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Molecular escape mechanisms due to patterns of resistance-associated amino acid variants in the hepatitis C virus NS3 protease

丙型肝炎病毒 NS3 蛋白酶中耐药相关氨基酸变异模式引起的分子逃逸机制

基本信息

批准号：
238386962
负责人：
Privatdozent Dr. Christoph Welsch
金额：
--
依托单位：
Max-Planck-Institut für Informatik
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2013
资助国家：
德国
起止时间：
2012-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/238386962?language=en
关键词：
Molecular escape mechanisms due patterns

项目摘要

Resistance-associated amino acid variants are a challenging problem in the era of direct-acting antiviral agents in hepatitis C (HCV). Clonal and deep sequencing techniques enable the identification of minority variants from HCV-infected patient sera and for gaining more profound insight into the dynamics of resistance acquisition in the viral quasispecies under drug pressure. Complex patterns of variants in treatment escape from ketoamide and macrocyclic NS3 protease inhibitors (PI) are expected to arise with second-site mutations emerging to compensate for resistant variant fitness losses, which is crucial to select variants from the quasispecies population under drug pressure. We perform large scale sequencing of HCV patient sera from PI-containing regimens and machine learning to identify treatment-failure related variant patterns in the NS3 protease domain. We will apply molecular virology tools, i.e. infectious HCV cell culture, for phenotype description of resistant variants and second-site mutations. Using a residue-interaction network approach on crystal structures and molecular dynamics simulation data of the NS3 protease, we aim in identifying protease residues of structural and functional importance and their role in molecular escape mechanisms from PI treatment. Using the data from phenotype characterization of the protease variants, we will be able to differentiate between resistance associated and compensatory sites. The goal of this research proposal is to translate knowledge from molecular virology and structure biology of NS3 protease variants into treatment algorithms to avoid resistance development and treatment failure in future antiviral therapy.

在丙型肝炎（HCV）的直接作用抗病毒剂时代，耐药相关氨基酸变异是一个具有挑战性的问题。克隆和深度测序技术能够从HCV感染的患者血清中鉴定少数变异体，并更深入地了解药物压力下病毒准种获得耐药性的动态。预计在酮酰胺和大环NS3蛋白酶抑制剂（PI）的治疗逃逸中出现复杂的变异模式，同时出现第二位点突变以补偿耐药变异体适应性损失，这对于在药物压力下从准种群体中选择变异体至关重要。我们对含PI方案的HCV患者血清进行大规模测序和机器学习，以识别NS 3蛋白酶结构域中与治疗失败相关的变异模式。我们将应用分子病毒学工具，即感染性HCV细胞培养，用于耐药变体和第二位点突变的表型描述。使用残基相互作用网络方法的晶体结构和分子动力学模拟数据的NS3蛋白酶，我们的目的是在确定蛋白酶残基的结构和功能的重要性和它们的作用，从PI治疗的分子逃逸机制。使用来自蛋白酶变体的表型表征的数据，我们将能够区分抗性相关位点和补偿位点。这项研究计划的目标是将NS3蛋白酶变体的分子病毒学和结构生物学知识转化为治疗算法，以避免未来抗病毒治疗中的耐药性发展和治疗失败。