Mechanisms of HIV fitness and drug resistance inferred from high-resolution molecular dynamics and sequence co-variation models

摘要 全世界约有4000万人感染了人类免疫缺陷病毒1型(HIV-1， 通常指的是艾滋病毒)。由于目前没有治愈方法，抗逆转录病毒治疗是主要的治疗方法。 选择。然而，随着时间的推移，由于耐药性的发展，抗逆转录病毒治疗最终会失败。我们会 开发新的计算工具来预测治疗选择下的HIV进化轨迹 压力导致耐药性，使用高分辨率全原子分子动力学模拟与 序列协变的基于物理的机器学习模型。计算研究将是 辅以对两个HIV蛋白多聚体靶标的结构、生物物理和病毒学研究：HIV 整合酶(IN)和衣壳蛋白(CA)。建模和实验将以迭代的方式进行， 实验结果被用于验证、参数化和改进模型；以及分子 用于指导新实验和开发高分辨率低温电磁新工具的动力学模拟 改进HIV抑制剂与界面溶剂的多种结合模式。我们的共同主题是 拟议的工作是为观察到的突变的适合性和抗性效应提供结构性解释， 目标是开发可用于预测病毒突变的整体结构-功能模型 给出了药物选择压力下的运动轨迹，并给出了机理解释。有三个具体的 目的：(1)确定不同药物环境下突变上位性的物理机制， 并使用MD模拟和病毒学数据来参数化HIV IN和CA在 新的理论框架；(2)使用高分辨率、大尺度的炼金术分子动力学自由能 基于先进抽样方法的模拟分析蛋白质突变对蛋白质稳定性的影响 构成内体和衣壳颗粒组件的蛋白质-蛋白质界面；(3)决定 HIV-IN抑制剂多种结合模式的分子基础及溶剂化在强结合中的作用 这些抑制物中。这些目标寻求实现对合作效应(上位性)的分子理解。 抑制物与其病毒蛋白靶标(IN、CA)结合的多残基突变模式及其影响 关于多聚体(内质粒和衣壳粒)的稳定性。我们预计这项工作将导致 开发监测工具来预测病毒系统对抗病毒药物选择压力的反应 治疗学。

ABSTRACT There are ~40 million people world-wide infected by the Human Immunodeficiency Virus Type 1 (HIV-1, commonly referred to as HIV). As currently there is no cure, antiretroviral treatment is the primary treatment option. Yet antiretroviral treatment eventually fails over time due to the development of drug resistance. We will develop new computational tools for forecasting HIV evolutionary trajectories under therapeutic selection pressure leading to drug resistance, using high resolution all atom molecular dynamics simulations together with physics-based machine learning models of sequence co-variation. The computational studies will be complemented by structural, biophysical, and virological studies on two HIV protein multimeric targets: HIV integrase (IN), and capsid (CA). The modeling and experiments will be employed in an iterative manner, with the experimental results being used to validate, parameterize and improve the models; and the molecular dynamics simulations used to guide new experiments and also to develop new tools for high resolution cryo-EM refinement of multiple binding modes of HIV inhibitors and interfacial solvent. The common theme of our proposed work is to provide structural interpretations for the observed fitness and resistance effects of mutations, with the goal of developing holistic structure-function models which can be used to predict viral mutation trajectories under drug selection pressure and give a mechanistic explanation for them. There are three specific aims: (1) determine the physical mechanisms underlying mutational epistasis under varied drug environments, and use MD simulations and virological data to parameterize drug specific landscapes for HIV IN and CA under a novel theoretical framework; (2) use high resolution, large scale alchemical molecular dynamics free energy simulations based on advanced sampling methods to analyze the effects of protein mutations on the stability of protein-protein interfaces that constitute the intasome and the capsid particle assemblies; (3) determine the molecular basis for multiple binding modes of inhibitors of HIV IN, and the role of solvation in the strong binding of these inhibitors. These aims seek to achieve a molecular understanding of the cooperative effects (epistasis) of multi-residue mutation patterns on the binding of inhibitors to their viral protein targets (IN, CA) and their effects on the stability of the multimers (intasome and capsid particle). We anticipate that this work will lead to the development of surveillance tools to forecast the response of viral systems to the selection pressure of antiviral therapeutics.