Patent Application
20210134398
The present invention relates in general to the field of drug development. In particular, the present invention relates to modeling molecular syntheses in silico to identify likely promising combinations, and to eliminate likely unsuccessful combinations before synthesizing and experimenting with combinations.
Without limiting the scope of the invention, its background is described in connection with drug development. In particular the invention is described in connection with a use of one or more computer programs to model molecular syntheses.
In the last few decades, the quality and efficiency of scientific and technological tools that are important for progress in biopharmaceutical discovery and research have improved significantly. For example, DNA sequencing has become over a billion times faster since the first genome sequences were determined in the 1970s. The improvements in drug discovery tools should enable identification and evaluation of therapeutic candidates that have high reliability, efficacy, reproducibility, and safety. However, therapeutic candidates today are more likely to fail in clinical trials than those identified in the 1970s, while the cost to develop and gain marketing approval for a new therapeutic agent has increased to approximately $2.6 billion.
Organic chemistry is a rate-limiting factor in drug discovery. Investments in organic chemistry from drug discovery applications have decreased over time, with more focus toward applied research such as translational medicine and biomarker development. There are a number of chemical synthesis challenges in that most drug candidates contain amines, N-heterocycles, and unprotected polar groups that add to the complexity in synthesis.
In drug development program, especially in lead development and optimization, large sets of molecules that are related to a known molecule of interest are often synthesized with the intent of identifying derivative molecules that have better drug-like characteristics than those observed in the assays of the originally identified molecule. These organic chemistry syntheses are expensive and time-consuming, and they can be exceedingly laborious, requiring the skills and time of a team of highly qualified chemists. While some drug-like characteristics can be estimated using computational approaches, others require assessment by biochemical, biophysical, pharmacological, cell-biological, or animal experimentation. Often, hundreds or thousands of compounds are synthesized, with only a few variants showing desired improvement in pharmacological characteristics.
The prior art features Cramer et al. 1998 (likely the earliest available virtual chemistry program description); Krier et al. 2005 (uses a compound scaffold with linkers containing the functional group for reaction); Srinivasan et al. 2006 (uses pre-specified “click” chemistry to which the present invention is not restricted); Melnikov et al. 2007 (focuses on quantitative structure-activity relationships of the compounds); and Durrant and McCammon 2012 (uses pre-specified “click” chemistry to which the present invention is not restricted).
Another prior art method for combinatorial in silico drug-lead optimization exists, which the present invention uses. This prior art method is described below, and the present invention is distinguished from it.
It is desirable to improve on existing methods to enhance and accelerate organic synthesis chemistry through the use of computational systems and methods to identify likely useful molecular combinations.
In some embodiments of the disclosure, a system for identifying one or more potentially useful molecular combinations is disclosed as including applying a selection procedure to a compound of interest to identify a first set of one or more candidate molecules, the selection procedure including: providing a chemical synthesis scheme for a compound of interest, a virtual scaffold molecule of the compound of interest, and a virtual reactant fragment to react with the virtual scaffold molecule according to the chemical synthesis scheme; preparing the virtual reactant fragment and the virtual scaffold molecule for analyzing combinations of the virtual reactant fragment and the virtual scaffold molecule; designating a remaining scaffold subset and a remaining fragment subset if a product molecule can be formed from the virtual scaffold molecule and the virtual reactant fragment; rotating the remaining fragment subset about an axis connecting the remaining scaffold subset and the remaining fragment subset through 360 degrees in increments of less than or equal to 5 degrees; and identifying potentially useful combinations of the virtual reactant fragment and the virtual scaffold molecule, by: recording as a potential product increment each increment at which a steric collision is not detected; and recording a separation distance between the remaining fragment subset and the remaining scaffold subset at each increment and identifying a set of product increments for which the separation distances are less than or equal to a predetermined criterion distance to identify the one or more potentially useful molecular combinations; identifying a set of combinatorial fragments from the first set of one or more candidates; and applying the selection procedure to the set of combinatorial fragments to identify a second set of one or more candidate molecules that are the one or more potentially useful molecular combinations. In one aspect, the preparing the virtual reactant fragment and the virtual scaffold molecule includes providing a three-dimensional coordinate system for the virtual reactive fragment. In another aspect, the preparing the virtual reactant fragment and the virtual scaffold molecule includes identifying a fragment alignment atom and a fragment root atom in the virtual reactant fragment; and the preparing the virtual reactant fragment and the virtual scaffold molecule includes: identifying a scaffold alignment atom and a scaffold root atom in the virtual scaffold molecule; and providing a three-dimensional coordinate system for the virtual scaffold molecule and aligning the scaffold root atom with an origin and the scaffold alignment atom with an x-axis. In another aspect, the preparing the virtual reactant fragment and the virtual scaffold molecule includes: aligning the fragment alignment atom with the scaffold root atom; and aligning the fragment root atom with the scaffold alignment atom. In another aspect, the axis connecting the remaining scaffold subset and the remaining fragment subset is defined by the scaffold root atom and the virtual root atom. In another aspect, the identifying potentially useful combinations further includes creating a product file for a configuration of the remaining fragment subset and the remaining scaffold subset at each increment of the set of product increments.
In some embodiments of the disclosure, a non-transitory computer-readable medium encoded with a computer program for execution by a processor for identifying one or more potentially useful molecular combinations is disclosed, with the computer program including instructions for applying a selection procedure to a compound of interest to identify a first set of one or more candidate molecules, the selection procedure including: receiving a chemical synthesis scheme for a compound of interest, a virtual scaffold molecule of the compound of interest, and a virtual reactant fragment to react with the virtual scaffold molecule according to the chemical synthesis scheme; receiving input to prepare the virtual reactant fragment and the virtual scaffold molecule for analyzing combinations of the virtual reactant fragment and the virtual scaffold molecule; designating a remaining scaffold subset and a remaining fragment subset if a product molecule can be formed from the virtual scaffold molecule and the virtual reactant fragment; rotating the remaining fragment subset about an axis connecting the remaining scaffold subset and the remaining fragment subset through 360 degrees in increments of less than or equal to 5 degrees; identifying potentially useful combinations of the virtual reactant fragment and the virtual scaffold molecule by: recording as a potential product increment each increment at which a steric collision is not detected; and recording a separation distance between the remaining fragment subset and the remaining scaffold subset at each increment and identifying a set of product increments for which the separation distances are less than or equal to a predetermined criterion distance, to identify the first set of one or more candidate molecules; identifying a set of combinatorial fragments from the first set of one or more candidates; and applying the selection procedure to the set of combinatorial fragments to identify a second set of one or more candidate molecules that are the one or more potentially useful molecular combinations. In one aspect, the preparing the virtual reactant fragment and the virtual scaffold molecule includes providing a three-dimensional coordinate system for the virtual reactive fragment. In another aspect, the preparing the virtual reactant fragment and the virtual scaffold molecule includes identifying a fragment alignment atom and a fragment root atom in the virtual reactant fragment; and the preparing the virtual reactant fragment and the virtual scaffold molecule includes: identifying a scaffold alignment atom and a scaffold root atom in the virtual scaffold molecule; and providing a three-dimensional coordinate system for the virtual scaffold molecule and aligning the scaffold root atom with an origin and the scaffold alignment atom with an x-axis. In another aspect, the preparing the virtual reactant fragment and the virtual scaffold molecule includes: aligning the fragment alignment atom with the scaffold root atom; and aligning the fragment root atom with the scaffold alignment atom. In another aspect, the axis connecting the remaining scaffold subset and the remaining fragment subset is defined by the scaffold root atom and the virtual root atom. In another aspect, the identifying potentially useful combinations further includes creating a product file for a configuration of the remaining fragment subset and the remaining scaffold subset at each increment of the set of product increments.
In some embodiments of the disclosure, an apparatus is disclosed as including a processor; a memory communicably coupled to the processor; an output device communicably coupled to the processor; and a non-transitory computer-readable medium encoded with a computer program for execution by the processor that causes the processor to: apply a selection procedure to a compound of interest to identify a first set of one or more candidate molecules, the selection procedure including: receiving a chemical synthesis scheme for a compound of interest, a virtual scaffold molecule of the compound of interest, and a virtual reactant fragment to react with the virtual scaffold molecule according to the chemical synthesis scheme; receiving input to prepare the virtual reactant fragment and the virtual scaffold molecule for analyzing combinations of the virtual reactant fragment and the virtual scaffold molecule; designating a remaining scaffold subset and a remaining fragment subset if a product molecule can be formed from the virtual scaffold molecule and the virtual reactant fragment; rotating the remaining fragment subset about an axis connecting the remaining scaffold subset and the remaining fragment subset through 360 degrees in increments of less than or equal to 5 degrees; and identifying potentially useful combinations of the virtual reactant fragment and the virtual scaffold molecule, by: recording as a potential product increment each increment at which a steric collision is not detected; and recording a separation distance between the remaining fragment subset and the remaining scaffold subset at each increment and identifying a set of product increments for which the separation distances are less than or equal to a predetermined criterion distance, to identify the first set of one or more candidate molecules; identify a set of combinatorial fragments from the first set of one or more candidates; and apply the selection procedure to the set of combinatorial fragments to identify a second set of one or more candidate molecules that are the one or more potentially useful molecular combinations. In one aspect, the preparing the virtual reactant fragment and the virtual scaffold molecule includes providing a three-dimensional coordinate system for the virtual reactive fragment. In another aspect, the preparing the virtual reactant fragment and the virtual scaffold molecule includes identifying a fragment alignment atom and a fragment root atom in the virtual reactant fragment; and the preparing the virtual reactant fragment and the virtual scaffold molecule includes: identifying a scaffold alignment atom and a scaffold root atom in the virtual scaffold molecule; and providing a three-dimensional coordinate system for the virtual scaffold molecule and aligning the scaffold root atom with an origin and the scaffold alignment atom with an x-axis. In another aspect, the preparing the virtual reactant fragment and the virtual scaffold molecule includes: aligning the fragment alignment atom with the scaffold root atom; and aligning the fragment root atom with the scaffold alignment atom. In another aspect, the axis connecting the remaining scaffold subset and the remaining fragment subset is defined by the scaffold root atom and the virtual root atom. In another aspect, the identifying potentially useful combinations further includes creating a product file for a configuration of the remaining fragment subset and the remaining scaffold subset at each increment of the set of product increments.
For a more complete understanding of the features and advantages of the present invention, reference is now made to the detailed description of the invention along with the accompanying figures, in which:
Illustrative embodiments of the system of the present application are described below. In the interest of clarity, not all features of an actual implementation are described in this specification. It will of course be appreciated that in the development of any such actual embodiment, numerous implementation-specific decisions must be made to achieve the developer's specific goals, such as compliance with system-related and business-related constraints, which will vary from one implementation to another. Moreover, it will be appreciated that such a development effort might be complex and time-consuming but would nevertheless be a routine undertaking for those of ordinary skill in the art having the benefit of this disclosure.
In the specification, reference may be made to the spatial relationships between various components and to the spatial orientation of various aspects of components as the devices are depicted in the attached drawings. However, as will be recognized by those skilled in the art after a complete reading of the present application, the devices, members, apparatuses, etc. described herein may be positioned in any desired orientation. Thus, the use of terms such as “above,” “below,” “upper,” “lower,” or other like terms to describe a spatial relationship between various components or to describe the spatial orientation of aspects of such components should be understood to describe a relative relationship between the components or a spatial orientation of aspects of such components, respectively, as the device described herein may be oriented in any desired direction.
An objective of the present invention is an increase in the efficiency of drug development programs by performing iterative molecular syntheses using efficient computational approaches, instead of synthesizing large sets of compounds related to a molecule of interest using organic chemistry synthesis methods. The present invention allows the synthesis of large numbers of variants in silico to inform choices of which of the vast numbers of possible compounds to synthesize for experimentation, saving expense and time in the drug development process. After in silico production, the virtual compound variants are computationally assessed for any predicted improvements in pharmacological characteristics, including any characteristic that can be calculated, for example, physicochemical data, such as total polar surface area, log P values, molecular weight, etc. and more complex indicators of improved drug-like characteristics, for example, predicted toxicities, mutagenicity, likelihood of inducing potential drug-drug interactions (cytochrome P450 isozyme substrate character, etc.), increased binding affinities to targeted proteins, decreased bonding affinities to undesired protein targets, and more.
A prior art method for combinatorial in silico drug-lead optimization exists.
In the course of a typical virtual-computational or nonvirtual-wet-laboratory-based drug discovery program, initial candidate “hit” molecules are identified as molecules that may interact with and possibly inhibit or otherwise affect a given drug target (usually a cellular protein or a protein from a pathogen). The virtually identified molecules or those identified through conventional wet-lab procedures such as high throughput screens are then normally tested in wet-lab experimentation to verify their functional properties in a relevant assay that when successful, provides support for their interaction with, and effects on, the target. It is these initial hit molecules that are molecularly varied for potential identification of variant molecules that have more optimal molecular, biochemical and pharmacological properties using the prior art method 100.
The prior art method 100 (also, herein, “chemical variation procedure 100”) is used as a virtual chemical synthesis procedure in embodiments of the present invention a first time to produce thousands to millions of virtual variant candidate molecules in short periods of time, e.g., one to three days. From analyses performed by those skilled in organic chemical synthesis and/or medicinal chemistry, synthetic methods to synthesize the previously identified candidate molecule(s) are devised or elucidated from the literature. From the so-elucidated chemical synthetic pathways of the candidate molecules, a set of varied precursor molecules (combinatorial fragments) can be identified that would likely be capable of reaction to generate variants of the originally identified candidate “hit” molecule. By applying blocks 105-135 of prior art method 100, these fragments can be combined to identify a large set of thousands or millions of variant candidate molecules that are derivatives of the originally identified candidates that may possess one or more potentially useful molecular combinations.
The second set of one or more variant candidate molecules with predicted improvements are then synthesized by organic chemistry synthetic methods and tested using actual biochemical, biophysical, pharmacological, cell biological, and/or animal experimentation, including the chemical synthesis schemes identified originally identified for a compound of interest.
Another flow diagram for the prior art method 100 is shown in
The subsequent testing of these new variants of the originally identified hit molecule using computational molecular docking programs to identify improved ligand interactions (blocks 8-11 of prior art
Prior art for one type of intelligent pre-selection of compounds in
The type of intelligent pre-selection of compounds of interest as described in the prior art of Brewer et al. 2014, Follit et al. 2015 and Nanayakkara et al. 2018 as well as other selection schemes can be used with the prior art described in
The present invention, illustrated in a method embodiment 200 in
In the selection procedure 100 used in embodiments of the present invention, preparing the virtual reactant fragment and the virtual scaffold molecule for analyzing combinations of the virtual reactant fragment and the virtual scaffold molecule includes providing a three-dimensional coordinate system for the virtual reactive fragment. This may be done, for example, by identifying a three-dimensional coordinate system from a database of commercially available compounds such as zinc.docking.com or www.emolecules.com. SMILES-formatted or SDF-formatted 3D coordinate files for a virtual reactive fragment can be converted to PDB-type files by a program such as the openbabel program (O'Boyle et al. 2011) or the cactvs program (Ihlenfeldt et al. 2002; Ihlenfeldt et al. 1994).
In the selection procedure 100 used in embodiments of the present invention, preparing the virtual reactant fragment and the virtual scaffold molecule for analyzing combinations of the virtual reactant fragment and the virtual scaffold molecule also includes marking, via one or more marking programs, the virtual reactant fragment and the virtual scaffold molecule: identifying an alignment atom and a root atom in each of the virtual reactant fragment and the virtual scaffold molecule. In each case, a root atom is an atom that remains after the reaction and an alignment atom is an atom that does not remain after the reaction. A combination of bash (main_new10.bsh) and tcl (various generic_*.tcl) scripts running a program such as Visual Molecular Dynamics (Humphrey et al. 1996) may be used to mark the virtual reactant fragment and the virtual scaffold molecule. Using these tools, the alignment and the root atoms are marked in the beta column of respective 3D coordinate files. Each chemistry step which is inherent in marking is specifically programmed. This programming allows the selection procedure and embodiments of the present invention to go beyond the pre-specified “click” chemistries that limit some other prior art methods, but that do not limit the present invention.
In the selection procedure 100 used in embodiments of the present invention, preparing the virtual reactant fragment and the virtual scaffold molecule for analyzing combinations of the virtual reactant fragment and the virtual scaffold molecule further includes moving the root atom of the virtual scaffold molecule to the origin of the x,y,z coordinate system assigned to that molecule and orienting the alignment atom of the virtual scaffold molecule to the x-axis of that coordinate system. This preparation also includes aligning the alignment atom of the virtual reactant fragment with the root atom of the virtual scaffold molecule and aligning the root atom of the virtual reactant fragment with the alignment atom of the virtual scaffold molecule. A combination of bash and tcl scripts running a program such as Visual Molecular Dynamics may be used to prepare the virtual reactant fragment and the virtual scaffold molecule as described herein.
A virtual scaffold molecule of a compound of interest is a computer model of a molecule such as SMU 29 or SMU 45. A virtual reactant fragment is a computer model of a fragment that can be reacted with a compound of interest. The prior art method 100 and the prior art method 150 make use of modeling a reaction of the virtual reactant fragment with the virtual scaffold molecule according to the chemical synthesis scheme.
In the selection procedure 100 used in embodiments of the present invention, at each increment, steric hindrances of atoms may be assessed and recorded. If rotation through 360 degrees is completed and no solution without a steric hindrance is detected, a product of the remaining scaffold subset and the remaining fragment subset and is identified as failed. If increments of rotation are found that result in no steric hindrances, a separation distance between the remaining fragment subset and the remaining scaffold subset at each such increment is recorded and a set of product increments for which the separation distances satisfy one or more predetermined criteria is identified. For example, the increments with the most widely separated subset groups may be determined as preferred and identified as a preferred set of product increments.
Alternatively, in the selection procedure 100 used in embodiments of the present invention, at each increment, steric collisions of atoms may be assessed and recorded. If rotation through 360 degrees is completed and no solution without a steric collision is detected, a product of the remaining scaffold subset and the remaining fragment subset and is identified as failed. If increments of rotation are found that result in no steric collisions, a separation distance between the remaining fragment subset and the remaining scaffold subset at each such increment is recorded and a set of product increments for which the separation distances satisfy one or more predetermined criteria is identified. For example, the increments with the most widely separated subset groups may be determined as preferred and identified as a preferred set of product increments.
A virtual scaffold molecule of a compound of interest is a computer model of a molecule such as SMU 29 or SMU 45. A virtual reactant fragment is a computer model of a fragment that can be reacted with a compound of interest. The selection procedure used in embodiments of the present invention makes use of modeling a reaction of the virtual reactant fragment with the virtual scaffold molecule according to the chemical synthesis scheme.
In the selection procedure 100 used in embodiments of the present invention, analyzing combinations of the virtual reactant fragment and the virtual scaffold molecule includes identifying a remaining scaffold subset and a remaining fragment subset if a product molecule can be formed from the virtual scaffold molecule and the virtual reactant fragment. Then, the virtual scaffold molecule and the virtual reactant fragment are rotated about each other in increments around an axis defined by the root atoms of each virtual structure.
Further, the selection procedure 100 used in embodiments of the present invention uses the predicted binding energies and predicted fold improvements (defined as the ratio of the estimated Kd of the compound of interest to the predicted Kd of candidates for synthesis and testing) as factors in assessing the suitability of candidates for synthesis and testing.
Where a chemical synthesis scheme has one or more intermediate steps, as, for example the scheme for SMU 29 has, the method of the present invention can be repeated as necessary. Three-dimensional coordinates for a virtual reactant fragment for an intermediate step may be obtained as described herein. This intermediate virtual reactant fragment and the last product from the last analysis, as the intermediate virtual scaffold molecule of the intermediate compound of interest, can be prepared and analyzed as described herein. Potentially useful combinations of the intermediate virtual reactant fragment and the intermediate virtual scaffold molecule can be identified as described herein.
The skilled artisan will recognize that methods and systems of the present invention allows the synthesis of large numbers of variants in silico to inform choices of which of the vast numbers of possible compounds to synthesize for experimentation, saving expense and time in the drug development process.
Example of Use of an Embodiment of the Present Invention.
Resistances of cancers to chemically unrelated anti-cancer drugs are frequently caused by the expression of members of the ABC transporter superfamily, including ABCB1 (P-glycoprotein or P-gp)1-3 and/or ABCG2 (the breast cancer resistance protein or BCRP)3, 4. The phenomenon of multidrug resistance (MDR) remains a major obstacle in the treatment of both adult and pediatric cancers5-7. Despite close to 40 years of intense research, no inhibitor of these proteins has yet been approved for clinical use8-13. The reasons for failure in clinical trials are multifaceted: some could be attributed to flaws in trial design, others reported tumor penetration problems, and still others failed because of drug-drug interactions and associated toxicities. A significant number of failures of the clinical trials may be attributed to the fact that many of the assessed MDR-inhibitors were also good transport substrates of the pumps. This latter characteristic likely required elevated systemic inhibitor concentrations for efficacy that may have resulted in significant off-target toxicities. The fact that a Phase III trial using the immunosuppressant, cyclosporine A, led to improved patient outcomes in poor-risk acute myeloid lymphoma patients14 suggests, however, that despite the limited success in finding clinically successful inhibitors of MDR pumps, these proteins are important targets for drug discovery and development.
One of the biggest obstacles to developing effective inhibitors of membrane proteins like P-gp and BCRP has been the dearth of detailed structural and mechanistic knowledge, the lack of which made targeting these pumps ineffective. Over the last several years, however, significant advances in knowledge of the structure18-20 and mechanism21-25 of P-gp, BCRP and other related pumps have emerged that will enable the design of potent inhibitors of the pumps that may prove to be more successful in clinical applications.
Using the evolutionary relationship of different ABC transporters and the structural knowledge of both prokaryotic and eukaryotic ABC transporters, dynamic models of human P-gp 2 were created and a putative catalytic cycle22 was simulated that correlated well with published biochemical and biophysical studies as well as with the recently elucidated outward facing structure of the human P-gp16. These conformationally dynamic models of human P-gp in ultrahigh throughput in silico screenings were previously used to identify and characterize inhibitors of P-glycoprotein26. One desirable characteristic of the inhibitors identified in these screens was that these potential P-gp inhibitors should not be transport substrates of the pump26. For this reason, drug-like molecules that were computationally predicted to interact well with the nucleotide binding domains were computationally counter-screened for interactions with the drug binding parts of the protein. Compounds were discarded from further evaluation, if significant binding to the drug binding sites was predicted by the in silico docking calculations26. Using this approach, three compounds were initially identified and characterized that reversed the multidrug resistance phenotype of various cancer cell lines in both conventional and microtumor-spheroid cell cultures26-28. The efficacy of the compounds was assessed using P-gp overexpressing, multidrug resistant prostate and ovarian cancer cells in culture. All three compounds were observed to reverse multidrug resistance by increasing lethality of various chemotherapeutics. The increased lethality was correlated with increased cellular retention of the chemotherapeutics when inhibitor was present28. Importantly, studies also showed that these three P-gp inhibitors were not significantly transported by P-gp28, supporting the premise that these inhibitors would not bind effectively to the drug binding domains of the pump26.
One of these compounds that reversed MDR phenotypes in cancer cells was predicted to be an allosteric inhibitor of P-glycoprotein (“SMU-29”, “compound 29”, or “29” herein, 2-[(5-cyclopropyl-4H-1,2,4-triazol-3-yl)sulfanyl]-N-[2-phenyl-5-(2,4,5-trimethylphenyl)-pyrazol-3-yl,
Inspection of the computational docking of 29 at the putative allosteric site on P-gp (
A number of computational approaches exist that seek to analyze the potential chemical space of a hit compound by creating virtual libraries of variants of a given hit molecule29-32. These approaches mostly vary in the chemistry that is applied to perform the synthesis reactions. Presented herein are initial efforts at creating variants of compound 29 with optimized binding affinity to P-glycoprotein using a novel computer-aided and structure-based approach that was applied to the “Western” end of compound 29. Results of the virtual synthesis of a moderate number of variants of 29 and the virtual screening of these variants with structural models of P-gp are reported. A small portion of the nearly infinite chemical space around hit compound 29 was synthesized and assessed for reversal of the MDR phenotype in a multidrug resistant prostate cancer cell line that over-expresses P-gp (DU145TXR33). Using the same cell line, the inhibition of P-gp-catalyzed pumping of a P-gp substrate by these 29 variants was also assessed. In addition, biochemical analysis of the mode of P-gp inhibition was performed for all 29-variants using ATP hydrolysis and ATP binding assays as in26. After initial evaluation of the computationally predicted inhibitor variants in these assays as well as of the physicochemical properties of these variants, we developed a new, structure-based rational design to synthesize and analyze a small number of 29-derivatives with different structural and physicochemical characteristics. These compounds were not initially computationally evaluated using the subtractive binding routines as described in26, but were chosen mostly for the shape and size of the Western half of the molecule as well as for their physicochemical characteristics like polar surface area and solubility. All of the novel 29-variants were experimentally assessed for their potential of being transported by P-gp. The work led to the discovery of several variants of P-gp inhibitor hit compound 29 with improved efficacy in reversing MDR in P-glycoprotein over-expressing cancer cells by inhibiting P-gp catalyzed substrate pumping.
Results. Virtual synthesis of novel variants of the “Western” half of SMU-29 using the ChemGen computational suite. Evaluation of the fit of compound 29 into a putative allosteric binding site on P-gp as visualized from the results of docking studies the inventors recognized that if variants of inhibitor 29 were made larger and more hydrophobic they would likely fill the relatively large hydrophobic pocket in the protein where the cyclopropyl group of 29 interacts (
Some of the potential chemical space of these 647 ChemGen-produced “Western” variants of 29 (“Group 1” compounds) is visualized in
Docking to P-glycoprotein and chemical synthesis of compound 29 variants. The 647 Group 1 molecules created by ChemGen were used in docking studies to the same structural model of P-gp that was employed previously and led to the identification of compound 29 as a potential inhibitor26 (see steps 8 through 10 of
Estimated Kd values for the ligand interactions with P-gp were calculated from the lowest estimated binding ΔG values from the AutoDock calculations. The ratio of Kd values is shown as a relative value for increased affinity exhibited by the respective variants over the parent P-gp inhibitor compound 29. Molecular weights, topological polar surface areas, and consensus log P values were calculated at the SwissADME website (http://www.swissadme.c/) as described herein.
One additional compound (29-551) which contains abromo-substituent and has a molecular weight of 627 Da was added for consideration.
Syntheses were performed using the scheme shown in
The Group 1 ChemGen/docking routine produced variants of P-gp inhibitor 29 resensitize a multidrug resistant, P-gp overexpressing prostate cancer cell line to paclitaxel. The mitochondrial reduction potential of cells is often used as an indicator for cell viability using MTT assays4. Using these assays it was observed that the five Group 1 derivatives of 29 predicted through the ChemGen/docking routine and synthesized here, 216, 227, 231, 541 and 551, re-sensitized the P-gp overexpressing prostate cancer cell line, DU145TXR33, to the chemotherapeutic, paclitaxel (
Cytotoxicity of the chemotherapeutic, paclitaxel (PTX) to P-gp overexpressing prostate cancer cells, DU145TXR, was determined in the absence and presence of the ChemGen designed 29-variants, 216, 227, 231, 541 and 551. For each experimental compound IC50 values of PTX alone or in the presence of inhibitors, fold improvement of PTX sensitivity in the presence of inhibitor, and fold improvement of PTX sensitivity by variants compared to parental compound 29 are given.
At increasing concentrations, the efficacy of variant 216 in increasing paclitaxel 10 toxicity decreased when compared to the parental compound 29. At the highest concentration tested (10 μM), the 216 variant was observed to be somewhat less effective than parental compound 29 (0.4 fold compared to the 1 fold of paclitaxel+29). Unlike 216, variants 227, 231, 541 and 551 were more effective than 29 at all concentrations tested. At 3 μM, the presence of variants 227, 231, 541 and 551 resulted in 4 to 11-fold decreased paclitaxel IC50 when compared to parental compound 29 and up to 38-fold overall sensitization to paclitaxel when compared to paclitaxel alone (compound 551). At higher concentrations (5 to 10 μM), addition of these variants resulted in increased paclitaxel toxicity and decreased paclitaxel IC50 of up to 500-1000-fold at 10 μM, as compared to ˜100-fold sensitization caused by the parental compound 29 at 10 μM. This data indicated that variants 227, 231, 541 and 551 were better re-sensitizers of the multidrug resistant cells to paclitaxel than the original compound 29 at all concentrations tested, while variant 216 appeared to be marginally better than 29 at lower concentrations. These data demonstrate that the ChemGen generated and docking analyses selected Group 1 variants of compound 29 had increased affinity for P-gp resulting in improved efficacy for reversing chemotherapy resistance in a P-gp overexpressing cancer cell line than did the parental compound.
Accumulation and cellular retention of calcein AM in P-gp overexpressing prostate cancer cells upon incubation with Group 1 SMU-29 variants. Calcein AM accumulation assays have been used by us previously to evaluate P-gp-substrate accumulation in real time in the presence or absence of P-gp inhibitors28. For these assays, P-gp overexpressing DU145TXR cells were incubated with the respective inhibitors in the presence of the P-gp substrate, calcein AM. Inhibition of P-gp leads to cellular accumulation of calcein AM and to cleavage of its acetoxymethyl ester groups, resulting in the generation of the highly fluorescent compound, calcein. The anionic calcein is not a substrate of P-gp and remains in the cells. In these assays, the relative fluorescence of cellular calcein was measured over time and the results of these assays are shown in
To test whether the lower accumulation of calcein in the presence of the Group 1 29 variants was the result of retention of the compounds in the cellular membrane due to their mostly increased log P values relative to 29 (Table 1), similar calcein accumulation assays were performed after a 6-hour pre-incubation with the 29-variants and parental compound 29,
Assessing the roles of polarity and size of 29 variants in improving efficacy of compound 29 variants. To assess the contributions of overall hydrophobicity and size of the “western halves” of the 29-variants on efficacy in inhibiting P-gp and reversing multidrug resistance in cancer cells, five structural derivatives of 29 (“Group 2 variants”,
Estimated Kd values for the ligand interactions with P-gp were calculated from the lowest estimated binding ΔG values from the AutoDock calculations. The ratio of Kd values is given as a relative value for potentially changed affinities exhibited by the respective variants over the parent P-gp inhibitor compound 29. Molecular weights, topological polar surface areas, and consensus log P values were calculated at the SwissADME website (http://www.swissadme.ch/) as described herein.
The variations of structure in these molecules were made in the “western” half of the molecule (
Table 3 shows that all five of these Group 2 variants are somewhat larger than 29, but the calculated log P values for these Group 2 compounds (Table 3) are closer to that of 29 than the log P values of the Group 1 ChemGen generated variants with the exception of 541 (Table 1). The consensus log P values43, 44 of 238 and 255 were calculated to be 4.8 and 5.3, while those of 278, 280 and 286 were calculated to be 5.7, 6.0 and 5.2, respectively. The topological polar surface areas (TPSA) of 238 and 255 were calculated to be higher than those of 278, 280 and 286. These TPSA values were also higher than those of the Group 1 variants, 216, 227 and 231 (compare Tables 1 and 3). Of the five structural variants in Table 3, two had increased calculated topological polar surface areas and three had reduced calculated topological polar surface areas when compared with 29.
Subsequent docking of the Group 2 variants to the putative allosteric inhibitor binding site of P-gp showed that the “western” portions of compounds 238, 255 and 286 could penetrate deeper into the hydrophobic void than does compound 29, but that compounds 278 and 280 did not seem to penetrate into the hydrophobic void as well as does compound 29 (compare
Effects of Group 2 variants on the paclitaxel sensitivity of P-glycoprotein overexpressing prostate cancer cells, DU145TXR. MTT assays were again used to assess the efficacy of the new structural 29-variants on sensitizing the chemotherapy-resistant prostate cancer cell line, DU145TXR, to paclitaxel, at concentrations of 3 μM, 5 μM, 7 μM, and 10 μM as shown in
The data suggest that the presence of all of the variants except for 286 increased the paclitaxel toxicities to these P-gp overexpressing cells. Compounds 238 and 255 increased paclitaxel toxicities to the greatest extents: At 5 μM concentration, compound 238 decreased the paclitaxel IC50 by about a thousand-fold, similar to compound 255 at 7 μM. Comparison with parental compound 29 showed that 238 improved sensitization of DU145TXR to paclitaxel by 3.4-fold at 3 μM, and by around 100-fold at 5 and 7 μM. At 10 μM, compound 238 resulted in a 300-fold decreased paclitaxel IC50 of DU145TXR compared to parental compound 29 at the same concentration. Compound 255 also showed substantial improvement in sensitization of DU145TXR to paclitaxel that was comparable to 238 at 3 μM, but the effect was not as pronounced at higher concentrations. The other three compounds, 278, 280 and 286, were similar or less effective than the Group 1 variants, 216, 227 and 231. In addition, compound 280 seemed to exhibit some toxicity to the multidrug resistant cancer cells as judged by the lowered cell viability at very low concentrations of paclitaxel in the presence of 280 (
Accumulation and cellular retention of calcein AM in DU145TXR in the presence of 29-variants from Group 2.
Evaluation of mode of inhibition of P-glycoprotein by Group 1 and Group 2 variants of compound 29. To assess the mode of inhibition of P-gp by the novel variants of P-gp inhibitor 29, ATP hydrolysis by P-gp was evaluated in the presence or absence of the variants. Both “basal” ATP hydrolysis (assayed in the absence of added transport substrate) and “stimulated” ATP hydrolysis (assayed in the presence of the P-gp transport substrate, verapamil) were assessed as described in reference 266. Murine P-gp (MDR3) expressed in Pichia pastoris that had all naturally occurring cysteines replaced with alanine, was used45, 46. It is widely assumed that the ATP hydrolytic rate of P-gp is stimulated in the presence of transport substrates when compared to ATP hydrolysis in the absence of transport substrates. Assays comparing these rates can therefore be useful not only in identifying inhibitors of P-gp catalyzed ATP hydrolysis, but also to potentially infer whether a compound might be a transport substrate if basal ATPase rates are stimulated by the addition of a compound.
Effects of compound 29 variants on verapamil-stimulated ATP hydrolysis by P-gp. The effects of compound 29 variants on P-gp ATP hydrolysis rates assayed in the presence of verapamil (a good substrate for transport by P-gp) are presented in Table 5 A (“Stimulated ATPase”).
indicates data missing or illegible when filed
ATP hydrolysis assays using purified P-glycoprotein were performed without added transport substrate (“basal ATPase”) or in the presence of verapamil (“Stimulated ATPase”). Results are presented compared to DMSO control standard deviation (three independent experiments with duplicate samples). Basal activity of P-gp was 20 to 30 nmol/min mg, verapamil-stimulated rates were 200 to 400 nmol/min mg P-gp. Stimulation of basal ATPase by 29-variants was used as an indicator that a compound may be a P-gp transport substrate. Effects on stimulated P-gp ATPase activity indicated whether a compound directly interfered with ATP usage by the protein (***, p<0.001; **, p<0.01; *, p<0.1; NS, not significant). Quantitative cellular accumulation of 29-variants was performed using LC-MS/MS and is presented as a ratio of the cellular amounts of 29-variants in the presence of P-gp inhibitor, tariquidar, divided by amounts accumulated in its absence. A ratio >1 indicates that the compound likely is a transport substrate of P-gp (***, very significant; *, significant; NS, not significant). Binding of an ATP analog, SL-ATP, to P-gp was used to determine whether ATP binding to P-gp was affected by the 29-variants. Values +/−standard deviations are shown for at least three different P-gp preparations and three independent SL-ATP titration experiments. The values for SL-ATP binding in the presence of 29 were taken directly from Brewer et al. (2014).
The respective percent ATPase activity is shown, normalized to the ATPase in the presence of DMSO carrier/no added experimental compound. Interestingly, the Group 1 compounds differed in their effects on “stimulated” ATPase: 216 did not affect stimulated ATP hydrolysis activities, while compounds 227, 541 and 551 inhibited activity similar to parental compound 29. Compound 231 slightly stimulated ATP hydrolysis rates in the presence of verapamil. For Group 2 compounds, 238 stimulated the “stimulated” ATPase rates by about two-fold, while variant 280 showed only a slight stimulation of hydrolysis rates and compounds 255 and 286 had no significant effect. Only compound 278 of the Group 2 variants inhibited verapamil-stimulated ATP hydrolysis by P-gp similar to the parental compound 29.
Effects on “basal” ATP hydrolysis rates of compound 29 variants. Group 1 compounds 216, 227 and 541 did not significantly affect basal ATP hydrolysis by P-gp, while compound 231 inhibited the basal ATPase rates of P-gp. Only 551 of the Group 1 molecules stimulated basal ATPase activities of P-gp. Of the Group 2 compounds, 238, 255 stimulated basal ATPase by ˜10 and ˜3 fold respectively. Compounds 280 and 286 stimulated basal ATPase only marginally or with no statistical significance. Only compound 278 inhibited basal ATPase of P-gp. The relatively strong activation of basal ATPase by compounds 238 and 255 was suggestive that these two compounds and potentially to a lesser extent, compound 280, may be transport substrates of the pump. Compound 278 was not indicated to be a good transport substrate for P-gp since it inhibited basal ATPase by P-gp.
Intracellular accumulation of compound 29 variants. Cell accumulation assays for each of the 29 variants were performed as in reference28 to more directly assess whether the compounds were indeed transport substrates for P-gp. These assays measured the intracellular accumulation of the experimental compounds using LC-MS/MS methods after incubation with the P-gp over-expressing cell line, DU145TXR, in the absence and presence of the strong P-gp inhibitor, tariquidar47 (TQR). Low levels of cellular accumulation of a compound in the absence of tariquidar accompanied by much higher levels of accumulation in the presence of tariquidar suggests that the compound in question may be a transport substrate of P-gp. In other words, if a compound is an effective transport substrate for P-gp, active P-glycoprotein in these cells would limit intracellular accumulation, while inhibited P-gp would result in higher intracellular concentrations. Daunorubicin (DNR) is an example of a good transport substrate for P-gp and showed very strong cellular accumulation in these assays when P-gp was inhibited by tariquidar, but much less accumulation in the cells when P-gp was not inhibited (see
None of the Group 1 molecules tested resulted in intracellular accumulations that were considerably different in the absence versus presence of TQR, similar to the parental compound 29 (
Of the Group 2 compounds, variant 238 showed a very large and significant increase in intracellular accumulation in the presence of TQR (
To assess whether the observed discrepancies of compounds stimulating basal P-gp ATPase activity but not being transport substrates of the human pump in the cell culture assessments were due to the fact that these biochemical assays used a cysteineless variant of the mouse MDR3 P-glycoprotein, the experiments were repeated using normal human MDR1 P-gp. In order to stabilize the human protein for the activity assays, the protein was assembled into membrane nanodiscs as described herein. The results of the experiments are shown in Table 6.
ATP hydrolysis assays using purified P-glycoprotein were performed without added transport substrate (“basal ATPase”) or in the presence of verapamil (“Stimulated ATPase”). Results are presented compared to DMSO control ±standard deviation (three independent experiments with duplicate samples). The specific basal activity of normal human MDR1 P-gp was between 123 and 193 nmol min−1g−1, and transport substrate (verapamil) stimulated activity was between 193-263 nmol min−1mg−1. Effects on stimulated P-gp ATPase activity indicated whether a compound directly interfered with ATP usage by the protein (***, p<0.001; **, p<0.01; *, p<0.1; NS, not significant).
Interestingly, neither compound 29 nor any of is variants had a stimulatory effect on basal ATPase activity of the normal human protein reconstituted into membrane nanodiscs, while all of them significantly inhibited transport substrate (verapamil) stimulated activity. The results clearly indicate that the source (human vs. mouse) and potentially also the membrane environment of P-glycoprotein strongly affects the overall behavior of potential biochemical inhibitors.
Effects of 29 variants on binding of an ATP-analog to purified P-glycoprotein. ATP binding in the presence of the 29 variants was assessed in titration assays using a spin-labeled analog of ATP, 2′,3′-SL-ATP (2′,3′-(2,2,5,5,-tetramethyl-3-pyrroline-1-oxyl-3-carboxylic acid ester) ATP; (2′,3′ indicates a rapid equilibrium of the ester bond between the C2′ and C3′ of the ribose moiety))48-50, and electron spin resonance spectroscopy as described in26. Due to the lower stability of the human P-glycoprotein in the extended times needed for these experiments, the cysteineless mouse protein was used here. The goal was to assess whether binding of the 29 variants to P-gp affected nucleotide binding to the protein. Results of these assays are presented in Table 5A. Except for compounds 238 and 278, neither of which initially underwent the selective docking routines used for Group 1 compounds, none of the novel inhibitors affected maximal binding of the ATP analog or the apparent Kd, showing that the inhibitors were indeed targeted to the putative allosteric binding site on P-gp. Compounds 238 and 278 reduced SL-ATP binding to about 1 mol SL-ANP (adenine nucleotide with an undefined number of phosphoryl groups) bound per mol of enzyme, suggesting that these inhibitors may also interact with the nucleotide binding sites or may indirectly induce changes in nucleotide binding to P-gp that affect ATP binding.
In addition to evaluating the effects of the decreased hydrophobicity of the Group 2 variants on the reversal of MDR in cell-based assays, it was also of interest to evaluate whether or not the docking routines employed for the Group 1—ChemGen derived variants of 29 were better able to predict compounds that were not transport substrates of P-gp when compared to the Group 2 compounds. All five of the Group 1 molecules that were chosen though the subtractive docking routine and that were predicted to not interact well with the drug binding domains were observed to not be transport substrates. When Group 2 molecules were docked to a structural model of P-gp that was essentially identical to the one initially used to identify parental compound 29 as a P-gp inhibitor26 as well as to choose Group 1 variants, four of the five molecules were predicted to interact well with the drug binding domains and one was not predicted to bind well (data not shown). Three of these five predictions were confirmed by the LC MS/MS experiments described above. All in all, the experimental data for Groups 1 and 2 suggested that the subtractive docking method was predicting the correct outcome (transport substrate vs. no transport substrate) in 4 out of 5 cases or at 80%.
While optimization efforts of hit compound 29 did not include aspects of compound toxicity, it seems of interest to note that only one of the 29-variants (compound 541) showed some toxicity in cell viability assays in the P-gp overexpressing DU45TXR13 cancer cells when administered in the absence of chemotherapeutic. No significant toxicity of the compounds was observed in non-cancerous human lung fibroblast cells, HFL-151 (data not shown). In addition, toxicity of the chemotherapeutic, paclitaxel, was not increased in the presence of 29 or 29-variants in cells that do not overexpress P-gp, i.e. HFL-1 and the not chemotherapy resistant, not P-gp overexpressing prostate cancer line, DU14552 (data not shown). The overall results indicate that increased lethality of paclitaxel to the P-gp overexpressing cells was due to the inhibition of the pump and increased accumulation of paclitaxel to therapeutic levels within the cells. It should be noted that compounds 541 and 551 were not assessed in these latter experiments.
Using computational approaches to create novel variants of “hit” molecules from drug discovery programs. In drug development, often large sets of molecules that are related to a molecule of interest are synthesized to identify derivative molecules with better drug-like characteristics than those of the originally identified molecule. The required organic chemistry syntheses are expensive, costly in time, can be very laborious, and require the skills and time of highly qualified chemists. Often hundreds or thousands of compounds are synthesized with only a few variants showing desired improvements in pharmacological characteristics. Even in these early steps of a medicinal chemistry project, these efforts add to the already significant costs of drug development53. While some drug-like characteristics can be estimated from computational approaches, most require biochemical, biophysical, pharmacological, cell biological and/or animal experimentation to assess potential improvement over the parental compound, which again increases the time and expenditures required for each potential lead compound.
A number of virtual chemical synthesis computer programs have been previously described. Some use fragments annotated with reaction rules29 or compound scaffolds with chemically reactive linkers30, and still others use popular click chemistries that can easily translate into the laboratory31, 32 just to mention only a few. To make more informed choices about which of the vast numbers of possible compound variants to synthesize for subsequent testing, a set of computational routines (collectively called ChemGen) have been written and developed to synthesize in silico what can be very large numbers of variant compounds. The methods differ from predecessor methods in that retrosynthetic approaches to the discovered hit molecule synthetic routes are mimicked in the computations. This results in advantageous translation to actual chemical syntheses of identified variants of interest, is not constrained to one or a few chemical reaction types, but can theoretically encompass any chemical reaction. A disadvantage is that each reaction type must be programmed ahead of its implementation, but the ChemGen platform may be adapted to new chemistries relatively easily.
Next, the inventors determined whether an increase in the efficiency of drug development can be achieved by performing iterative virtual molecular syntheses using efficient computational approaches instead of physically synthesizing a large set of compounds related to a molecule of interest. After production of the virtual compound variant library, the new molecules were computationally assessed for predicted improvements in any pharmacological characteristics that can be calculated, including relatively simple physiochemical data (topological polar surface area or TPSA, log P values, molecular weight, etc.) as well as more complex indicators of improved drug-like characteristics such as predicted toxicities, mutagenicity, likelihood of inducing potential drug-drug interactions (cytochrome P450 isozyme substrate character, etc.). Other important factors that can be calculated and that are valuable for decision making are predicted increased binding affinities to targeted proteins as well as potentially decreased binding affinities to undesired protein targets of the drug lead compounds. In recent years, machine learning machine methods have been employed for predicting toxicities, various ADME characteristics and even protein-ligand binding affinities of molecules of potential interest54-59.
By creating hit variants computationally and then assaying them—again computationally—for improved characteristics, variants that do not possess the desired improved characteristics can be eliminated from consideration before any actual organic synthetic chemistry is performed. This path can lead to expedited and much more cost-effective syntheses of a relatively small number of potentially improved hit-variants. The latter part of this approach, namely computational counter-selection against compounds with characteristics that are undesirable, was used by us previously to identify molecules that inhibited P-gp catalysis, but that were not transport substrates of P-gp26-28. Counter selections such as these, used to eliminate from consideration compounds with undesirable target interactions, can be extended to any property of a molecule that is calculable. When coupled with virtual synthesis of hit variants, increasing the efficiency and cost-effectiveness of synthesis programs is practically assured.
Ligand docking methods as described in26 have previously led us to identify the P-glycoprotein inhibitor, compound 29, that served as the initial hit for further drug development. Compound 29 and several other hits discovered were evaluated in biochemical and biophysical studies for their mechanism of inhibition of P-gp action26, as well as for their potential to reverse multidrug resistance in different cancer cell lines in culture27, 28 Compound 29 was chosen here as an initial compound for further development mostly for the fact that binding of compound 29 was predicted to be at an allosteric site, away from the nucleotide binding sites of P-gp26. Biophysical assessment using electron spin resonance spectroscopy and a spin-labeled ATP analog suggested that ATP binding was not affected in the presence of the inhibitor, while ATP hydrolysis assays showed inhibition of ATPase activity26. A putative mechanism for P-gp inhibition by 29 can be envisioned when comparing the position to which 29 docked with high affinity26 in
A closer evaluation of the high affinity allosteric docking site of compound 29 to P-gp revealed a relatively large hydrophobic pocket where the cyclopropyl moiety of the “western” half of the molecule interacted with the protein (
Five of the 29 variants from Table 1 (216, 227, 231, 541 and 551) were chosen for actual chemical synthesis mostly based on the perceived ease of synthesis and expense of precursor fragments. All three variants added more volume to the “western” half of the molecules and all but 541 had lower TPSA and higher log P values than the original compound 29. Closer inspection of the docking poses of the three variants (
Cell viability assays using a P-gp overexpressing prostate cancer cell line indicated that all five of the 29 variants had improved characteristics over the parental 29 for causing cell mortality (summarized in Table 2). This remarkable result, that five out of five Group 1—ChemGen produced variants showed between 2.4-fold and 11-fold improvement over the performance of 29 in reversing P-glycoprotein-conveyed multidrug resistance phenotype (summarized in Table 2), underscores the utility of the ChemGen virtual synthesis approach and the employed docking selections for increasing affinity to P-gp. It is a reasonable conclusion that the larger Group 1 variants were able to interact more strongly with the protein as depicted in
In assays designed to allow quantification of the accumulation of the P-gp transport substrate, calcein AM, in cells that over-express P-gp, however, the larger, more hydrophobic Group 1 variants did not perform better than 29. Comparison of the calculated consensus log P values for variants 216, 227, 231 and 551 (6.6, 6.4, 5.7, and 5.9 respectively, Table 1) with the log P of the parental compound 29 (4.0, Table 1) led us to ask whether the lack of efficacy in inhibiting P-gp-catalyzed export of calcein AM may have been due to 29 variants being too hydrophobic to efficiently transfer across the cellular membrane to the cytosol-located nucleotide binding domains of P-gp for efficacious inhibition in the nucleotide binding domain of the protein to occur. The relatively short incubation times used in the calcein AM assays as shown in
Since the ChemGen/docking routine computational approach for selecting variants at the putative allosteric site resulted in larger but mostly also more hydrophobic “western” fragments in variants 216, 227, 231, 541 and 551 and since increased hydrophobicity may have limited utility of the compounds, the goal was to rationally design other variants of the “western” portion of compound 29 that might result in improved interactions with P-gp as well as more favorable physicochemical characteristics. In this light, five additional “western” derivatives of 29 were synthesized with varying shape, size and physicochemical properties, compounds 238, 255, 278, 280 and 286 (Group 2 variants). Again, the compounds were chosen for relative ease of synthesis as well as availability and expense of precursors. Unlike the previous set of ChemGen generated 29 variants (Group 1 variants), this latter set did not initially undergo the docking routines that selected for high affinity binding to the nucleotide binding domains and low affinity to the drug binding domains that were used to identify the parental compound 29 and the Group 1 variants. Instead these variants were chosen by visual inspection of the putative binding site, as well as by the calculated physicochemical properties of the resulting variants.
Efficacy of rationally designed Group 2 variants in reversing MDR caused by P-gp over-expression. If compounds 216, 227, 231 and 551 were too hydrophobic for favorable passage through the cellular membrane, thereby causing lowered efficacy of P-gp inhibition and decreased calcein AM accumulation in the P-gp overexpressing cells, then the more hydrophilic Group 2 derivatives, 238 and 255, as judged by their TPSA values and possibly 286 as judged by its log P value, might show increased re-sensitization of MDR cells to paclitaxel as well as improved calcein AM retention as compared to the other derivatives. These predictions were also based on the observed docking poses shown in
Effectiveness of the selective docking routines used on Group 1 variants to ensure targeting to the nucleotide binding domains and avoid the drug transport domains of P-gp. It was also of interest to investigate whether the subtractive docking routine performed on Group 1 variants added value to the overall process in selecting variants for synthesis and subsequent testing. Specifically, the docking selections employed were aimed at identifying compound 29 variants that preferentially bound to the nucleotide binding domains and were therefore not good transport substrates of P-gp. Comparison of the results from Group 1 compounds to the more traditional rationally designed Group 2 variants that were chosen without additional input on docking derived binding affinities to different substructures of the protein was therefore made. As can be seen in Table 5A, only compound 551 of the Group 1 variants selected through the ChemGen/docking routines stimulated “basal” ATP hydrolysis rates, and compound 231 inhibited basal ATPase activities. Intracellular accumulation assays which more directly measure whether a compound is a transport substrate of P-gp (see reference28) confirmed the predictions (Table 5,
On the other hand, intracellular accumulation data (summarized in Table 5) and stimulation of “basal” ATP hydrolysis activity of the mouse cysteine-less P-gp that was induced by Group 2 compounds 238, 255 and 286 (also summarized in Table 5) correlated quite well. Although the intracellular accumulation for compound 280 with or without addition of tariquidar were not observed to be significantly different, compound 280 did stimulate “basal” ATP hydrolysis in the absence of any other added transport substrate, which may indicate that this compound may also be a transport substrate of P-gp. However, the lack of stimulation of the human P-gp lets this conclusion be more doubtful. Compound 278 of Group 2 did not show differences in intracellular accumulation with or without tariquidar, but showed strong inhibition of both “basal” and verapamil-stimulated ATP hydrolysis of both orthologous enzymes. Compound 278 is therefore the only member of Group 2 that one can conclude is definitely not a transport substrate of P-gp, while 4 of the 5 Group 2 compounds either were transport substrates of P-gp or were potentially transport substrates of P-gp. In contrast to these conclusions, none of the five Group 1 molecules were transported by P-gp. Although the general case cannot be statistically proven since the number of synthesized and tested variants was too small, these studies show that the ChemGen produced variants that were selected against interactions at drug transporting structures on P-gp were much more likely not to be transport substrates of P-gp (five of five Group 1 variants were not observed to be transport substrates) than the Group 2 molecules that did not undergo the docking counter-selection procedures (where 4 out of 5 molecules were likely or potentially transport substrates for P-gp). It is very clear therefore that the docking and counter-selections were very effective in identifying 29 variants that were not transported by P-gp and that these procedures out-performed the rationally designed molecules that were not subjected to these selections.
Mechanism of action of the 29 variants. The effects of the 29 variants on verapamil-stimulated ATP hydrolysis rates catalyzed by P-gp (Table 5A and B) are consistent with the effects observed for the compounds in reversing MDR caused by P-gp (Tables 2 and 4). Group 1 compound 216 and Group 2 compound 286 had little effect in either the stimulated ATPase or the MDR reversal assays, likely indicating that these compounds do not strongly interact with P-gp under the conditions tested in these assays.
To assess whether the 29 variants also interacted with the nucleotide binding sites of P-glycoprotein, titration experiments using an electron spin resonance (ESR) active ATP analog, SL-ATP were performed, where the amount of P-gp bound SL-ANP was determined in the presence of the 29 variants (Table 5A). The results showed that none of the Group 1 variants significantly affected ATP binding while two of the Group 2 variants reduced ATP binding to about 1 mol per mol of protein. This again indicates that the selection process through ChemGen/selective docking was much more predictive of the effects the potential inhibitors have on the enzyme.
Among all compounds tested, the strongest reversal of MDR and the strongest stimulator of both “basal” and “verapamil-stimulated” ATPase activities was variant 238 of the Group 2 molecules. Compound 238, while strongly reversing MDR, was also the best transport substrate of all the variants tested, a characteristic that is deemed undesirable for any clinically relevant P-gp modulator lead as discussed above.
Group 2 compound 255 reversed MDR and moderately accelerated verapamil-stimulated ATPase rates, an effect that may be related to its role as a transport substrate of P-gp. Compound 280 affected MDR, ATP hydrolysis, as well as SL-ANP binding, but was not strong enough in any of these assays to warrant further study. Finally, Group 2 compound 278 affected MDR relatively weakly, but did inhibit both ATPase hydrolysis and SL-ANP binding to P-gp and therefore may warrant further study. Of the 10 new variants of the P-glycoprotein inhibitor compound 29 that were experimentally tested, compounds 227, 278, 541 and 551 inhibited verapamil-stimulated ATPase activity of the mouse cysteine-less P-gp similarly to that observed with the parental compound 29. However, the results using normal human P-gp reconstituted in a more native-like nanodisc environment indicate that relying on ATP hydrolysis assays, especially when not the same isoform of the enzyme is used and when the enzymes are in different environments (mixed micelles vs. nanodiscs), interpretations of results may not be as clear cut as often assumed.
It was found that the virtual synthesis of hit variants with a program suite like ChemGen combined with a novel selection of characteristics predicted from docking experiments, i.e., increased affinity to targeted structures and decreased affinity against sub-structures that should be avoided as employed here, resulted in efficient and cost-effective identification of five out of five variants assessed that met these goals, was demonstrated in every example tested so date. The comparison of physicochemical characteristics of the resulting new variants and the rational alteration of structure to investigate changed solubility properties (TPSA and log P) without the aid of computational prediction of desired properties, i.e. avoidance of transport structures on P-gp, led to the synthesis of molecules of which a majority was not targeted as desired, while every molecule that underwent the previous selection process inhibited as predicted. This is therefore a good example of how computational evaluation and selection of potential inhibitors before their actual synthesis adds to the speed and overall success rates in identifying hit-to-lead variants that possess desired characteristics.
Materials and methods.
Virtual synthesis of compound 29 derivatives using ChemGen. Because of the nature of the putative allosteric site shown for compound 29 and in light of rational design considerations, only a moderate set of variants were virtually synthesized using the ChemGen program. The ChemGen program and its use are described in detail herein below. In the virtual syntheses performed here, a scaffold molecule, 2-chloro-N-[1-phenyl-3-(2,4,5-trimethylphenyl)-1H-pyrazol-5-yl]acetamide, which is equivalent to the chloroacetamide that retains the “Eastern” substituent group from compound 29 was reacted with approximately 650 thiol compounds obtained by simple structural searches for thiols from the “clean drug-like” commercially available molecule set at the ZINC database34. The 2-chloro-N-[1-phenyl-3-(2,4,5-trimethylphenyl)-1H-pyrazol-5-yl]acetamide scaffold and the thiol precursor molecules were “marked” for reaction in ChemGen as described for the second reaction shown in
In silico docking of compound 29 variants to a model of human P-gp. AutoDock Vina60 and AutoDock 4.261-63 were used with a model of P-glycoprotein with drug binding domains open to the outside and nucleotide binding sites fully formed that was extracted from targeted molecular dynamics trajectories as described in21, 22. This conformation of P-gp is one that is very similar to the homologous Sav1866 crystal structure reported by Dawson and Locher64 and was the conformation with which compound 29 was originally identified26. Ligand docking was limited to a volume equivalent to 20×24×26 Å3 centered on the putative allosteric site of P-gp (see
Calculation of physicochemical properties. The SWISS-ADME server at http://www.swissadme.ch/ was used for the calculation of the physicochemical properties of the compounds as discussed in44.
Imaging of P-glycoprotein and ligands. The VMD (Visual Molecular Dynamics) program suite was used extensively in this work for the analysis of structural data and for the presentation of visual images65 and included the SURF surface representation program66 as well as the pdb2pgr67, 68 and APBS69, 70 programs for electrostatic/solvation calculations.
Synthetic procedures: All synthetic procedures and analyses of products are provided herein below.
Cell lines and cell culture. The chemotherapeutic sensitive DU145 human prostate cancer cells52 as well as the multidrug resistant sub-line, DU145TXR33 were generous gifts from Dr. Evan Keller (University of Michigan, Ann Arbor, Mich.). The multidrug resistant DU145TXR was maintained under positive selection pressure by supplementing complete medium with 10 nM paclitaxel (Acros Organics, NJ). Both cell lines were maintained in complete media consisting of RPMI-1640 with L-glutamine, 10% fetal bovine serum (FBS; BioWest, Logan, Utah), 100 U/mL penicillin and 100 μg/mL streptomycin in a humidified incubator at 37° C. and 5% CO2. The noncancerous human fetal lung cell line, HFL151, was kindly provided by Dr. Robert Harrod (Southern Methodist University, Dallas, Tex.) and maintained in complete media consisting of F-12K with L-glutamine, 10% FBS (BioWest, Logan, Utah), 100 U/mL penicillin, and 100 μg/mL streptomycin in a humidified incubator at 37° C. and 5% CO2. To promote attachment of HFL1 cells, growth surfaces were treated with 0.1 mg/mL rat tail collagen (BD Biosciences, Palo Alto, Calif.) in 0.02 N acetic acid for 10 min and rinsed with PBS prior to use. Cell culture materials were purchased from Corning Inc. (Corning, N.Y.) unless otherwise stated.
MTT cell viability assay. Cells were trypsinized from monolayers and seeded with 3000 cells in 150 μL of complete medium in a 96 well plate. After 24 hours, cells were treated for 48 hours with paclitaxel (Acros Organics, NJ) and/or P-gp inhibitory compounds dissolved in DMSO, or DMSO controls. All additions were diluted into complete medium. After 48 hours of treatment, MTT assays were performed as described41 using 5 mg/mL of MTT (Acros Organics, NJ) solution prepared in PBS (137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, 1.8 mM KH2PO4, pH 7.4). After 4 hours of incubation with MTT, the media was removed and the formazan crystals were dissolved in 100 μL of DMSO. The absorbance at 570 nm was then measured using a BioTek Cytation 5 imaging multi-mode reader (Bio-Tek, Winooski, Vt.). Percent viability was calculated using DMSO treated cells as representative for 100% viability, according to Equation 1. Background absorbance was determined using MTT and complete medium without cells and subtracted from all the test values. Equation 1:
The results were plotted as the mean with standard deviation (SD) of eight replicates per concentration from at least two independent experiments with n=8. The graphical representations and IC50 values were determined using four parameter variable slope non-linear regression, using the following equation: Y=bottom+(top-bottom)/(1+10{circumflex over ( )}((log IC50−X)*Hill Slope) (GraphPad Prism™, La Jolla Calif., USA, Version 6.05). The reported “fold sensitization” was calculated as follows, per Equation 2:
Calcein AM assay. To assess inhibition of P-gp-catalyzed transport of the P-gp pump substrate, calcein AM, DU145TXR cells were seeded in 96 wells plates and allowed to grow in complete medium until confluency was reached. Medium was removed, and cells were treated without 2 sM P-gp inhibitory compounds and 1 μg/mL calcein AM (Life Technologies, OR) and diluted into phenol red free RPMI 1640 media. To study the effect of pre-incubation of compounds, cells were treated with just P-gp inhibitory compounds and incubated at 37° C. for six hours before adding calcein AM. Fluorescence excitation at 485 nm with a 20 nm gate and at emission at 535 nm with a 20 nm gate was measured using a BioTek Cytation 5 imaging multi-mode reader (Bio-Tek, Winooski, Vt.) over 60 minutes in 20 minute intervals. DMSO was used as vehicle. Results were plotted as the mean with standard deviation (SD) of six replicates per concentration and are representative of at least two independent experiments.
Cellular Accumulation Assays for Experimental P-gp Inhibitors. Cells used (DU145TXR), cell culturing, cell exposure to compounds, cellular handling and extractions were performed as described in28. LC-MS/MS methods were performed as described in71 and as modified in28.
P-glycoprotein Purification. Cysteine-less MDR3 and the human normal MDR1 P-glycoprotein was recombinantly expressed in the yeast Pichia pastoris essentially as in45, 46 and used for assaying ATP hydrolysis and ATP binding to the protein in the presence of the 29-variants. Purification of the protein was performed as described49 with small modifications resulting in highly enriched P-gp in mixed micelles containing dodecyl maltoside (DDM) and lysophosphatidyl choline26.
Nanodisc assembly. Human P-gp in mixed detergent micelles obtained during protein purification, was reconstituted into nanodiscsas described in references73, 74 with small modifications. P-gp was assembled with membrane scaffold protein, MSP1E3D1 (Sigma-Aldrich) expressed in BL21 (DE3) and L-alpha-phosphatidylcholine (Sigma-Aldrich), at a ratio of 1:10:500 (P-gp:MSP:PC) in 50 mM Tris-CL (pH 8). The detergent was removed with Bio-Beads™ SM-2 Adsorbent Media (BioRad). Ni-NTA Agarose (Qiagen) chromatography was used to purify P-gp reconstituted nanodiscs using 6 bed volumes of start buffer (20% (v/v) glycerol, 50 mM Tris-CL pH 7.5 at 4° C., 50 mM NaCl), and 5 bed volumes of elution buffer (20% (v/v) glycerol, 50 mM Tris-Cl pH 7.5 at 4° C., 50 mM NaCl, 300 mM imidazole).
ATPase Activity Assays. ATP hydrolysis activity was measured using a coupled enzyme assay72 as modified in reference26. The specific basal activity of the mouse MDR3 cysteineless P-gp was between 20 and 30 nmol min−1mg−1, and transport substrate (verapamil) stimulated activity was 200-400 nmol min−1mg−1. The specific basal activity of normal human MDR1 P-gp was between 123 and 193 nmol min−1 mg−1, and transport substrate (verapamil) stimulated activity was between 193-263 nmol min−1mg−1.
ESR Measurements. ESR measurements were as described in26. The amount of protein-bound spin-labeled (SL) adenine nucleotide was determined as the difference between the known total concentration of SL-ATP (2′,3′-(2,2,5,5,-tetramethyl-3-pyrroline-1-oxyl-3-carboxylic acid ester) —ATP48) added and the free spin-labeled nucleotide (SL-ANP) observed in the experiment. Hyperbolic curve fitting of the results was performed using GraphPad Prism 7 to determine maximum binding and apparent affinity for the spin-labeled nucleotide. The equation used for the fitting the curves was y=P*x/(P2+x), where P1 corresponds to the maximum binding of SL-ANP (moles of SL-ANP bound per mole P-gp), and P2 equals the apparent dissociation constant for SL-ANP. To quantify the amount of free SL-ANP, standard curves were established where the signal amplitude of the high field signal of the ESR spectra of free SL-ANP in the absence of protein was correlated to the concentration of SL-ANP added. All ESR measurements were performed using a Bruker EMX 6/1 ESR spectrophotometer operating in X-band mode and equipped with a high sensitivity cavity. Spectra were acquired at a microwave frequency of 9.33 GHz, microwave power of 12.63 mW, 100 kHz modulation frequency and a resolution of 1024 points. The centerfield of the scan was at 3325 G and an area of 100 G was scanned. The peak to peak modulation amplitude was 1G and the time constant was set to 10.240 ms. The conversion time was 163.84 ms, resulting in a total time sweep of 167.772 s. The signal gain was adjusted for the SL-ATP concentrations in the different experiments.
Synthetic Procedures. General Materials and Methods.
The reactions were performed under nitrogen and dried glassware. Reagents were purchased from Sigma-Aldrich (St. Louis, Mo.), Alfa Aesar (Ward Hill, Mass.), EMD Millipore (Billerica, Mass.), Oakwood Chemical (West Columbia, S.C.), and Cayman Chemical (Ann Arbor, Mich.). Silica gel P60 (SiliCycle) was used for column chromatography and Analytical Chromatography TLC Silica gel 60 F254 (Merck Millipore, Darmstadt, Germany) was used for analytical thin layer chromatography. 1H NMR and 13C NMR spectra were used for analyzed the compounds by using CDCl3 (Cambridge Isotope Laboratories, Cambridge, Mass.) on a JEOL 500 MHz and BRUKER 400 MHz spectrometer in the Department of Chemistry at Southern Methodist University. Chemical abbreviations are used as follows: CH2Cl2, dichloromethane; EtOAc, ethyl acetate; THF, tetrahydrofuran; DMF, dimethylformamide; H2O, water; HBTU, O-benzotriazole-N,N,N′,N′-tetramethyl-uronium-hexafluoro-phosphate; DIPEA, N,N-diisopropylethylamine; KOH potassium hydroxide; DMSO, dimethylsulfoxide N2, nitrogen. High resolution mass spectroscopy was performed on a Shimadzu IT-TOF (ESI source) and low resolution mass spectroscopy was performed on a Shimadzu LCMS-8050 Triple Quadrupole LCMS (ESI source) or a Shimadzu Matrix Assisted Laser Desorption/Ionization MS (MALDI) at the Shimadzu Center for Advanced Analytical Chemistry at the University of Texas, Arlington.
Each substituted amine (1.0 equiv) was dissolved in 3 mL of anhydrous THF, followed by addition of one equivalent of Et3N. After placing the reaction mixture in an ice bath, 2-chloroacetyl chloride (1.2 equiv) was added dropwise for one hour and the reaction was stirred overnight at room temperature. After being concentrated, CH2Cl2 and water were added and the organic compounds were extracted three times with CH2Cl2. The organic layers were washed with brine, dried over Na2SO4, filtered, and concentrated.
General Synthesis for SN2 Coupling of Alkyl Thiols.
The reaction was performed by dissolving the thiol (1 equiv) in 3 mL of DMF (deoxygenated by bubbling N2) and adding K2CO3 (2 equiv). The chloroacetamide (1.2 equiv) was then added to the reaction mixture and stirred overnight at room temperature. The reaction was diluted in EtOAc and washed with water. The water layer was extracted three times with EtOAc, washed with brine, dried over Na2SO4, filtered and concentrated to give the crude product, which was purified as indicated.
Synthetic Procedures for Aromatic Sulfide Derivatives.
It will be understood that particular embodiments described herein are shown by way of illustration and not as limitations of the invention. The principal features of this invention can be employed in various embodiments without departing from the scope of the invention. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, numerous equivalents to the specific procedures described herein. Such equivalents are considered to be within the scope of this invention and are covered by the claims.
All publications and patent applications mentioned in the specification are indicative of the level of skill of those skilled in the art to which this invention pertains. All publications and patent applications are herein incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference.
The use of the word “a” or “an” when used in conjunction with the term “comprising” in the claims and/or the specification may mean “one,” but it is also consistent with the meaning of “one or more,” “at least one,” and “one or more than one.” The use of the term “or” in the claims is used to mean “and/or” unless explicitly indicated to refer to alternatives only or the alternatives are mutually exclusive, although the disclosure supports a definition that refers to only alternatives and “and/or.” Throughout this application, the term “about” is used to indicate that a value includes the inherent variation of error for the device, the method being employed to determine the value, or the variation that exists among the study subjects.
As used in this specification and claim(s), the words “comprising” (and any form of comprising, such as “comprise” and “comprises”), “having” (and any form of having, such as “have” and “has”), “including” (and any form of including, such as “includes” and “include”) or “containing” (and any form of containing, such as “contains” and “contain”) are inclusive or open-ended and do not exclude additional, unrecited elements or method steps. In embodiments of any of the compositions and methods provided herein, “comprising” may be replaced with “consisting essentially of” or “consisting of.” As used herein, the phrase “consisting essentially of” requires the specified integer(s) or steps as well as those that do not materially affect the character or function of the claimed invention. As used herein, the term “consisting” is used to indicate the presence of the recited integer (e.g., a feature, an element, a characteristic, a property, a method/process step, or a limitation) or group of integers (e.g., feature(s), element(s), characteristic(s), property(ies), method/process(s) steps, or limitation(s)) only.
The term “or combinations thereof” as used herein refers to all permutations and combinations of the listed items preceding the term. For example, “A, B, C, or combinations thereof” is intended to include at least one of: A, B, C, AB, AC, BC, or ABC, and if order is important in a particular context, also BA, CA, CB, CBA, BCA, ACB, BAC, or CAB. Continuing with this example, expressly included are combinations that contain repeats of one or more item or term, such as BB, AAA, AB, BBC, AAABCCCC, CBBAAA, CABABB, and so forth. The skilled artisan will understand that typically there is no limit on the number of items or terms in any combination, unless otherwise apparent from the context.
As used herein, words of approximation such as, without limitation, “about,” “substantial” or “substantially” refers to a condition that when so modified is understood to not necessarily be absolute or perfect but would be considered close enough to those of ordinary skill in the art to warrant designating the condition as being present. The extent to which the description may vary will depend on how great a change can be instituted and still have one of ordinary skill in the art recognize the modified feature as still having the required characteristics and capabilities of the unmodified feature. In general, but subject to the preceding discussion, a numerical value herein that is modified by a word of approximation such as “about” may vary from the stated value by at least 1, 2, 3, 4, 5, 6, 7, 10, 12 or 15%.
All of the devices and/or methods disclosed and claimed herein can be made and executed without undue experimentation in light of the present disclosure. While the devices and/or methods of this invention have been described in terms of particular embodiments, it will be apparent to those of skill in the art that variations may be applied to the compositions and/or methods and in the steps or in the sequence of steps of the method described herein without departing from the concept, spirit and scope of the invention. All such similar substitutes and modifications apparent to those skilled in the art are deemed to be within the spirit, scope, and concept of the invention as defined by the appended claims.
Furthermore, no limitations are intended to the details of construction or design herein shown, other than as described in the claims below. It is therefore evident that the particular embodiments disclosed above may be altered or modified and all such variations are considered within the scope and spirit of the disclosure. Accordingly, the protection sought herein is as set forth in the claims below.
Modifications, additions, or omissions may be made to the systems and apparatuses described herein without departing from the scope of the invention. The components of the systems and apparatuses may be integrated or separated. Moreover, the operations of the systems and apparatuses may be performed by more, fewer, or other components. The methods may include more, fewer, or other steps. Additionally, steps may be performed in any suitable order.
To aid the Patent Office, and any readers of any patent issued on this application in interpreting the claims appended hereto, applicants wish to note that they do not intend any of the appended claims to invoke 35 U.S.C. § 112(f) as it exists on the date of filing hereof unless the words “means for” or “step for” are explicitly used in the particular claim.
This application claims priority to U.S. Provisional Application Ser. No. 62/931,333, filed Nov. 6, 2019, the entire contents of which are incorporated herein by reference.
This invention was made with government support under GM094771 awarded by the National Institute of Health. The government has certain rights in the invention.
| Number | Date | Country | |
|---|---|---|---|
| 62931333 | Nov 2019 | US |
