CN103049678B - Based on the treating different diseases with same method molecule mechanism analytical approach of protein reciprocation network - Google Patents
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Abstract
The invention discloses a kind of analytical approach disclosing treating different diseases with same method molecule mechanism, for analyzing the molecule mechanism without disease, identical treatment, comprising the steps: S1, building various disease protein reciprocation network separately; S2, predict according to the chemical composition of medicine of ruling together and the potential target of each compound in this medicine of ruling together retain the compound of answering target with the gene pairs of described disease association; S3, according to the distribution in the protein reciprocation network of each disease of the potential target of chemical composition of medicine of ruling together to medicine of ruling together in each compound carry out cluster; The frequent target combination occurred is determined in S4, each class in described cluster bunch; S5, the node corresponding to the target of the numerous appearance of protein reciprocation network intermediate frequency of various disease are analyzed, to obtain the molecule mechanism of medicine to described at least two kinds of diseases of ruling together.The present invention can be used for making an explanation from the mechanism of identical treatment principle of molecular layer in the face of various disease, is particularly useful for the theoretical utilization in the clinical and combination of Chinese tradiational and Western medicine of the treating different diseases with same method of the traditional Chinese medical science and development.
Description
Technical field
The invention belongs to bioinformatics technique field, be specifically related to a kind of analytical approach for the treatment of different diseases with same method molecule mechanism, particularly a kind for the treatment of different diseases with same method molecule mechanism analytical approach based on protein reciprocation network.
Background technology
From ancient times to the present, " treating different diseases with same method " is used by traditional Chinese medical science doctor, and becomes a large characteristic of Chinese pharmaceutical therapeutics, and existing a large amount of clinical reports is card.
The implication of " treating different diseases with same method " refers to different diseases, if impel the interpretation of the cause, onset and process of an illness of morbidity identical, available same method treatment, namely card is ruled together same.But the intension of " treating different diseases with same method " again more than that, " card " of the traditional Chinese medical science is a kind of multisystem, Mutiple Targets, pathological change is comprehensive at many levels, Chinese medicine is act on Mutiple Targets to play drug effect too, need there has been sufficient understanding understanding to two aspects, find to support that the material base of this theory and molecular mechanisms of action just can make " treating different diseases with same method " theory better be used and develop.
At present, although have correlative study to analyze the similarities and differences between similar disorder abroad, reusing of drugs, does not also have the special research for treating different diseases with same method; Although have some domestic about the research for the treatment of different diseases with same method theory, its molecular mechanisms of action is not explained fully, and this will be an impediment to further research and development and this theoretical widespread use of related drugs.
Chinese medicine have developed multiple prescription in treating different diseases with same method, and confirmed definite curative effect.But Chinese medicinal formulae composition compound is complicated, and Chinese medicine passes through polycomponent, Mutiple Targets combined action realizes effect, and its molecular mechanisms of action in treating different diseases with same method process is not studied fully, and thus from molecular layer, in the face of the mechanism of action of this prescription, to carry out deep explaination very important.
At present, developed the interaction of multiple method for target molecules in drugs and human body, wherein, network pharmacology receives increasing concern as the developing direction that medicament research and development one is important.The method of Excavation Cluster Based on Network Analysis is widely used in the middle of the relevant research of medicine.Also establish individual about drug targets and the interactive database of protein simultaneously.
These methods and data are conducive to the mechanism of action explaining medicine from molecule aspect, but current not using in the research for the treatment of different diseases with same method is gone.Therefore, what how to utilize these to accumulate is a large amount of about medicine-target effect, and the interactive data of protein are problem demanding prompt solutions from the mechanism of action of the complicated Chinese medicine system of molecular layer surface analysis.
Summary of the invention
(1) technical matters that will solve
The technology of solution of the present invention asks that next week is the mechanism of action interactive for protein data come from the complicated medicine of molecular layer surface analysis.
(2) technical scheme
The present invention is directed to the molecule mechanism of Chinese medicine treating different diseases with same method, first build various disease protein reciprocation network separately; Then cluster is carried out according to the distribution situation of potential target on protein network of chemical composition in medicine of ruling together, cluster basis utilizes Apriori algorithm find target combination frequently, obtain finally by the frequent target obtained under comparative analysis various disease and characteristic in a network thereof the molecule mechanism that this medicine of ruling together realizes treating different diseases with same method.
Thus, the present invention proposes a kind for the treatment of different diseases with same method molecule mechanism analytical approach, the molecule mechanism for the treatment of different diseases with same method is realized for analyzing medicine of ruling together, described medicine of ruling together refers to the medicine simultaneously can treating multiple disease, comprises the steps: S1, builds at least two kinds of diseases protein reciprocation network separately; S2, according to described in the rule together chemical composition of medicine predict and the potential target of each compound in this medicine of ruling together retain the compound of answering target with the gene pairs of described disease association; S3, according to described in rule together the distribution in the protein reciprocation network of each disease of the potential target of chemical composition of medicine to medicine of ruling together in each compound carry out cluster; The frequent target combination occurred is determined in S4, each class in described cluster bunch; S5, the node corresponding to the target of the numerous appearance of protein reciprocation network intermediate frequency of described disease are analyzed, to obtain this medicine of ruling together to realize treating different diseases with same method molecule mechanism to described at least two kinds of diseases.
According to a kind of embodiment of the present invention, described step S2 comprises the screening step of the chemical composition to described medicine of ruling together further: if the gene-correlation of neither one and described disease in the potential target of described compound, then screened out, otherwise retained this compound.
According to a kind of embodiment of the present invention, the cluster in described step S3 carries out cluster analysis for the distance of target potential between compound on the protein reciprocation network of described disease association to compound.
According to a kind of embodiment of the present invention, being defined as follows of described distance:
Wherein distance
ijrepresent two compound i, the distance between j, G
i, G
jrepresent compound i respectively, the target set that j is corresponding, || represent the length of getting set, max (| G
j|, G
j|) represent set G
i, G
jin maximum length, m, n represent set G
i, G
jin target; d
mnrepresent the distance of two targets in protein reciprocation network, utilize shortest path to represent the distance of two nodes in protein reciprocation network.
According to a kind of embodiment of the present invention, described step S4 comprises: utilize Apriori algorithm to find target combination frequently, finds out the coefficient target combination of principal ingredient institute of this medicine of ruling together from molecule aspect.
According to a kind of embodiment of the present invention, the comparative analysis in described step S5 refers to the situation being subject to the node of this pharmaceutical intervention of ruling together in the protein reciprocation network by the disease of at least two types described in contrasting.
According to a kind of embodiment of the present invention, described step S5 comprises:
Analyze described step S4 obtain described in rule together the principal ingredient institute coefficient target combination of medicine and the effective object that described principal ingredient is different separately in described at least two kinds of diseases;
The characteristic of the neighbor node of target in described protein-protein interaction network that at least two kinds of diseases described in analysis are common analyzes the indirectly-acting of this medicine of ruling together;
In conjunction with the analysis of above-mentioned two aspects, analyze this molecule mechanism of medicine for described at least two kinds of diseases of ruling together from molecule aspect.
According to a kind of embodiment of the present invention, described in medicine of ruling together be Chinese medicinal formulae.
(3) beneficial effect
The present invention combines and utilizes data mining algorithm on the basis of protein-protein interaction network analytical approach, and to be ruled together the impact of medical compounds composition on the protein-protein interaction network of various disease by comparative analysis, from molecular layer in the face for the treatment of different diseases with same method, namely the identical treatment mechanism that various disease is passable makes an explanation and analyzes, and is particularly useful for the theoretical utilization in the clinical and combination of Chinese tradiational and Western medicine for the treatment of different diseases with same method and development.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the molecule mechanism analytical approach based on protein reciprocation network of the present invention;
Fig. 2 is that the brain heart based on protein reciprocation network of one embodiment of the present of invention is ruled together the process flow diagram of molecule mechanism analytical approach;
Fig. 3 is the protein reciprocation network figure relevant to coronary heart disease that embodiments of the invention obtain;
Fig. 4 is the protein reciprocation network figure relevant to apoplexy that embodiments of the invention obtain.
Embodiment
For making the object, technical solutions and advantages of the present invention clearly understand, below in conjunction with specific embodiment, and with reference to accompanying drawing, the present invention is described in further detail.
The present invention is from molecule aspect, in conjunction with utilizing the network analysis of protein reciprocation and data mining algorithm, carry out analyzing to explain the mechanism of action of medicine in treating different diseases with same method process of ruling together respectively on the protein reciprocation network of at least two kinds of disease associations, described in medicine of ruling together refer to the medicine of simultaneously treating various disease.The overall flow of method of the present invention is shown in Fig. 1.The present invention includes following several step:
Step S1: build at least two kinds of diseases protein reciprocation network separately.
In order to study the molecular mechanisms of action for the treatment of different diseases with same method, first needing to understand the respective related gene of disease and interaction thereof, building the protein reciprocation network with described disease association.In protein reciprocation network, the node of network represents a kind of protein, and internodal limit represents has reciprocation between two protein.
Step S2: the potential target predicting each compound in this medicine of ruling together according to the chemical composition of medicine of ruling together, retains the compound of answering target with the gene pairs of described disease association.
In view of the compound of analog structure often has identity function, therefore utilize the target of target as this compound of analog structure compound.
Step S3: according to the distribution in the protein reciprocation network of each disease of the potential target of the chemical composition of described medicine of ruling together to medicine of ruling together in each compound carry out cluster.
Step S4: determine the frequent target combination occurred in each class in described cluster bunch.
This step can utilize apriori algorithm to carry out Association Rule Analysis.
Step S5: the node corresponding to the target of the numerous appearance of protein reciprocation network intermediate frequency of each disease is analyzed, to obtain this medicine of ruling together to realize treating different diseases with same method molecule mechanism to described at least two kinds of diseases.
On the one hand according to the frequent target combination of each disease, find out main compound coefficient target combination at least two kinds of diseases of medicine of ruling together, and the effective object that these compounds are different separately at least two kinds of diseases; On the other hand, the characteristic by analyzing the topological property of the common gene of at least two kinds of diseases in various disease network and neighbor node thereof analyzes the effect of this medicine of ruling together further.In conjunction with the analysis of two aspects, thus explain the mechanism of action for the treatment of different diseases with same method from molecule aspect.
Under with reference to accompanying drawing 2 further illustrate technical scheme of the present invention by embodiment.
Step S1: the protein reciprocation network building at least two kinds of diseases.
In this embodiment, we determine two kinds of representational cardiovascular and cerebrovascular diseases as shown in Figure 2: apoplexy and coronary heart disease.In order to study the molecular mechanisms of action for the treatment of different diseases with same method, first need the respective related gene of understanding two kinds of diseases and interaction thereof.This embodiment finds relevant disease gene for coronary heart disease and apoplexy respectively in omim database, wherein coronary heart disease: 131 genes, apoplexy: 165 genes.By gene shine in the protein reciprocation network of GeneMania.Wherein, the node of network represents a kind of protein, and internodal limit represents has reciprocation between two protein.The protein reciprocation network finally obtaining coronary heart disease relevant is shown in Fig. 3, and the protein reciprocation network that apoplexy is relevant is shown in Fig. 4.
In this embodiment, we analyze Chinese medicinal formulae " step-length cerebral ischemic ".First, the chemical composition collecting every taste Chinese medicine in step-length cerebral ischemic prescription is needed: traditional Chinese medicine ingredients can come from Chinese medicine innovation net (http://www.tcm120.com/tcm/q_tcd.asp).Compound structure data come from PubChem database.
Step S2: the potential target predicting each compound in this medicine of ruling together according to the chemical composition of medicine of ruling together, retains the compound of answering target with the gene pairs of described disease association.
The compound target forecast function that the present invention utilizes MetaDrug software to provide, be input as the two-dimensional structure file of compound, the two-dimensional structure according to each compound finds analogue compounds, and using the target of analogue compounds as the potential target of this compound.Described method for screening compound refers to and to screen according to the potential target set of each compound, if the gene-correlation of neither one and disease in the potential target of a compound, then thinks that this compound is invalid for this disease, is screened out; Otherwise retain this compound, namely only retain the compound that those contain the corresponding target of disease related gene.After screening, 68 kinds of compounds are remained for coronary heart disease; 64 kinds of compounds are remained for apoplexy.
Step S3: the distribution each compound to rule together medicine of potential target in the protein reciprocation network of each disease according to the chemical composition of described medicine of ruling together carries out cluster.
For the distance of target potential between compound on the protein reciprocation network of disease association, cluster analysis is carried out to compound.Here the distance of two compounds refers to that two targets that two compounds are corresponding are integrated into the distance on protein reciprocation network, is defined as follows:
Wherein distance
ijrepresent two compound i, the distance between j, G
i, G
jrepresent compound i respectively, the target set that j is corresponding, || represent the length of getting set, max (| G
i|, | G
j|) represent set G
i, G
jin maximum length, m, n represent set G
i, G
jin target; d
mnrepresent the distance of two targets in protein reciprocation network, utilize shortest path to represent the distance of two nodes in protein reciprocation network.Utilize the distance value between this formulae discovery compound, utilize hierarchical clustering algorithm to carry out cluster analysis according to the distance between compound.
Cluster result under coronary heart disease condition is as table 1, and the cluster result under apoplexy condition is in table 2.Wherein, a larger class bunch corresponding compound is the compound that this drug main is wanted, and the target of its correspondence also embodies main function.
The compound cluster result that the protein network that table 1 is correlated with based on coronary heart disease obtains
The compound cluster result that the protein network that table 2 is correlated with based on apoplexy obtains
Step S4: determine the frequent target combination occurred in each class in described cluster bunch.
After cluster, the compound within each class of cluster bunch has higher similarity in potential target, and compound in inhomogeneity bunch often in potential target difference comparatively large, have different functions; Namely each class bunch also correspond to a kind of function type; The more class bunch of inclusion compound then illustrates the large percentage that the compound of this kind of function in this medicine accounts for, and so the major function of this medicine corresponds to the function of compound in larger class bunch.The set of the corresponding potential target of each compound in class bunch, the present invention using corresponding for each compound potential target set as a record, the target combination of described frequent appearance analyzes the potential target of compound in each class bunch, apriori algorithm is utilized to find target combination frequently, maximum kind bunch corresponding frequent target combination is the target set of the multiple principal ingredient effects in prescription, corresponding to the target embodying this prescription major function, the coefficient target combination of principal ingredient institute of prescription is found out from molecule aspect, it is exactly the coefficient target set of multiple main compound in " step-length cerebral ischemic " prescription.Like this, both have found the compound combination playing major function medicine from molecule aspect, and also determined this compound of ruling together in medicine and frequently act on which target in human body.The results are shown in Table 3,4.
Table 3 is for the frequent target combination of table 1 cluster result
Table 4 is for the frequent target combination of table 2 cluster result
Step S5: the node corresponding to the target of the numerous appearance of protein reciprocation network intermediate frequency of each disease is analyzed, to obtain this medicine of ruling together to realize treating different diseases with same method molecule mechanism to described at least two kinds of diseases.
This embodiment for the analysis that coronary heart disease and apoplexy are carried out as above, finally contrasts the result under two kinds of diseases respectively.On the one hand according to the frequent assortment of genes obtained under each disease, find out the coefficient target combination in two kinds of diseases of " step-length cerebral ischemic " main compound, and the effective object that these compounds are different separately in two kinds of diseases; On the other hand, the characteristic by analyzing the common neighbor node of gene in various disease network of two kinds of diseases analyzes the indirectly-acting of the party further.In conjunction with the analysis of two aspects, thus explain the material base that " step-length cerebral ischemic " square brain heart is ruled together and the mechanism of action from molecule aspect.
The adjacent node of the node that in the protein network of comparative analysis two kinds of disease associations, Chinese medicine main compound is applied to and these nodes: find that the main compound of " step-length cerebral ischemic " acts on LDLR for coronary heart disease or apoplexy all simultaneously, APOA1, APOE, APOB, these 5 targets of LPL, main and the lipid of these targets, the metabolism of lipoprotein and mediation lipid, the path of transport digestion is correlated with; And these 5 targets belong to the product of omim database atherosclerosis related gene, also accord with relevant result of study.This 5 targets are analyzed from network, calculate and find that its degree average in two networks (being 6 in the coronary heart disease and apoplexy network of path association) is all obviously greater than the average degree (in coronary heart disease and apoplexy network, the average degree of all nodes is 3) of whole network, these 5 targets visible occupy relative consequence in a network, and can find out that these five targets all compare in a corresponding network to close on, and be arranged in the sub-network connecting relative close.Meanwhile, while frequently acting on two kinds of common associated target of disease, the main compound of this prescription is directed to different diseases and also frequently acts on each autocorrelative target, the main compound of such as this prescription also frequently acts on the relevant HGPS of coronary heart disease, CETP, PON1, CD36, CTNNB1, AR target, frequently acts on the NOS1 relevant with apoplexy, NOS2A simultaneously, ITGA2, APP target.This prescription visible, while acting on the common target of two kinds of various disease, can also affect two kinds of each autocorrelative targets of disease respectively, thus achieves the brain heart and rule together.
In addition in order to contrast the relation between the result that obtains in two kinds of disease association networks, the present invention has added up LDLR, APOA1, the degree of the neighbor node of these 5 targets of APOE, APOB, LPL in Fig. 2 and Fig. 3 also carries out rank: the neighbor node of the rank front three obtained according to Fig. 1 is PPARG, ESR1, USF1, these targets all and ALK1, bmp receptor, Arf6, ErbB acceptor, the signal transmission path that c-Met, VEGFR etc. are relevant is correlated with; The neighbor node of the rank front three obtained according to Fig. 2 is APOA4, APOC3, A2M, and these relevant biological pathways all relate to the metabolism of lipid and lipoprotein, transport, and digestion, its function class is similar to 5 targets above.When treating cardiovascular and cerebrovascular disease as can be seen from this result " step-length cerebral ischemic ", different paths can also be indirectly intervened while acting on the common target of two kinds of diseases, thus have different impacts to different morbid states, reach the object of simultaneously treating various disease.
Although be described with the rule together analysis of medicine of the brain heart to the explanation of embodiments of the invention above, the present invention is not limited to this, and the present invention is applicable equally for the treating different diseases with same method molecule mechanism analysis of other medicines of ruling together.
Above-described specific embodiment; object of the present invention, technical scheme and beneficial effect are further described; be understood that; the foregoing is only specific embodiments of the invention; be not limited to the present invention; within the spirit and principles in the present invention all, any amendment made, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (4)
1. a treating different diseases with same method molecule mechanism analytical approach, realizes the molecule mechanism for the treatment of different diseases with same method for analyzing medicine of ruling together, described in medicine of ruling together refer to the medicine simultaneously can treating multiple disease, it is characterized in that, comprise the steps:
S1, structure at least two kinds of diseases protein reciprocation network separately;
S2, according to described in the rule together chemical composition of medicine predict and the potential target of each compound in this medicine of ruling together retain the compound of answering target with the gene pairs of described disease association;
S3, according to described in rule together the distribution in the protein reciprocation network of each disease of the potential target of chemical composition of medicine to medicine of ruling together in each compound carry out cluster, this cluster carries out cluster analysis to compound, being defined as follows of described distance for the distance of target potential between compound on the protein reciprocation network of described disease association:
Wherein distance
ijrepresent two compound i, the distance between j, G
i, G
jrepresent compound i respectively, the target set that j is corresponding, || represent the length of getting set, max (| G
i|, | G
j|) represent set G
i, G
jin maximum length, m, n represent set G
i, G
jin target; d
mnrepresent the distance of two targets in protein reciprocation network, utilize shortest path to represent the distance of two nodes in protein reciprocation network;
The frequent target combination occurred is determined in S4, each class in described cluster bunch;
S5, the node corresponding to the target of the numerous appearance of protein reciprocation network intermediate frequency of described disease are analyzed, to obtain this medicine of ruling together to realize treating different diseases with same method molecule mechanism to described at least two kinds of diseases, described comparative analysis refers to the situation being subject to the node of this pharmaceutical intervention of ruling together in the protein reciprocation network by the disease of at least two types described in contrasting;
Described step S5 comprises:
Analyze described step S4 obtain described in rule together the principal ingredient institute coefficient target combination of medicine and the effective object that described principal ingredient is different separately in described at least two kinds of diseases;
The characteristic of the neighbor node of target in described protein-protein interaction network that at least two kinds of diseases described in analysis are common analyzes the indirectly-acting of this medicine of ruling together;
In conjunction with the analysis of above-mentioned two aspects, analyze this molecule mechanism of medicine for described at least two kinds of diseases of ruling together from molecule aspect.
2. treating different diseases with same method molecule mechanism analytical approach as claimed in claim 1, it is characterized in that, described step S2 comprises the screening step of the chemical composition to described medicine of ruling together further: if the gene-correlation of neither one and described disease in the potential target of described compound, then screened out, otherwise retained this compound.
3. treating different diseases with same method molecule mechanism analytical approach as claimed in claim 1, it is characterized in that, described step S4 comprises: utilize Apriori algorithm to find target combination frequently, finds out the coefficient target combination of principal ingredient institute of this medicine of ruling together from molecule aspect.
4. the treating different diseases with same method molecule mechanism analytical approach according to any one of claim 1-3, is characterized in that, described in medicine of ruling together be Chinese medicinal formulae.
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| CN110289049B (en) * | 2019-06-19 | 2021-06-25 | 江南大学 | Method for analyzing heat resistance relation between communication path and lipase |
| CN112309505B (en) * | 2020-11-05 | 2021-08-17 | 湖南大学 | Anti-neocoronal inflammation drug discovery method based on network characterization |
| CN115458061B (en) * | 2022-10-13 | 2024-01-23 | 南开大学 | Medicine-protein interaction prediction method and system |
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