Kannan Sridharan, Thirumal Kumar D, Suchetha Manikandan, Gaurav Prasanna, Lalitha Guruswamy, Rashed Al Banna, George Priya Doss C
{"title":"CYP2C9突变的计算结构验证和机器学习算法在预测华法林治疗结果中的评估。","authors":"Kannan Sridharan, Thirumal Kumar D, Suchetha Manikandan, Gaurav Prasanna, Lalitha Guruswamy, Rashed Al Banna, George Priya Doss C","doi":"10.2174/1389200224666230705124329","DOIUrl":null,"url":null,"abstract":"<p><strong>Aim: </strong>The study aimed to identify the key pharmacogenetic variable influencing the therapeutic outcomes of warfarin using machine learning algorithms and bioinformatics tools.</p><p><strong>Background: </strong>Warfarin, a commonly used anticoagulant drug, is influenced by cytochrome P450 (CYP) enzymes, particularly <i>CYP2C9</i>. MLAs have been identified to have great potential in personalized therapy.</p><p><strong>Objective: </strong>The purpose of the study was to evaluate MLAs in predicting the critical outcomes of warfarin therapy and validate the key predictor genotyping variable using bioinformatics tools.</p><p><strong>Methods: </strong>An observational study was conducted on adults receiving warfarin. Allele discrimination method was used for estimating the single nucleotide polymorphisms (SNPs) in <i>CYP2C9</i>, VKORC1, and CYP4F2. MLAs were used for identifying the significant genetic and clinical variables in predicting the poor anticoagulation status (ACS) and stable warfarin dose. Advanced computational methods (SNPs' deleteriousness and impact on protein destabilization, molecular dockings, and 200 ns molecular dynamics simulations) were employed for examining the influence of <i>CYP2C9</i> SNPs on structure and function.</p><p><strong>Results: </strong>Machine learning algorithms revealed <i>CYP2C9</i> to be the most important predictor for both outcomes compared to the classical methods. Computational validation confirmed the altered structural activity, stability, and impaired functions of protein products of <i>CYP2C9</i> SNPs. Molecular docking and dynamics simulations revealed significant conformational changes with mutations R144C and I359L in <i>CYP2C9</i>.</p><p><strong>Conclusion: </strong>We evaluated various MLAs in predicting the critical outcome measures associated with warfarin and observed <i>CYP2C9</i> as the most critical predictor variable. The results of our study provide insight into the molecular basis of warfarin and the <i>CYP2C9</i> gene. A prospective study validating the MLAs is urgently needed.</p>","PeriodicalId":10770,"journal":{"name":"Current drug metabolism","volume":" ","pages":"466-476"},"PeriodicalIF":2.1000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computational Structural Validation of <i>CYP2C9</i> Mutations and Evaluation of Machine Learning Algorithms in Predicting the Therapeutic Outcomes of Warfarin.\",\"authors\":\"Kannan Sridharan, Thirumal Kumar D, Suchetha Manikandan, Gaurav Prasanna, Lalitha Guruswamy, Rashed Al Banna, George Priya Doss C\",\"doi\":\"10.2174/1389200224666230705124329\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aim: </strong>The study aimed to identify the key pharmacogenetic variable influencing the therapeutic outcomes of warfarin using machine learning algorithms and bioinformatics tools.</p><p><strong>Background: </strong>Warfarin, a commonly used anticoagulant drug, is influenced by cytochrome P450 (CYP) enzymes, particularly <i>CYP2C9</i>. MLAs have been identified to have great potential in personalized therapy.</p><p><strong>Objective: </strong>The purpose of the study was to evaluate MLAs in predicting the critical outcomes of warfarin therapy and validate the key predictor genotyping variable using bioinformatics tools.</p><p><strong>Methods: </strong>An observational study was conducted on adults receiving warfarin. Allele discrimination method was used for estimating the single nucleotide polymorphisms (SNPs) in <i>CYP2C9</i>, VKORC1, and CYP4F2. MLAs were used for identifying the significant genetic and clinical variables in predicting the poor anticoagulation status (ACS) and stable warfarin dose. Advanced computational methods (SNPs' deleteriousness and impact on protein destabilization, molecular dockings, and 200 ns molecular dynamics simulations) were employed for examining the influence of <i>CYP2C9</i> SNPs on structure and function.</p><p><strong>Results: </strong>Machine learning algorithms revealed <i>CYP2C9</i> to be the most important predictor for both outcomes compared to the classical methods. Computational validation confirmed the altered structural activity, stability, and impaired functions of protein products of <i>CYP2C9</i> SNPs. Molecular docking and dynamics simulations revealed significant conformational changes with mutations R144C and I359L in <i>CYP2C9</i>.</p><p><strong>Conclusion: </strong>We evaluated various MLAs in predicting the critical outcome measures associated with warfarin and observed <i>CYP2C9</i> as the most critical predictor variable. The results of our study provide insight into the molecular basis of warfarin and the <i>CYP2C9</i> gene. A prospective study validating the MLAs is urgently needed.</p>\",\"PeriodicalId\":10770,\"journal\":{\"name\":\"Current drug metabolism\",\"volume\":\" \",\"pages\":\"466-476\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current drug metabolism\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2174/1389200224666230705124329\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current drug metabolism","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2174/1389200224666230705124329","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Computational Structural Validation of CYP2C9 Mutations and Evaluation of Machine Learning Algorithms in Predicting the Therapeutic Outcomes of Warfarin.
Aim: The study aimed to identify the key pharmacogenetic variable influencing the therapeutic outcomes of warfarin using machine learning algorithms and bioinformatics tools.
Background: Warfarin, a commonly used anticoagulant drug, is influenced by cytochrome P450 (CYP) enzymes, particularly CYP2C9. MLAs have been identified to have great potential in personalized therapy.
Objective: The purpose of the study was to evaluate MLAs in predicting the critical outcomes of warfarin therapy and validate the key predictor genotyping variable using bioinformatics tools.
Methods: An observational study was conducted on adults receiving warfarin. Allele discrimination method was used for estimating the single nucleotide polymorphisms (SNPs) in CYP2C9, VKORC1, and CYP4F2. MLAs were used for identifying the significant genetic and clinical variables in predicting the poor anticoagulation status (ACS) and stable warfarin dose. Advanced computational methods (SNPs' deleteriousness and impact on protein destabilization, molecular dockings, and 200 ns molecular dynamics simulations) were employed for examining the influence of CYP2C9 SNPs on structure and function.
Results: Machine learning algorithms revealed CYP2C9 to be the most important predictor for both outcomes compared to the classical methods. Computational validation confirmed the altered structural activity, stability, and impaired functions of protein products of CYP2C9 SNPs. Molecular docking and dynamics simulations revealed significant conformational changes with mutations R144C and I359L in CYP2C9.
Conclusion: We evaluated various MLAs in predicting the critical outcome measures associated with warfarin and observed CYP2C9 as the most critical predictor variable. The results of our study provide insight into the molecular basis of warfarin and the CYP2C9 gene. A prospective study validating the MLAs is urgently needed.
期刊介绍：
Current Drug Metabolism aims to cover all the latest and outstanding developments in drug metabolism, pharmacokinetics, and drug disposition. The journal serves as an international forum for the publication of full-length/mini review, research articles and guest edited issues in drug metabolism. Current Drug Metabolism is an essential journal for academic, clinical, government and pharmaceutical scientists who wish to be kept informed and up-to-date with the most important developments. The journal covers the following general topic areas: pharmaceutics, pharmacokinetics, toxicology, and most importantly drug metabolism.
More specifically, in vitro and in vivo drug metabolism of phase I and phase II enzymes or metabolic pathways; drug-drug interactions and enzyme kinetics; pharmacokinetics, pharmacokinetic-pharmacodynamic modeling, and toxicokinetics; interspecies differences in metabolism or pharmacokinetics, species scaling and extrapolations; drug transporters; target organ toxicity and interindividual variability in drug exposure-response; extrahepatic metabolism; bioactivation, reactive metabolites, and developments for the identification of drug metabolites. Preclinical and clinical reviews describing the drug metabolism and pharmacokinetics of marketed drugs or drug classes.
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