CN115116561B - Application of drug-target protein-schizophrenia interaction network - Google Patents
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Abstract
The invention belongs to the technical field of biomedicine, and discloses application of a drug-target protein-schizophrenia interaction network. The invention uses multidimensional interaction group to screen out new drugs which can be used for relieving or even treating the schizophrenia by constructing a drug-target protein-disease interaction network and collecting candidate genes of the schizophrenia. The construction method of the drug-target protein-schizophrenia interaction network provides a basis for the relocation of the schizophrenia related preventive or therapeutic drugs, and the constructed interaction network detects the new clinical application of the existing drugs. The medicine development process can be quickened, and a great deal of manpower and financial resources are saved.
Description
Technical Field
The invention relates to the technical field of biomedicine, in particular to application of a drug-target protein-schizophrenia interaction network.
Background
Schizophrenia is a serious mental disorder with a lifetime prevalence of about 0.4% worldwide. It can have destructive effects on patients and their caregivers and can bring significant costs to the healthcare system. Schizophrenia is a heterogeneous disease with positive symptoms (delusions, hallucinations, thought disorder); negative symptoms (lack of pleasure, mental depression, social withdrawal, poor mind) and cognitive dysfunction. As the understanding and clinical study of schizophrenia continue to be in progress, schizophrenia is also gradually classified into different types, such as early-onset and late-onset schizophrenia according to the age of onset of schizophrenia, and into defective and non-defective schizophrenia according to the dimensions of signs and symptoms, disease course, pathophysiological relevance, risk and etiologic factors, and therapeutic response.
The etiology of schizophrenia is still poorly understood, and in the last few years, many different antipsychotics have been developed and tested for their effectiveness and safety in alleviating the positive symptoms of schizophrenia and maintaining stability. Although there are a variety of antipsychotics available for alleviating the symptoms of schizophrenia, the response rates to these drugs are lower than expected, they act slowly, and often produce serious adverse side effects.
Current antipsychotic therapies rely primarily on targeting the brain dopamine D2 receptor, but new drugs are being developed that act through glutamate receptors, glycine transporter or the alpha-7-nicotinic acetylcholine receptor. However, none of these new approaches has brought therapeutic breakthrough to date. Although antipsychotics have an undisputed efficacy in treating positive symptoms of schizophrenia, for most patients, the drugs are ineffective against all symptoms including negative and cognitive symptoms, and serious side effects persist. Although new drugs subsequently developed can alleviate the occurrence of side effects of exercise, other safety and tolerability problems arise. Subsequent progress has been insignificant since the advent of initial antipsychotic therapy in the 1950 s. While there is still a lack of screening drugs for treatment for different symptoms and disease patterns of different types of schizophrenia, pathophysiological heterogeneity in various areas of schizophrenia requires multiple treatment methods, so finding effective drugs for different types is one of the most important research problems in the field of schizophrenia.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide application of a drug-target protein-schizophrenia interaction network.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
the invention applies the drug-target protein-schizophrenia interaction network in screening drugs for preventing or treating schizophrenia.
As a preferred embodiment of the application of the invention, weight and restarting probability are given according to the node type in the drug-target protein-schizophrenia interaction network, random walk is restarted from the disease and drug nodes, and the drug and disease diffusion curve is calculated by calculating the influence condition of the drug and the disease on the nodes in the multidimensional interaction group through the frequency of the walk nodes; and respectively calculating the diffusion curves of the medicine and the disease and the diffusion curve SIM of the diseases related to the schizophrenia, comparing through the SIM, respectively calculating the Euclidean distance between every two of the diffusion curves, and sequencing the predicted medicine of the given schizophrenia through the distance.
The invention provides a method for constructing a drug-target protein-schizophrenia interaction network, which comprises the following steps:
(1) Collecting the interaction relation of the medicine and the target protein through a medicine database, and screening out human targets and medicines meeting FDA standards;
(2) Mapping the disease to the gene related to the schizophrenia through a disease database, and integrating the disease-pathogenic gene correlation;
(3) And integrating the drug-target protein interaction relationship and the disease-pathogenic gene interaction relationship by using Python to construct a drug-protein-schizophrenia interaction network.
The drug-protein-schizophrenia interaction network of the present invention provides a general way to systematically learn how drugs treat diseases, systematically identify treatment-related proteins, predict which schizophrenia-related genes will alter the efficacy of drugs or cause serious adverse effects of drug treatment, and the multidimensional interaction set can be easily extended to add other node types associated with diseases.
The drug-target protein-schizophrenia interaction network provided by the invention can be used for finding out drugs affecting corresponding targets according to the difference table genes of the drug-target protein-schizophrenia interaction network starting from different expression modes of different schizophrenia types, so that the drug-target protein-schizophrenia interaction network has a therapeutic effect on different schizophrenia types.
As a preferred embodiment of the method for constructing a drug-target protein-schizophrenia interaction network according to the present invention, in the step (2), the schizophrenia candidate genes are collected and defective schizophrenia differential genes and premature schizophrenia differential genes are obtained by sequencing; the candidate gene, the defective schizophrenia differential gene and the premature schizophrenia differential gene are pathogenic genes; the pathogenic genes are mapped on a human protein interaction network through Cytoscape and R, and the interaction relation of the schizophrenia-pathogenic genes is screened.
As a preferred embodiment of the method for constructing a drug-target protein-schizophrenia interaction network according to the present invention, the schizophrenia candidate genes include ABL2, aloa, ARHGAP1, ABR, SLC25A6, ARNT, ACACA, APAF1, STS, ACVR2A, APBA2, ASCL1, ADRA1A, BIRC3, SERPINC1, JAG1, APOE, RERE, AGT, FAS, ATP A2, AK4, AQP6, ATP2B4, AKT1, AR, ATRX, ALDH1A1, ARL4D, and KIF1A; the defective schizophrenia differential gene comprises ABR, ALAD, ARHGAP, ACLY, ALAS1, ARNT, ACO2, ABCD1, ARRB1, ACTG1, ALDH1A1, GET3, ACTN4, ALDH3B1, ATIC, ACVR1B, ALOX15B, ATOX1, ACVR2B, APLP2, TNFRSF17, ADCY7, APP, ZFP36L1, AP2A1, APRT, ZFP36L2, AKT1, ARF3, ARHGAP1; the differential gene of the premature schizophrenia comprises ABCF1, AQP3, POLR3D, ACVR A6, ARHGAPS, BNIP1, PLIN2, ARHGDIA, KLF9, ADORA2A, ARHGDIB, C3AR1, PARP1, ATF3, TMEM258, AGER, ATP5F1D, CFAP410, AHR, ATPSF1E, CBFA2T3, ALDOA, ATP6V1A, SLC A6, ATP6V1C1, CCNE1, FAS, BMI1 and CCNH. As a preferred embodiment of the application of the invention, the node type is given a weight w= { 'indication':3.541889556309463, 'protein':4.396695660380823, 'drug':3.2071696595616364}, probability of a pedestrian to continue walking instead of restarting at a given step α= 0.8595436247434408.
As a preferred embodiment of the application according to the invention, the drug and disease spread profile and the schizophrenia related disease spread profile SIM are calculated by the L2 norm, respectively.
The diffusion profile of the present invention provides predictive power and interpretability in drug-disease therapy modeling, and allows the determination of proteins associated with the treatment of schizophrenia.
As a preferred embodiment of the use according to the invention, the medicament for the treatment of schizophrenia comprises Rilonacept, tetrabenazine, lsometheptene, zuclopenthixol, droperidol, acetophenazine, lloperidone, dopamine, ketanserin, enzastaurin, vilazodone, epicriptine, dihydrexidine, flupentixol, taurine, benzphetamine, piceatannol, citalopram, butabarbital and Cinnarizine.
As a preferred embodiment of the use according to the invention, the drugs for the treatment of premature schizophrenia include Veliparib, talazoparib, niraparib, fingolimod, E-2012, rucaparib, olaparib, mexiletine, nadroparin, aldesleukin, denileukin diftitox, asparagine, vinblastine, auranofin, rivanicline, mesalazine, dupilumab, aspirin, muromonab and Ribavirin.
As a preferred embodiment of the use according to the invention, said drugs for the treatment of defective schizophrenia include Tasonerm, A-675563, castanospermine, belantamab mafodotin, bexarotene, lpilimumab, thyrotropin alfa, reversine, puromycin, anisomycin, botulinum toxin type A, glyconic acid, pazopanib, aminolevulinic acid, alfacalcidol, dimethyl fumarate, pexidartinib, wortmannin, bezafibrate and Cediranib.
Compared with the prior art, the invention has the beneficial effects that:
the invention uses multidimensional interaction group to screen out new drugs which can be used for relieving or even treating the schizophrenia by constructing a drug-target protein-disease interaction network and collecting candidate genes of the schizophrenia. The construction method of the drug-target protein-schizophrenia interaction network provides a basis for the relocation of the schizophrenia related preventive or therapeutic drugs, and the constructed interaction network detects the new clinical application of the existing drugs. The medicine development process can be quickened, and a great deal of manpower and financial resources are saved.
Drawings
FIG. 1 is a flow chart of the construction of a drug-target protein-disease interaction network;
FIG. 2 is a diagram of a drug-protein-disease interaction network;
fig. 3 is a schematic diagram of drug and disease spread curves versus disease spread curves SIM.
Detailed Description
Protein interactions play an important role in the cellular molecular signaling pathway network, and the molecular mechanisms of disease are studied through the protein interaction network of pathogenic genes, and from the perspective of systemic biology, disease risk genes for schizophrenia may act on a common molecular network, which may involve multiple signaling pathways to perform the relevant cellular functions, and it is important to understand the pathogenic mechanisms of schizophrenia through the schizophrenia network and to find therapeutic drugs. However, with the increasing awareness of pharmacology, the "multi-target, multi-drug" mode has been widely accepted as a replacement for "one target, one drug". Drugs typically target multiple proteins, rather than just one. Furthermore, in addition to the primary therapeutic target, drugs may also interact with other proteins, i.e. off-target effects. And the causative gene of a disease is usually more than one, but includes a small number of major genes and many minor genes.
Therefore, identification of Drug-target interactions (DTI) is an important prerequisite for the relevant fields of pharmacology, drug repositioning, drug discovery, side effect prediction, drug resistance, etc.
For a better description of the objects, technical solutions and advantages of the present invention, the present invention will be further described with reference to the following specific examples. It will be appreciated by persons skilled in the art that the specific embodiments described herein are for purposes of illustration only and are not intended to be limiting.
The test methods used in the examples are conventional methods unless otherwise specified; the materials, reagents and the like used, unless otherwise specified, are all commercially available.
Example 1: construction method of drug-target protein-disease interaction network
Schizophrenia is a complex multifactorial disease, it seems unlikely that all symptoms of the disease would be treated with a single target drug, and more desirable treatment would be to find different drugs and combinations of drugs for different types based on different expression patterns for different types of schizophrenia. The cost of time, money, resources, etc. for developing new drugs is enormous. New therapeutic effects and uses of existing or abandoned drugs on diseases, namely drug repositioning, are discovered by using known interaction data and unpaired small molecule compounds stored in various databases. The flow is shown in fig. 1.
The method comprises the following specific steps:
(1) Data collection
The drug-target protein interaction relationship is collected through a drug database (drug bank, drug Repurposing Hub), and human targets and drugs (4,622 nodes, 11,959 sides) meeting the FDA standard, including 2,268 drugs and 2,354 target proteins, are screened out.
Diseases are mapped to genes affected by the diseases through Cytoscape by effects such as genome change, expression change or post-translational modification of a disease database (DisGeNet), and disease-pathogenic gene correlations (27,092 nodes, 673,412 sides) including 21,878 diseases and 5,214 pathogenic genes are integrated.
(2) Multidimensional interaction set architecture
Three interactions were integrated using Python to construct a drug-protein-disease interaction network, as shown in figure 2.
(3) Calculation of drug and disease spread curves
By using a re-start random walk to propagate the effects of each drug and disease in the multidimensional interaction group, the drug or disease spread profile knows the proteins most affected by each drug or disease. Each drug or disease spread curve is calculated by a biased random walk from the drug or disease node. At each step, the random walker may restart its walk or jump to the neighboring node according to the optimized edge weights. After multiple walks, the diffusion profile measures the frequency of access to each node, representing the effect of the drug or disease on that node.
The weight w= { W is given by different types of nodes drug ,w protein ,w indication A relative likelihood of jumping from one node type to another. Alpha represents the probability that a pedestrian will continue walking at a given step rather than restarting.
First, the probability of walker to jump to a different type of node is calculated. And secondly, calculating the probability of the walker to jump to different nodes of the same type. Finally, the diffusion distribution is calculated through power iteration.
(4) Drug prediction
For a drug to treat a disease, it must affect proteins similar to those destroyed by the disease and to those with biological functions. The diffusion profile of drugs and diseases encodes the effects of drugs and diseases on proteins.
Comparing the diffusion profile of a drug and a disease predicts which drugs can treat a given disease. For each drug, its profile of spread with disease SIM (similarity) was calculated separately by L2 norm, and the drugs most likely to treat the disease were ranked together as shown in fig. 3.
Example 2: construction method of drug-target protein-schizophrenia interaction network
(1) Data collection
The drug-target protein interaction relationship is collected through a drug database (drug bank, drug Repurposing Hub), and human targets and drugs (4,622 nodes, 11,959 sides) meeting the FDA standard, including 2,268 drugs and 2,354 target proteins, are screened out.
Diseases are mapped to genes affected by the diseases through Cytoscape by effects such as genome change, expression change or post-translational modification of a disease database (DisGeNet), and disease-pathogenic gene correlations (27,092 nodes, 673,412 sides) including 21,878 diseases and 5,214 pathogenic genes are integrated.
1,720 candidate genes for schizophrenia were collected and mapped to the human protein interaction network (18,276 nodes, 817,086 sides) by Cytoscape and R, from which interaction subnetworks of pathogenic genes for schizophrenia (1,501 nodes, 9,084 sides) were screened. And obtaining defective and premature schizophrenia differential genes through sequencing.
The first 30 candidate pathogenic genes for schizophrenia (n=1501) are shown in table 1:
TABLE 1 pathogenic genes selected for schizophrenia
The first 30 differential expression genes of early-onset schizophrenia (n=1206) are shown in table 2:
TABLE 2 differential expression Gene for early schizophrenia
The first 30 defective schizophrenia differentially expressed genes (n=1161) are shown in table 3:
table 3 defective schizophrenia differential expression genes
(2) Multidimensional interaction set architecture
Three interactions were integrated using Python to construct a drug-protein-schizophrenia interaction network. In order to find out medicines for treating different types of schizophrenia, schizophrenia and candidate genes thereof are added into diseases and pathogenic genes in the process of constructing a multidimensional interaction group, and the interaction relationship between different types of schizophrenia and different genes thereof is improved.
(3) Calculation of drug and disease spread curves
And (3) according to the node type, giving weight and restarting probability, restarting random walk from the disease and medicine nodes, and calculating the influence condition of the medicine and the disease on the nodes in the multidimensional interaction group through the frequency of the walk nodes.
The weight w= { 'indication }' 3.541889556309463, 'protein:' 4.396695660380823, 'drug:' 3.2071696595616364}, α= 0.8595436247434408 is given by different types of nodes.
First, the probability of walker to jump to a different type of node is calculated. And secondly, calculating the probability of the walker to jump to different nodes of the same type. Finally, the diffusion distribution is calculated through power iteration.
(4) Drug prediction
And respectively calculating the diffusion curve of the medicine and the disease and the diffusion curve SIM (similarity) of the diseases related to the schizophrenia through L2 norms, respectively calculating the Euclidean distance between every two medicines and the diffusion curve SIM of the medicine and the disease, respectively predicting and sequencing the medicines for each given disease through the distance, and screening out the medicines with the rank of 20.
The integrated analysis of various schizophrenia prediction drugs shows that the closer drugs are associated with more schizophrenia types and protein regulation mechanisms of related diseases, are more likely to be used for treating schizophrenia, and the predicted drugs for relieving or even treating the schizophrenia are obtained by sequencing and annotating the drugs through calculated Euclidean distance.
The first 20 drugs predicted to treat schizophrenia by the multiscale action group, including drug ID, name, and treatment disease in drug bank, are shown in table 4:
table 4 predicted first 20 drugs for treatment of schizophrenia
Further, the protein interaction relation net is replaced by an interaction net between different expression genes of different types of schizophrenia, and medicine prediction is carried out on the different types of schizophrenia. The results were as follows:
the first 20 drugs predicted to treat early-onset schizophrenia in the multiscale-acting group, including drug ID, name, and treatment disease in drug bank, are shown in table 5:
table 5 predicts the first 20 drugs for the treatment of early-onset schizophrenia
The first 20 drugs predicted by the multiscale action group to treat defective schizophrenia, including drug ID, name, and treatment disease in drug bank, are shown in table 6:
table 6 predicts the first 20 drugs for treatment of defective schizophrenia
Some of the predicted drugs are drugs already used for treating schizophrenia, demonstrating the feasibility of the method for constructing drug-target protein-schizophrenia interaction network.
The multi-dimensional interaction set of the present invention provides a general way to systematically learn how drugs treat diseases, systematically identify treatment-related proteins, predict which genes will alter the efficacy of a drug or cause serious adverse effects of a drug treatment, and can be easily expanded to add other node types associated with a disease. Diffusion curves provide predictive power and interpretability in drug-disease therapy modeling, and the proteins associated with treating a given disease can be determined.
The drug-target protein-schizophrenia interaction network provided by the invention can be used for finding out drugs affecting corresponding targets according to the difference table genes of the drug-target protein-schizophrenia interaction network starting from different expression modes of different schizophrenia types, so that the drug-target protein-schizophrenia interaction network has a therapeutic effect on different schizophrenia types.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the scope of the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted equally without departing from the spirit and scope of the technical solution of the present invention.
Claims (6)
1. An application method of a drug-target protein-schizophrenia interaction network in screening drugs for preventing or treating schizophrenia is characterized in that weights and restarting probabilities are given according to node types in the drug-target protein-schizophrenia interaction network, random walk is restarted from disease and drug nodes, and drug and disease diffusion curves are calculated according to the frequency of the walk nodes to calculate the influence condition of drugs and diseases on the nodes in a multidimensional interaction group; calculating diffusion curves of the medicines and the diseases and a diffusion curve SIM of the diseases related to the schizophrenia respectively, comparing the diffusion curves with the SIM, calculating Euclidean distances between every two of the diffusion curves, and sequencing predicted medicines of the given schizophrenia according to the distances;
the construction method of the drug-target protein-schizophrenia interaction network comprises the following steps:
(1) Collecting the interaction relation of the medicine and the target protein through a medicine database, and screening out human targets and medicines meeting FDA standards;
(2) Mapping the disease to the gene related to the schizophrenia through a disease database, and integrating the disease-pathogenic gene correlation;
(3) Integrating the drug-target protein interaction relationship and the disease-pathogenic gene interaction relationship by using Python to construct a drug-protein-schizophrenia interaction network;
in the step (2), collecting the schizophrenia candidate genes, and obtaining defective schizophrenia differential genes and premature schizophrenia differential genes by sequencing; the candidate gene, the defective schizophrenia differential gene and the premature schizophrenia differential gene are pathogenic genes; mapping the pathogenic genes on a human protein interaction network through Cytoscape and R, and screening out the interaction relation between schizophrenia and pathogenic genes;
the schizophrenia candidate genes include ABL2, aloa, ARHGAP1, ABR, SLC25A6, ARNT, ACACA, APAF1, STS, ACVR2A, APBA2, ASCL1, ADRA1A, BIRC3, SERPINC1, JAG1, APOE, RERE, AGT, FAS, ATP A2, AK4, AQP6, ATP2B4, AKT1, AR, ATRX, ALDH A1, ARL4D, and KIF1A; the defective schizophrenia differential gene comprises ABR, ALAD, ARHGAP, ACLY, ALAS1, ARNT, ACO2, ABCD1, ARRB1, ACTG1, ALDH1A1, GET3, ACTN4, ALDH3B1, ATIC, ACVR1B, ALOX15B, ATOX1, ACVR2B, APLP2, TNFRSF17, ADCY7, APP, ZFP36L1, AP2A1, APRT, ZFP36L2, AKT1, ARF3, ARHGAP1; the differential gene of the premature schizophrenia comprises ABCF1, AQP3, POLR3D, ACVR A6, ARHGAPS, BNIP1, PLIN2, ARHGDIA, KLF9, ADORA2A, ARHGDIB, C3AR1, PARP1, ATF3, TMEM258, AGER, ATP5F1D, CFAP410, AHR, ATPSF1E, CBFA2T3, ALDOA, ATP6V1A, SLC A6, ATP6V1C1, CCNE1, FAS, BMI1 and CCNH.
2. The application method according to claim 1, wherein the node type is given a weight w= { 'indication':3.541889556309463, 'protein':4.396695660380823, 'drug':3.2071696595616364}, probability of a pedestrian to continue walking instead of restarting at a given step α = 0.8595436247434408.
3. The method of claim 1, wherein the drug and disease spread profile and the schizophrenia-related disease spread profile SIM are calculated by L2 norms, respectively.
4. The method of use according to claim 1, wherein said drugs for the treatment of schizophrenia comprise Rilonacept, tetrabenazine, lsometheptene, zuclopenthixol, droperidol, acetophenazine, lloperidone, dopamine, ketanserin, enzastaurin, vilazodone, epicriptine, dihydrexidine, flupentixol, taurine, benzphetamine, piceatannol, citalopram, butabarbital and Cinnarizine.
5. The method of use according to claim 1, wherein said drugs for the treatment of premature schizophrenia comprise Veliparib, talazoparib, niraparib, fingolimod, E-2012, rucaparib, olaparib, mexiletine, nadroparin, aldesleukin, denileukin diftitox, asparagine, vinblastine, auranofin, rivanicline, mesalazine, dupilumab, aspirin, muromonab and Ribavirin.
6. The method of use according to claim 1, wherein the drug for treating defective schizophrenia comprises Tasonermin, a-675563, castanospermine, belantamab mafodotin, bexarotene, lpilimumab, thyrotropin alfa, reversine, puromycin, anisomycin, botulinum toxin type A, glyconic acid, pazopanib, aminolevulinic acid, alfacalcidol, dimethyl fumarate, pexidartinib, wortmannin, bezafibrate and celiranib.
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