Department of Chemistry, Temple University, Philadelphia, Pennsylvania19122, United States.
Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania19122, United States.
J Phys Chem B. 2022 Dec 22;126(50):10622-10636. doi: 10.1021/acs.jpcb.2c06123. Epub 2022 Dec 9.
The ability of HIV-1 to rapidly mutate leads to antiretroviral therapy (ART) failure among infected patients. Drug-resistance mutations (DRMs), which cause a fitness penalty to intrinsic viral fitness, are compensated by accessory mutations with favorable epistatic interactions which cause an evolutionary trapping effect, but the kinetics of this overall process has not been well characterized. Here, using a Potts Hamiltonian model describing epistasis combined with kinetic Monte Carlo simulations of evolutionary trajectories, we explore how epistasis modulates the evolutionary dynamics of HIV DRMs. We show how the occurrence of a drug-resistance mutation is contingent on favorable epistatic interactions with many other residues of the sequence background and that subsequent mutations entrench DRMs. We measure the time-autocorrelation of fluctuations in the likelihood of DRMs due to epistatic coupling with the sequence background, which reveals the presence of two evolutionary processes controlling DRM kinetics with two distinct time scales. Further analysis of waiting times for the evolutionary trapping effect to reverse reveals that the sequences which entrench (trap) a DRM are responsible for the slower time scale. We also quantify the overall strength of epistatic effects on the evolutionary kinetics for different mutations and show these are much larger for DRM positions than polymorphic positions, and we also show that trapping of a DRM is often caused by the collective effect of many accessory mutations, rather than a few strongly coupled ones, suggesting the importance of multiresidue sequence variations in HIV evolution. The analysis presented here provides a framework to explore the kinetic pathways through which viral proteins like HIV evolve under drug-selection pressure.
HIV-1 快速突变的能力导致感染患者的抗逆转录病毒治疗 (ART) 失败。耐药突变 (DRMs) 会导致内在病毒适应性降低,但有利的上位相互作用的辅助突变会对其进行补偿,从而导致进化陷阱效应,但这一整体过程的动力学尚未得到很好的描述。在这里,我们使用描述上位相互作用的 Potts 哈密顿模型结合进化轨迹的动力学蒙特卡罗模拟,探索了上位相互作用如何调节 HIV DRMs 的进化动力学。我们展示了耐药突变的发生如何取决于与序列背景中许多其他残基的有利上位相互作用,以及随后的突变如何使 DRMs 根深蒂固。我们测量了由于与序列背景的上位相互作用而导致 DRMs 出现的可能性的时间自相关,这揭示了控制 DRM 动力学的两个进化过程的存在,它们具有两个不同的时间尺度。进一步分析进化陷阱效应逆转的等待时间表明,使 DRM 陷入困境(困住)的序列负责较慢的时间尺度。我们还量化了不同突变对进化动力学的上位相互作用的整体强度,结果表明,对于 DRM 位置,上位相互作用的强度比多态性位置大得多,并且我们还表明,DRM 的捕获通常是由许多辅助突变的集体效应引起的,而不是少数几个强耦合突变引起的,这表明多残基序列变异在 HIV 进化中的重要性。这里提出的分析为探索 HIV 等病毒蛋白在药物选择压力下进化的动力学途径提供了一个框架。