Interactions of retroviral and host proteins guided by advanced modeling

先进模型指导下的逆转录病毒和宿主蛋白的相互作用

• 批准号: 10551964
• 负责人: MONICA J ROTH
• 金额: $ 64.43万
• 依托单位: RUTGERS BIOMEDICAL AND HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-30 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10551964
• 关键词: Address; Affinity; Area; Artificial Intelligence; Binding; Binding Proteins; Bioinformatics; Cell physiology; Computer Assisted; Development; Disease; Drug Design; Foundations; Generations; Genes; Integrase; Knowledge; Lead; Life; Membrane Proteins; Modeling; Molecular; Mus; Oncogenes; Orphan; Pathogenesis; Protein Family; Proteins; Public Health; Receptor Cell; Regulation; Research; Specificity; Structure; Tissues; Viral; Viral Pathogenesis; Virus; Virus Receptors; design; drug discovery; env Gene Products; inhibitor; leukemia; novel; novel strategies; programs; protein structure prediction; receptor; small molecule; small molecule inhibitor; tool; virology

ABSTRACT With the recent revolution in artificial intelligence for molecular design and protein structure prediction, we were motivated to apply these new tools to address bottlenecks in our research focusing on retroviral entry, integration, and drug design. Viral entry and receptor usage has become a major focus with the emergence of new viruses with expanded host and tissue specificities. Our research focuses on the ability of retroviral Envelopes to select and utilize novel host cell receptors. In this proposal, we are utilizing new approaches to identify and study two novel retroviral Env proteins and their host cell receptors. These include the binding of the A5/A9a Env protein to the host membrane protein SLC35F2 and the identification of the cognate receptor(s) for the L1 Env. Applying AlphaFold2, Phyre2 and Evolutionary Covariance structure prediction programs, we have a first generation model for SLC35F2, which serves as the foundation for a broad number of questions relating to the function of this orphan receptor. The second area of focus builds on the gammaretroviral Integrase (IN) protein binding to the host BET proteins. Through our structural studies of both the Murine Leukemia Leukemia (MLV) IN protein and the host NSD3 protein binding to the ET domain of the Brd3 BET protein, we are now able to apply our knowledge of the common binding pocket to advance approaches for studies of alternative binding substrates and small molecule inhibitors. The ET domain of the BET family of proteins serves as a node for multi-protein assemblies. Understanding the affinity of different proteins and small molecules to this ET binding pocket can have profound effects of gammaretroviral pathogenesis as well as gene and oncogene regulation. Using computer-aided drug discovery approaches, we have identified first-in-class lead compounds targeting the ET domain. These studies build on our cohesive collaborative research team with expertise in virology, NMR structural studies, and bioinformatics.

抽象的 随着最近分子设计和蛋白质结构人工智能的革命 预测，我们有动力应用这些新工具来解决我们研究中的瓶颈 专注于逆转录病毒进入、整合和药物设计。病毒进入和受体使用 随着宿主和组织扩大的新病毒的出现成为主要焦点 特殊性。我们的研究重点是逆转录病毒包膜选择和利用新型病毒的能力 宿主细胞受体。在本提案中，我们正在利用新方法来识别和研究两个 新型逆转录病毒环境蛋白及其宿主细胞受体。其中包括 A5/A9a 的结合 Env蛋白与宿主膜蛋白SLC35F2及其同源物的鉴定 L1 Env 的受体。应用AlphaFold2、Phyre2和进化协方差结构 预测程序，我们有 SLC35F2 的第一代模型，它作为 为与该孤儿受体功能相关的许多问题奠定了基础。这 第二个重点领域是伽马逆转录病毒整合酶 (IN) 蛋白与宿主 BET 的结合 蛋白质。通过我们对小鼠白血病 (MLV) IN 蛋白的结构研究 以及宿主 NSD3 蛋白与 Brd3 BET 蛋白的 ET 结构域结合，我们现在能够 应用我们对共同结合口袋的知识来推进研究方法 替代结合底物和小分子抑制剂。 BET 家族的 ET 结构域 蛋白质充当多蛋白质组装的节点。了解不同事物的亲和力 蛋白质和小分子结合到这个 ET 结合袋上可以产生深远的影响 γ逆转录病毒发病机制以及基因和癌基因调控。使用计算机辅助 在药物发现方法中，我们已经确定了针对 ET 的一流先导化合物 领域。这些研究建立在我们具有凝聚力的合作研究团队的基础上，该团队拥有以下方面的专业知识： 病毒学、核磁共振结构研究和生物信息学。