Evolution of antiviral resistance mutations and their biological and biophysical implications

抗病毒耐药突变的演变及其生物学和生物物理意义

• 批准号: 10242909
• 负责人: Ronald Levy
• 金额: $ 117.56万
• 依托单位: SEATTLE CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10242909
• 关键词: Address; Affect; Amino Acid Sequence; Amino Acids; Antiretroviral resistance; Antiviral resistance; Bar Codes; Biochemical; Bioinformatics; Biological; Biological Assay; Biophysics; Capsid; Characteristics; Clinical; Collaborations; Complement; Data; Development; Drug Modelings; Drug resistance; Enzymes; Evolution; Failure; Funding; Gag PR; Genetic; Goals; HIV; HIV Infections; HIV-1; Individual; Integrase; Integration Host Factors; Investigation; Lead; Length; Link; Linkage Disequilibrium; Location; Measures; Methodology; Modeling; Mutation; National Institute of General Medical Sciences; Nature; Patients; Pattern; Peptide Hydrolases; Pharmaceutical Preparations; Pharmacotherapy; Positioning Attribute; Probability; Proteins; RNA-Directed DNA Polymerase; Resistance; Resistance development; Risk; Role; Sampling; Sequence Alignment; Statistical Methods; Statistical Models; Structure; Technology; Time; Treatment Failure; Validation; Viral; Viral Proteins; Virus; antiretroviral therapy; base; database structure; deep sequencing; experience; fitness; gag Gene Products; inhibitor/antagonist; innovative technologies; insight; kinetic model; next generation sequencing; novel; patient population; pol Gene Products; pressure; prospective; resistance mutation; response; single molecule; small molecule; success; therapy resistant; treatment response; viral fitness; virology

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.

抽象的 抗逆转录病毒治疗下的HIV-1选择了由于遗传连接的突变，这些突变因 对蛋白质结构稳定性和功能的约束，这有助于适应性。项目5研究是 与分析的抗逆转录病毒抗性突变的分析对（或高阶）模式有关 结合生物物理，生化和结构对药物耐药性和病毒适应性的影响。在过去 资金期，开发了新的统计方法，以识别存在的相关突变模式 遗传上未链接的GAG和蛋白酶深度测序数据。 potts汉密尔顿概率模型是 由蛋白酶序列比对构建，以识别导致抗药性的突变模式。 为了扩展过去的发现，建议识别一般连接的抗逆转录病毒抗性模式 来自全长的，来自进化枝B或非乳腺B HIV感染患者的突变 抗逆转录病毒治疗。研究影响选择的HIV蛋白中的结构约束 抗性突变，利用序列和 结构数据。 Torbett的新型全长测序方法和病毒学专业知识的结合 将通过生物信息学和征收征款的建模专业知识来完成以下特定目标： 1）在纵向患者的HIV中确定一般连接的药物抗药性突变（对或更高级） 利用多读条形码辅助的单分子测序（MRBASMS）的样品。协变量 突变将在功能和结构上使用先前描述的生化， 生物物理和病毒学测定法以验证其在耐药性崛起中的作用。 2）全长，来自1），以及来自数据库和结构信息的HIV序列数据，将用于 构建药物幼稚和药物经验的蛋白酶，逆转录酶，整合酶和potts模型 插科打诨。 Potts模型将用于研究上认识突变组合对适应性的影响，如 以及预测HIV蛋白保留率有抗药性突变的风险。这些研究会 提供对HIV遗传障碍的重要洞察力，必须克服这些障碍才能发展对多重 抑制剂组合。 纵向患者样本的HIV准菜的MRBASMS测序将由Torbett和 Sarafianos，以及外部合作者Routh（UTMB）。生化，结构和病毒学 验证突变协变量将由Torbett，Sarafianos和Levy领导，并由 核心2。LEVY将从获得HIV序列数据和蛋白质结构信息中开发POTTS模型 来自项目1、2和核心1。