2

first
CID_5452 thioridazine
−172.527
0
0
0
0
0
0
2

generation

CID_5663 vesnarinone
−215.742
1
0
1
0
2
0
2

CID_40692_Mefloquine
−236.274
0
0
1
0
0
1
0

CID_60464 sparfloxacin
−226.743
0
1
1
1
0
0
2

Second
CID_60854_ziprasidone
−200.906
1
0
1
0
0
0
0

generation

CID_123618 norastemizole
−172.629
0
0
2
0
0
0
0

CID_129211 tamsulosin
−220.227
0
1
1
0
3
0
3

CID_149096_levofloxacin
−206.513
0
0
0
1
1
0
2

CID_152946_moxifloxacin
−226.448
0
0
1
1
1
0
1

CID_446220_cocaine
−167.839
0
0
0
0
0
0
2

Second
CID_450907_clozapine
−161.2
0
0
1
0
0
0
1

generation

CID_6604102_doxazosin
−250.585
0
1
0
0
4
0
2

Lambda
Lambda

Group
Heat of
HOMO
Ionization
Ionization
Max UV-
Max far-UV-

Count
Formation
Energy
Potential
Potential
Visible
Visible

Chemical Sample
(sulfide)
(kcal/mole)
(eV)
(eV)
(eV)
(nm)
(nm)

CID_2351_bepridil
0
−13.706
−8.325
8.32
8.319
192.181
192.187

CID_2769_cisapride
0
−157.8
−8.732
8.734
8.733
202.855
202.921

CID_2771_citalopram
0
−2.471
−9.191
9.192
9.193
195.756
195.747

CID_2995_desipramine
0
42.572
−8.422
8.423
8.424
200.026
200.071

CID_3148_dolasetron
0
−77.125
−8.741
8.741
8.741
212.783
212.792

CID_3168_droperidol
0
−54.68
−8.568
8.568
8.568
196.757
196.766

CID_3185E-4031
0
−74.029
−9.058
9.06
9.062
201.184
201.2

CID_3356_flecainide
0
−411.507
−9.604
9.604
9.604
193.056
193.112

CID_3386_Fluoxetine
0
−149.934
−9.381
9.38
9.383
190.881
222.799

CID_3510_Granisetron
0
12.997
−8.925
8.914
8.917
217.619
217.573

first
CID_3559_Haloperidol
0
−94.321
−9.229
9.229
9.23
196.526
196.424

generation

CID_3696_imipramine
0
40.25
−8.402
8.417
8.418
199.954
200.048

CID_4078 mesoridazine
1
18.658
−7.992
7.991
7.994
235.722
235.709

CID_4893_ prazosin
0
−58.424
−8.512
8.495
8.51
239.511
239.584

Second
CID_5002_quetiapine
1
2.072
−8.633
8.63
8.633
211.893
211.871

generation

Second
CID_5073 risperidone
0
−35.875
−9.065
9.064
9.064
201.447
201.449

generation

CID_5379_gatifloxacin
0
−132.594
−8.937
8.937
8.937
244.657
244.892

CID_5401_ terazosin
0
−103.064
−8.321
8.327
8.324
240.998
240.894

first
CID_5452 thioridazine
2
46.388
−7.827
7.828
7.826
238.346
238.385

generation

CID_5663 vesnarinone
0
−105.635
−8.368
8.369
8.369
201.952
201.955

CID_40692_Mefloquine
0
−317.644
−9.573
9.573
9.573
217.075
217.093

CID_60464 sparfloxacin
0
−144.461
−8.572
8.572
8.572
280.525
280.662

Second
CID_60854_ziprasidone
1
17.583
−8.613
8.614
8.615
196.916
196.914

generation

CID_123618 norastemizole
0
21.256
−8.595
8.594
8.595
205.653
205.675

CID_129211 tamsulosin
0
−136.409
−8.766
8.766
8.764
194.077
194.065

CID_149096_levofloxacin
0
−157.384
−8.721
8.721
8.721
274.685
274.561

CID_152946_moxifloxacin
0
−134.15
−8.882
8.877
8.872
269.73
270.165

CID_446220_cocaine
0
−137.468
−9.433
9.434
9.434
192.294
192.405

Second
CID_450907_clozapine
0
88.836
−8.08
8.08
8.076
225.962
226.004

generation

CID_6604102_doxazosin
0
−96.755
−8.561
8.561
8.561
193.3
193.308

LUMO

Ring
Size of
Size of

Energy
Molar
Molecular
Count
Smallest
Largest

Chemical Sample
Log P
(eV)
Refractivity
Weight
(all rings)
Ring
Ring

CID_2351_bepridil
5.512
0.229
115.116
366.545
3
5
6

CID_2769_cisapride
2.246
−0.136
122.437
465.951
3
6
6

CID_2771_citalopram
3.76
−0.855
93.835
324.397
3
5
6

CID_2995_desipramine
3.645
0.284
85.311
266.385
3
6
7

CID_3148_dolasetron
1.511
−0.335
88.868
324.379
6
5
6

CID_3168_droperidol
1.498
−0.738
107.586
379.433
4
5
6

CID_3185E-4031
2.063
−0.735
111.09
401.523
3
6
6

CID_3356_flecainide
2.981
−0.775
87.898
414.347
2
6
6

CID_3386_Fluoxetine
4.194
−0.371
80.368
309.331
2
6
6

CID_3510_Granisetron
1.705
−0.665
91.008
312.414
4
5
6

first
CID_3559_Haloperidol
3.378
−0.708
102.592
375.87
3
6
6

generation

CID_3696_imipramine
4.006
0.296
90.606
280.412
3
6
7

CID_4078_mesopridazine
3.048
−0.688
115.041
386.569
4
6
6

CID_4893_ prazosin
1.498
−0.761
102.974
383.406
4
5
6

Second
CID_5002_quetiapine
3.056
−0.709
113.801
383.507
4
6
7

generation

Second
CID_5073 risperidone
1.65
−0.849
116.156
410.49
5
5
6

generation

CID_5379_gatifloxacin
1.299
−1.001
97.997
375.399
4
3
6

CID_5401_ terazosin
1.017
−0.669
105.176
387.438
4
5
6

first
CID_5452 thioridazine
4.185
−0.42
113.669
370.57
4
6
6

generation

CID_5663 vesnarinone
1.867
−0.334
110.254
395.457
4
6
6

CID_40692_Mefloquine
4.246
−1.891
82.577
378.317
3
6
6

CID_60464 sparfloxacin
1.321
−0.812
100.868
392.405
4
3
6

Second
CID_60854_ziprasidone
3.444
−0.788
116.906
412.936
5
5
6

generation

CID_123618 norastemizole
3.179
−0.486
94.518
324.4
4
5
6

CID_129211 tamsulosin
2.21
−0.604
108.863
408.512
2
6
6

CID_149096_levofloxacin
1.087
−0.778
94.112
361.372
4
6
6

CID_152946_moxifloxacin
1.422
−0.858
105.4
401.437
5
3
6

CID_446220_cocaine
1.925
−0.314
80.662
303.357
3
5
6

Second
CID_450907_clozapine
3.582
−1.182
96.773
326.828
4
6
7

generation

CID_6604102_doxazosin
2.042
−0.784
121.638
451.481
5
6
6

Predicted Log

IC50 (nm) (C) =

−0.124236*M +

0.0305374*P +

1.0651*V −

Shape
Shape
Shape
Solvent
0.0639271*AH −

Index
Index
Index
Accessibility
0.380434*AO +

(basic
(basic
(basic
Surface Area
9.12642 rCV{circumflex over ( )}2 =

kappa,
kappa,
kappa,
(angstrom-
0.807357 r{circumflex over ( )}2 =

Chemical Sample
order 1)
order 2)
order 3)
square)
0.874903

CID_2351_bepridil
21.703
11.87
7.396
392.105
1.983

CID_2769_cisapride
26.602
13.185
7.759
484.148
2.51

CID_2771_citalopram
18.781
8.131
4.066
357.47
3.607

CID_2995_desipramine
14.917
7.32
3.442
308.272
3.708

CID_3148_dolasetron
16.194
6.311
2.823
330.621
4.338

CID_3168_droperidol
21.24
9.871
5.202
398.056
1.233

CID_3185E-4031
22.68
10.347
7.335
420.652
1.646

CID_3356_flecainide
24.271
10.858
9.58
376.177
3.805

CID_3386_Fluoxetine
18.34
8.741
5.864
333.528
3.177

CID_3510_Granisetron
16.467
6.719
3.133
340.013
3.557

first
CID_3559_Haloperidol
20.727
9.467
5.75
393.948
1.271

generation

CID_3696_imipramine
15.879
7.513
3.855
325.247
3.523

CID_4078_mesopridazine
19.322
8.566
4.224
382.602
1.907

CID_4893_ prazosin
21.24
9.428
4.542
391.721
3.803

Second
CID_5002_quetiapine
20.28
10.156
5.136
400.796
3.631

generation

Second
CID_5073 risperidone
21.825
9.469
4.578
425.463
1.745

generation

CID_5379_gatifloxacin
20.28
8.025
3.545
366.156
4.775

CID_5401_ terazosin
21.24
9.428
4.542
402.588
3.974

first
CID_5452 thioridazine
18.367
8.347
3.984
360.78
2.05

generation

CID_5663 vesnarinone
22.203
10.08
5.087
410.79
3.014

CID_40692_Mefloquine
20.727
7.788
4.543
332.742
4.281

CID_60464 sparfloxacin
21.24
7.922
3.55
369.708
4.286

Second
CID_60854_ziprasidone
19.934
8.626
4.258
404.49
2.01

generation

CID_123618 norastemizole
17.416
8.131
4.233
341.837
1.279

CID_129211 tamsulosin
24.271
12
7.987
444.184
3.672

CID_149096_levofloxacin
19.322
7.438
3.338
345.307
5.703

CID_152946_moxifloxacin
20.878
8.165
3.457
377.353
5.353

CID_446220_cocaine
16.844
7.266
3.44
317.583
3.847

Second
CID_450907_clozapine
16.467
7.087
3.52
327.498
4.59

generation

CID_6604102_doxazosin
24.684
10.948
5.259
452.689
2.903

ADVANTAGES OF THE INVENTION

1. The main advantage of our virtual screening model is that compounds are screened very fast thus readily providing hits for in-vitro screening.

2. The other major advantage of our model is that it avoids unnecessary animal scarifies in animal testing for drug discovery hence; it is the need of hour to switch to virtual screening.

2. The other major advantage of our model is that it will reduce many fold cost and duration of antipsychotic drug discovery.

3. The other advantage of our model is that virtual molecules can be easily, economically synthesized in less time.

4. It may provide structural novelty.

5. Apart from saving animal life, cost, and time this is very fast, reliable, statistically validated and has become one of the essential component of antipsychotic drug discovery.

6. This virtual screening model for prediction of antipsychotic activity may be of immense advantage in understanding action mechanism and directing the molecular design of lead compound with improved anti-psychotic activity.

7. The other advantage will be that we can update the present virtual screening model for better predicting accuracy of antipsychotic agents.

METHOD FOR PREDICTING AND MODELING ANTI-PSYCHOTIC ACTIVITY USING VIRTUAL SCREENING MODEL

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