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评估in silico工具和分子动力学模拟的性能,以预测药物遗传变异影响

Maryam Jamal AlSaeed^1,2, Peter Ramdhan³, Jean Gabriel Malave¹

¹Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA.

Clinical pharmacology and therapeutics

|June 19, 2024

概括

使用in silico工具预测药物基因功能是一项挑战. 分子动态模拟可能比基于序列或结构的预测更准确地评估非同义单核酸多态 (nsSNP) 影响.

科学领域:

药物基因组学药物基因组学
计算生物学计算生物学
生物信息学是一种生物信息学.

背景情况:

药物基因中的非同义单核酸多态 (nsSNP) 可以改变蛋白质功能,影响药物反应.
自由可用的nSSNP工具对药物基因功能的影响的预测准确性仍然不清楚.

研究的目的:

评估基于序列和基于结构的in silico工具在预测 nsSNP 在关键药物基因中的功能影响方面的性能.
调查分子动力学 (MD) 模拟用于评估nsSNP在CYP2C9.9中的影响的实用性.

主要方法:

在CYP2C19,CYP2C9,CYP2B6,CYP2D6和DPYD基因中使用118个nsSNP评估了七种基于序列和五种基于结构的工具,具有已知的功能结果.
用S-华法林对CYP2C9变体 (*3和 *8) 进行MD模拟,以分析基质结合和代谢部位相互作用.

主要成果:

与基于结构的工具相比,基于序列的工具显示出更高的正预测值,但较低的负预测值.
在基于序列的工具 (59%) 和基于结构的工具 (34%) 之间,准确度没有显著差异.
MD模拟显示,CYP2C9变体 (I359L和R150H) 改变了S-华法林的结合和定位,可能阻碍了新陈代谢.

结论:

目前基于序列和结构的in silico工具在准确预测 nsSNP 对药物基因功能的影响方面存在局限性.
分子动态模拟可能提供一种更可靠的方法,以了解nSNP在药物基因中的功能后果.

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