Evolution of antiviral resistance mutations and their biological and biophysical implications

摘要 正在接受抗逆转录病毒治疗的HIV-1选择与基因相关的突变，原因是 对蛋白质结构稳定性和功能的限制，这有助于健身。项目5的研究包括 与分析成对(或更高顺序)的抗逆转录病毒耐药突变及其 生物物理、生化和结构对抗药性和病毒适应性的综合影响。在过去 在资助期间，开发了新的统计方法来确定存在于 基因上没有关联的Gag和蛋白酶深度测序数据。Potts哈密顿概率模型 从蛋白酶序列比对中构建，以识别导致耐药性的突变模式。 为了扩展过去的发现，建议确定抗逆转录病毒耐药性的基因关联模式。 来自B分支或非B分支HIV感染患者的全长单个病毒的突变 抗逆转录病毒治疗。研究HIV蛋白中影响选择的结构限制因素 抗性突变，将利用序列和序列建立蛋白质序列共变的Potts模型 结构数据。一种新的全长测序方法与Torbett的病毒学专业知识相结合 利维的生物信息学和建模专业知识将与之相辅相成，以实现以下具体目标： 1)在纵向患者中鉴定HIV的基因连锁耐药突变(成对或更高顺序) 利用多读条形码辅助单分子测序(MRBASMS)的样品。协变 突变将使用前面描述的生物化学在功能和结构上进行表征， 生物物理和病毒学分析，以验证它们在耐药性上升中的作用。 2)将利用来自1)的全长和来自数据库的艾滋病毒序列数据和结构信息 构建药物朴素和药物相关的蛋白水解酶、逆转录酶、整合酶和 恶作剧。POTS模型将用于研究上位性突变组合对适应度的影响，如 以及预测艾滋病毒蛋白残留物存在耐药突变发展的风险。这些研究将 提供对HIV基因障碍的重要见解，这些障碍必须克服才能对多种病毒产生抵抗力 抑制剂组合。 来自纵向患者样本的HIV准种的MR BASMS测序将由Torbett和 萨拉菲亚诺斯和外部合作者劳斯(UTMB)。生化、结构和病毒学 突变协变量的验证将由Torbett、Sarafianos和Levy领导，并由 Levy将根据HIV序列数据和获得的蛋白质结构信息开发POTS模型 来自项目1、2和核心1。

ABSTRACT HIV-1 under antiretroviral treatment selects for genetically-linked mutations that are correlated due to constraints on protein structural stability and function, which contribute to fitness. Project 5 studies are concerned with analyzing pairs (or higher-order) patterns of antiretroviral resistance mutations and their combined biophysical, biochemical, and structural effects on drug-resistance and viral fitness. During the past funding period, new statistical methods were developed to identify correlative mutational patterns present in genetically unlinked Gag and protease deep sequencing data. Potts Hamiltonian probabilistic models were constructed from protease sequence alignments to identify mutational patterns that lead to drug-resistance. To extend the past findings, it is proposed to identify genetically-linked patterns of antiretroviral resistance mutations from full-length, individual viruses from clade B or non-clade B HIV-infected patients during antiretroviral treatment. To investigate structural constraints in HIV proteins that influence selection of resistance mutations, Potts models of protein sequence covariation will be developed utilizing sequence and structural data. The combination of a novel full-length sequencing approach and virology expertise by Torbett will be complemented by bioinformatics and modeling expertise of Levy to serve the following specific aims: 1) Identify genetically-linked drug-resistance mutations (pairs or higher order) from HIV in longitudinal patient samples utilizing Multi-read Barcode-Assisted Single Molecule Sequencing (MrBASMS). Covariant mutations will be functionally and structurally characterized using previously described biochemical, biophysical and virological assays to validate their role in the rise of drug resistance. 2) Both full-length, from 1), and HIV sequence data from databases and structural information will be utilized to construct Potts models of drug naïve and drug-experienced protease, reverse transcriptase, integrase and Gag. Potts models will be used to investigate the effects of epistatic mutational combinations on fitness, as well as predict HIV protein residues at risk for drug-resistance mutation development. These studies will provide critical insight into HIV genetic barriers that must be overcome to develop resistance to multiple inhibitor combinations. The MrBASMS sequencing of HIV quasispecies from longitudinal patient samples will be led by Torbett and Sarafianos, along with outside collaborator Routh (UTMB). The biochemical, structural and virological validation of mutational covariants will be led by Torbett, Sarafianos and Levy, along with assistance from Core 2. Levy will develop Potts models from HIV sequence data and protein structural information obtained from Projects 1, 2, and Core 1.