Computational Structural Validation of CYP2C9 Mutations and Evaluation of Machine Learning Algorithms in Predicting the Therapeutic Outcomes of Warfarin.

IF 2.1 4区医学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY

Current drug metabolism Pub Date : 2023-01-01 DOI:10.2174/1389200224666230705124329

Kannan Sridharan, Thirumal Kumar D, Suchetha Manikandan, Gaurav Prasanna, Lalitha Guruswamy, Rashed Al Banna, George Priya Doss C

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引用次数: 0

Abstract

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.

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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。

目的：本研究旨在使用机器学习算法和生物信息学工具确定影响华法林治疗结果的关键药物遗传学变量。背景：华法林是一种常用的抗凝药物，受细胞色素P450（CYP）酶，特别是CYP2C9的影响。MLA已被确定在个性化治疗中具有巨大潜力。目的：本研究的目的是评估MLA在预测华法林治疗的关键结果方面的作用，并使用生物信息学工具验证关键的预测基因分型变量。方法：对接受华法林治疗的成年人进行观察性研究。等位基因鉴别法用于评估CYP2C9、VKORC1和CYP4F2的单核苷酸多态性（SNPs）。MLA用于确定预测不良抗凝状态（ACS）和稳定华法林剂量的重要遗传和临床变量。采用先进的计算方法（SNPs的毒性和对蛋白质不稳定的影响、分子对接和200ns分子动力学模拟）来检查CYP2C9 SNPs对结构和功能的影响。结果：与经典方法相比，机器学习算法显示CYP2C9是两种结果的最重要预测因子。计算验证证实了CYP2C9 SNPs蛋白质产物的结构活性、稳定性和功能受损。分子对接和动力学模拟揭示了CYP2C9中R144C和I359L突变的显著构象变化。结论：我们评估了各种MLA在预测与华法林相关的关键结果指标方面的作用，并观察到CYP2C9是最关键的预测变量。我们的研究结果为深入了解华法林和CYP2C9基因的分子基础提供了依据。迫切需要一项验证MLA的前瞻性研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Current drug metabolism 医学-生化与分子生物学

CiteScore

4.30

自引率

4.30%

发文量

审稿时长

4-8 weeks

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.