Patent Application
20160378911
This application claims priority to Korean Patent Application No. 10-2015-0091956, filed on Jun. 29, 2015, and all the benefits accruing therefrom under 35 U.S.C. §119, the content of which in its entirety is herein incorporated by reference.
(a) Field
Exemplary embodiments of the invention relate to a method and an apparatus for discovering a protein which serves as a target of a target therapy in a body signal transferring network.
(b) Description of the Related Art
Cancer is one of typical complex system diseases, and occurs in about 34 percent of male adults and about 29 percent of female adults. The incidence rate of cancer has been rapidly increasing every year, and it is expected that there will be about 180,000 cancer patients in 2015 in Korea, for example. Although researchers around the world use an astronomical amount of research funds every year to overcome cancer, they have not yet accomplished an impressive result due to misunderstanding of cancer development, progression, and mechanisms, as well as the absence of systemic analysis.
Conventionally, a method of using combinations of anti-cancer agents has been used to overcome multi-drug resistant cancer. However, simply using the combinations of anti-cancer agents makes it difficult to suggest a method of treating specific cancers caused by specific mutagenesis.
Therefore, a target therapy which may selectively attack cancer cells while minimizing damage to normal cells has been researched to reduce adverse reactions to the conventional anti-cancer agents. The target therapy may prevent cancer from developing and spreading by suppressing actions of specific molecules relating to cancer growth and development. Further, a cancer-treating solution using a body signal transferring network has been being researched to recognize a living thing as one system beyond the viewpoint of a protein or a single gene which specializes in a particular function.
The invention has been made in an effort to provide a method and an apparatus for effectively discovering a protein which serves as a target of a target therapy by using a body signal transferring network and a Boolean network model.
An exemplary embodiment of the invention provides a discovery method of a protein which serves as a target of a target therapy, including performing an attractor analysis on a first body signal transferring network of a cancer cell that is perturbed, and determining at least one of a plurality of proteins included in a third body signal transferring network of a cancer cell as a target protein based on the attractor analysis on the first body signal transferring network and an attractor analysis on a second body signal transferring network of a normal cell.
In an exemplary embodiment, the performing may include modeling the third body signal transferring network by applying a mutation map of a cancer state to the second body signal transferring network, modeling the first body signal transferring network by perturbing at least one of a plurality of proteins included in the third body signal transferring network, and simulating a signal-transmitting operation of the first body signal transferring network by using a Boolean network model.
In an exemplary embodiment, the modeling of the first body signal transferring network may include modeling the first body signal transferring network by perturbing a combination of some of a plurality of proteins included in the third body signal transferring network.
In an exemplary embodiment, the simulating may includes determining the Boolean network model relating to a mutual relationship of the proteins included in the first body signal transferring network, and time-dynamically simulating the first body signal transferring network based on the Boolean network model.
In an exemplary embodiment, the simulating may include generating a truth table relating to the mutual relationship of the proteins included in the first body signal transferring network based on the Boolean network model, generating a state transition table showing state transition of the proteins based on the truth table, and determining an attractor indicating a final state of each protein included in the first body signal transferring network by generating a state transition diagram based on the state transition table.
In an exemplary embodiment, the simulating may include calculating a basin size of an attractor of the perturbed cancer cell based on the simulation result of the first body signal transferring network.
In an exemplary embodiment, the determining may include comparing a basin size of an abnormal one of attractors of the normal cell with a basin size of an abnormal one of attractors of the perturbed cancer cell, and, when a difference between the basin size of the abnormal one of the attractors of the normal cell with the basin size of the abnormal one of the attractors of the perturbed cancer cell is smaller than a predetermined value, determining at least one perturbed protein of the proteins included in the third body signal transferring network as the target protein.
In an exemplary embodiment, the determining may include comparing a first basin size ratio of normal attractors and abnormal attractors among attractors of the normal cell with a second basin size ratio of normal attractors and abnormal attractors among attractors of the perturbed cancer cell, and, when a difference between the first basin size ratio and the second basin size ratio is smaller than a predetermined value, determining at least one perturbed protein of the proteins included in the third body signal transferring network as the target protein.
In an exemplary embodiment, the determining may further include, when at least two of the proteins included in the third body signal transferring network are the target protein, determining at least one of combinations of the at least two proteins as the target protein.
In an exemplary embodiment, the determining may include, when at least two of the proteins included in the third body signal transferring network are the target protein generating a fourth body signal transferring network by making combinations of the at least two proteins and perturbing the combinations of the at least two proteins, and re-performing the attractor analysis on the fourth body signal transferring network.
An exemplary embodiment of the invention provides a discovery apparatus of a protein which serves as a target of a target therapy, including at least one processor, a memory, and a transceiver, wherein the at least one processor executes at least one program stored in the memory to perform performing an attractor analysis on a first body signal transferring network of a cancer cell that is perturbed, and determining at least one of a plurality of proteins included in a third body signal transferring network of a cancer cell as a target protein based on the attractor analysis on the first body signal transferring network and an attractor analysis on a second body signal transferring network of a normal cell.
In an exemplary embodiment, the at least one processor may perform modeling the third body signal transferring network by applying a mutation map of a cancer state to the second body signal transferring network, modeling the first body signal transferring network by perturbing at least one of a plurality of proteins included in the third body signal transferring network, and simulating a signal-transmitting operation of the first body signal transferring network by using a Boolean network model.
In an exemplary embodiment, the at least one processor, when performing the modeling of the first body signal transferring network, may perform modeling the first body signal transferring network by perturbing a combination of some of a plurality of proteins included in the third body signal transferring network.
In an exemplary embodiment, the at least one processor, when performing the simulating, may perform determining the Boolean network model relating to a mutual relationship of the proteins included in the first body signal transferring network, and time-dynamically simulating the first body signal transferring network based on the Boolean network model.
In an exemplary embodiment, the at least one processor, when performing the simulating, may perform generating a truth table relating to the mutual relationship of the proteins included in the first body signal transferring network based on the Boolean network model, generating a state transition table showing state transition of the proteins based on the truth table, and determining an attractor indicating a final state of each protein included in the first body signal transferring network by generating a state transition diagram based on the state transition table.
In an exemplary embodiment, the at least one processor may perform calculating a basin size of an attractor of the perturbed cancer cell based on the simulation result of the first body signal transferring network.
In an exemplary embodiment, the at least one processor, when performing the determining, may perform comparing a basin size of an abnormal one of attractors of the normal cell with a basin size of an abnormal one of attractors of the perturbed cancer cell, and, when a difference between the basin size of the abnormal one of the attractors of the normal cell with the basin size of the abnormal one of the attractors of the perturbed cancer cell is smaller than a predetermined value, determining at least one perturbed protein of the proteins included in the third body signal transferring network as the target protein.
In an exemplary embodiment, the at least one processor, when performing the determining, may perform comparing a first basin size ratio of normal attractors and abnormal attractors among attractors of the normal cell with a second basin size ratio of normal attractors and abnormal attractors among attractors of the perturbed cancer cell, and, when a difference between the first basin size ratio and the second basin size ratio is smaller than a predetermined value, determining at least one perturbed protein of the proteins included in the third body signal transferring network as the target protein.
In an exemplary embodiment, the at least one processor, when performing the determining, may perform, when at least two of the proteins included in the third body signal transferring network are determined as the target protein, determining at least one of combinations of the at least two proteins as the target protein.
In an exemplary embodiment, the at least one processor, when performing the determining, performs, when at least two of the proteins included in the third body signal transferring network are determined as the target protein generating a fourth body signal transferring network by making combinations of the at least two proteins and perturbing the combinations of the at least two proteins, and re-performing the attractor analysis on the fourth body signal transferring network.
According to the exemplary embodiment of the invention, it is possible to develop an effective target therapy for a disease such as a cancer caused by activation or inactivation of a specific protein by determining a target protein by calculation of a basin size of an attractor of a body signal transferring network through the Boolean network model.
The above and other exemplary embodiments, advantages and features of this disclosure will become more apparent by describing in further detail exemplary embodiments thereof with reference to the accompanying drawings, in which:
In the following detailed description, only certain exemplary embodiments of the invention have been shown and described, simply by way of illustration. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature and not restrictive. Like reference numerals designate like elements throughout the specification.
It will be understood that when an element is referred to as being “on” another element, it can be directly on the other element or intervening elements may be therebetween. In contrast, when an element is referred to as being “directly on” another element, there are no intervening elements present.
It will be understood that, although the terms “first,” “second,” “third” etc. may be used herein to describe various elements, components, regions, layers and/or sections, these elements, components, regions, layers and/or sections should not be limited by these terms. These terms are only used to distinguish one element, component, region, layer or section from another element, component, region, layer or section. Thus, “a first element,” “component,” “region,” “layer” or “section” discussed below could be termed a second element, component, region, layer or section without departing from the teachings herein.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms, including “at least one,” unless the content clearly indicates otherwise. “Or” means “and/or.” As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items. It will be further understood that the terms “comprises” and/or “comprising,” or “includes” and/or “including” when used in this specification, specify the presence of stated features, regions, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, regions, integers, steps, operations, elements, components, and/or groups thereof.
Furthermore, relative terms, such as “lower” or “bottom” and “upper” or “top,” may be used herein to describe one element's relationship to another element as illustrated in the Figures. It will be understood that relative terms are intended to encompass different orientations of the device in addition to the orientation depicted in the Figures. In an exemplary embodiment, when the device in one of the figures is turned over, elements described as being on the “lower” side of other elements would then be oriented on “upper” sides of the other elements. The exemplary term “lower,” can therefore, encompasses both an orientation of “lower” and “upper,” depending on the particular orientation of the figure. Similarly, when the device in one of the figures is turned over, elements described as “below” or “beneath” other elements would then be oriented “above” the other elements. The exemplary terms “below” or “beneath” can, therefore, encompass both an orientation of above and below.
“About” or “approximately” as used herein is inclusive of the stated value and means within an acceptable range of deviation for the particular value as determined by one of ordinary skill in the art, considering the measurement in question and the error associated with measurement of the particular quantity (i.e., the limitations of the measurement system). For example, “about” can mean within one or more standard deviations, or within ±30%, 20%, 10%, 5% of the stated value.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and the invention, and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Exemplary embodiments are described herein with reference to cross section illustrations that are schematic illustrations of idealized embodiments. As such, variations from the shapes of the illustrations as a result, for example, of manufacturing techniques and/or tolerances, are to be expected. Thus, embodiments described herein should not be construed as limited to the particular shapes of regions as illustrated herein but are to include deviations in shapes that result, for example, from manufacturing. In an exemplary embodiment, a region illustrated or described as flat may, typically, have rough and/or nonlinear features. Moreover, sharp angles that are illustrated may be rounded. Thus, the regions illustrated in the figures are schematic in nature and their shapes are not intended to illustrate the precise shape of a region and are not intended to limit the scope of the claims.
Referring to
First, a protein discovery apparatus 100 (refer to
The Boolean network model according to the exemplary embodiment of the invention, which is a modeling method for indicating an active state of living molecules as activity (on) and non-activity (off), may model a discrete dynamical network having time and states of discrete values. Nodes of the Boolean network model include a plurality of protein molecules (xn), and each node may indicate states of the protein molecules. Further, each node may be connected to at least one link. Hereinafter, a method of simulating a signal transferring operation of the body signal transferring network by the protein discovery apparatus 100 based on the Boolean network model according to an exemplary embodiment of the invention will be described in detail with reference to
Referring to
In a truth table of the Boolean network model, when each protein is in an active (on) state, proteins x1, x2, x3, and x4 may be indicated by ‘1,’ and when each protein is in a non-active (off) state, the proteins x1, x2, x3, and x4 may be indicated by ‘0.’
Tables 1 to 4 show truth tables of the Boolean network illustrated in
Referring to
Further, a link of the Boolean network model may represent positive or negative actions. In this case, the positive action indicates an activation action, and the negative action indicates an inhibition action.
A simulation by the Boolean network model may be performed according to a discrete time step. In an exemplary embodiment, a state of a specific node at a time [t+1] may be determined by a state of an input node of a link connected to the specific node at a time [t], for example. In this case, when the time passes from the time t to the time t+1, states of all nodes may be simultaneously updated.
Referring back to
When the Boolean network model includes n protein molecules where n is a natural number, there may be 2n states of the Boolean network model at a maximum. Referring to
An attractor indicates a final state of a body signal transferring network that is finally converged by the body signal transferring network simulated by using the Boolean network model. In an exemplary embodiment, after a simulation of the body signal transferring network by the Boolean network model is performed in a discrete time step, the nodes of the Boolean network model are converged into at least one specific node. In this case, it may be determined as an attractor. Attractors of at least one attractor included in one Boolean network model are exclusive to each other.
A method of discovering an attractor and calculating a basin area of the attractor will be described in detail with reference to
In
Referring to
First, when a cell proliferation operation is adjustable as in normal cells, the attractors may be classified into normal attractors, and otherwise, the attractors may be classified into abnormal attractors. In this case, it may be determined according to activity of a CyclinD gene whether the cell proliferation operation is adjustable.
Second, when the cell proliferation operation is properly performed, the attractors may be classified into normal attractors, and otherwise, the attractors may be classified into abnormal attractors. In this case, it may be determined according to whether the activation is performed in order of CyclinD→CyclinE→CyclinA→CyclinB whether the cell proliferation operation is properly performed.
Third, when cell migration exists, the attractors may be classified into abnormal attractors. When there is no cell migration, the attractors may be classified into normal attractors. In this case, the cell migration may be determined based on an activation state of Rho and MMP genes.
In an exemplary embodiment, the attractors according to the illustrated exemplary embodiment include fixed-point attractors and circle attractors, for example. The fixed-point attractors indicate attractors having one state, and the circle attractors indicate attractors having two or more states. Referring to
Referring to
Referring to
Hereinafter, a change in the basin size of a cancer cell will be described with reference to
The colorectal cancer as a representative cancer disease occurs when mutation is sequentially generated in a normal cell in order of APC→Ras→Pten→p53 genes.
However, referring to
Referring to
Therefore, the protein discovery apparatus 100 may discover a target protein by comparing basin sizes of normal attractors and abnormal attractors included in normal cells and cancer cells perturbed with proteins.
Referring back to
In this case, ‘perturbation’ indicates changing the state of the selected protein, and the state of the perturbed protein may be changed into an active state or a non-active state. The body signal transferring network of the cancer cell may be generated by applying a mutation map for a cancer state to the body signal transferring network.
In the exemplary embodiment, when one protein is selected as a perturbation target, the simulation of the body signal transferring network may be performed a number of times corresponding to the number (e.g., m) of the proteins. In an alternative exemplary embodiment, in another exemplary embodiment of the invention, when a combination of the proteins is selected as a perturbation target, the simulation of the body signal transferring network of the perturbed cancer cell may be performed (2m−1) times, for example.
Next, the protein discovery apparatus 100 according to the exemplary embodiment calculates a basin size of an attractor based on the simulation result of the body signal transferring network of the perturbed cancer cell (S204). When at least one of the proteins included in the body signal transferring network is perturbed, the basin size of the attractor may be reduced or increased after the simulation of the body signal transferring network, and the protein discovery apparatus 100 according to the exemplary embodiment may calculate the changed basin size. In this case, according to another exemplary embodiment of the invention, the protein discovery apparatus 100 may selectively calculate a basin size for a normal attractor or an abnormal attractor.
Next, the protein discovery apparatus 100 according to the exemplary embodiment compares the basin sizes of the attractors of the normal cell and the perturbed cancer cell. In this case, for the compassion of the basin size of an attractor, the protein discovery apparatus 100 according to the exemplary embodiment may use both the basin sizes of the normal attractor and the abnormal attractor as comparison targets, and may use one of the basin sizes of the normal attractor and the abnormal attractor as the comparison target. In this case, the protein discovery apparatus 100 may perform the calculation of the basin sizes of the attractors of the perturbed cancer cell a number of times corresponding to the number of the proteins included in the body signal transferring network, and thus the comparison of the basin sizes of the attractors may be performed the number of times corresponding to the number of the proteins included in the body signal transferring network at the least.
Next, the protein discovery apparatus 100 determines a target protein candidate among the proteins included in the body signal transferring network based on the comparison result of the basin sizes of the attractors (S206). In an exemplary embodiment, in the exemplary embodiment, when an attractor calculated as a result of perturbation of one protein has a basin size that is similar to the basin size of the attractor of the normal cell, the protein discovery apparatus 100 may determine the protein as a candidate of the target protein. In this case, the determination of whether the basin size of the attractor of the normal cell is similar to the basin size of the attractor of the perturbed cancer cell may be made through a predetermined threshold value. In an exemplary embodiment, when a difference between the basin size of the abnormal attractor among the attractors of the perturbed cancer cell and the basin size of the abnormal attractor among the attractors of the normal cell is smaller than the predetermined threshold value, the perturbed protein may be determined as a target protein candidate, for example.
The protein discovery apparatus 100 according to the exemplary embodiment simulates the body signal transferring network by perturbing a specific protein, and calculates the basin size of the attractor based on the simulation result. Accordingly, the basin size of the attractor based on the result of the simulation that is performed on one perturbed body signal transferring network may correspond to one protein.
In an alternative exemplary embodiment, according to another exemplary embodiment of the invention, the protein discovery apparatus 100 may compare a basin size ratio of the normal attractor and the abnormal attractor of the perturbed cancer cell with a basin size of the attractors of the normal cell. In this case, when the basin size ratio (e.g., 8:2) of the normal attractor and the abnormal attractor of the perturbed cancer cell is similar to the basin size of the attractors of the normal cell, the perturbed protein may be determined as a target protein candidate. In this regard, this determination may be made based on whether similarity of the basin size ratio or a difference between the basin size ratios exceeds a predetermined threshold value.
Referring back to
Hereinafter, a target protein discovery result of the protein discovery apparatus 100 and a target protein determining method will be described in detail with reference to
Next, the protein discovery apparatus 100 according to the illustrated exemplary embodiment may additionally perform the attractor analysis on a combination of the above-mentioned genes. In an exemplary embodiment, the attractor analysis on the cases where the Raf and Ras genes are simultaneously performed, where the Raf and Mek genes are simultaneously performed, where the Ras and Mek genes are simultaneously performed, and where the Raf, Ras, and Mek genes are simultaneously performed may be additionally performed, for example.
Next, the protein discovery apparatus 100 according to the exemplary embodiment may determine at least one of a plurality of target protein combinations as a target protein combination to which the target therapy is to be applied.
According to another exemplary embodiment of the invention, in the case where the protein discovery apparatus 100 simulates the body signal transferring network by perturbing a combination of proteins, when the basin size of the attractor calculated based on the simulation result is similar to the basin size of the attractor of the normal cell, the combination of proteins may be determined as a target protein combination.
Referring to
Finally, the comparison of the basin size of the attractor of the normal cell and the basin size of the attractor of the cancer cell perturbed with the target protein is performed, and a target therapy effect is expected according to the comparison result (S1003). As a result, as the basin size of the attractor of the cancer cell perturbed with the target protein approaches the basin size of the attractor of the normal cell, an outstanding target therapy effect may be expected.
Referring to
In the exemplary embodiment of the invention, the memory 102 may be disposed inside or outside the processor 101, and may be connected to the processor 101 through various already known means. In an exemplary embodiment, the memory 102 may be various types of volatile or non-volatile storage media, and may include, for example, a read-only memory (“ROM”) or a random access memory (“RAM”).
While this invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
| Number | Date | Country | Kind |
|---|---|---|---|
| 10-2015-0091956 | Jun 2015 | KR | national |
