Centre for Computational Science, Department of Chemistry, University College London, London WC1H 0AJ, UK.
J Chem Inf Model. 2011 Oct 24;51(10):2636-49. doi: 10.1021/ci200308r. Epub 2011 Oct 7.
The emergence of drug resistance is a major challenge for the effective treatment of HIV. In this article, we explore the application of atomistic molecular dynamics simulations to quantify the level of resistance of a patient-derived HIV-1 protease sequence to the inhibitor lopinavir. A comparative drug ranking methodology was developed to compare drug resistance rankings produced by the Stanford HIVdb, ANRS, and RegaDB clinical decision support systems. The methodology was used to identify a patient sequence for which the three rival online tools produced differing resistance rankings. Mutations at only three positions ( L10I , A71IV, and L90M ) influenced the resistance level assigned to the sequence. We use ensemble molecular dynamics simulations to elucidate the origin of these discrepancies and the mechanism of resistance. By simulating not only the full patient sequences but also systems containing the constituent mutations, we gain insight into why resistance estimates vary and the interactions between the various mutations. In the same way, we also gain valuable knowledge of the mechanistic causes of resistance. In particular, we identify changes in the relative conformation of the two beta sheets that form the protease dimer interface which suggest an explanation of the relative frequency of different amino acids observed in patients at residue 71.
耐药性的出现是有效治疗 HIV 的主要挑战。在本文中，我们探讨了原子分子动力学模拟在量化患者衍生的 HIV-1 蛋白酶序列对抑制剂洛匹那韦的耐药程度的应用。开发了一种比较药物排序方法，以比较斯坦福 HIVdb、ANRS 和 RegaDB 临床决策支持系统生成的耐药性排序。该方法用于确定三个竞争在线工具对患者序列产生不同耐药性排序的患者序列。只有三个位置的突变（L10I、A71IV 和 L90M）影响了序列分配的耐药水平。我们使用集合分子动力学模拟阐明这些差异和耐药机制的起源。通过模拟不仅是完整的患者序列，而且还包含组成突变的系统，我们深入了解为什么耐药估计值会有所不同以及各种突变之间的相互作用。同样，我们还获得了耐药性机制原因的有价值的知识。特别是，我们确定了形成蛋白酶二聚体界面的两个β片层的相对构象的变化，这表明了在残基 71 处观察到的不同氨基酸的相对频率的解释。
