Structural Dynamics of Viral Proteins: Development and Application of Multiscale Computational Methods for Studying Viral Capsids, Proteins and Membrane Systems

这份提案为我未来五年的研究计划提出了一个愿景。我的实验室从事 应用和发展多尺度计算方法来研究生物分子系统，主要 对无包膜病毒衣壳、生物膜和蛋白质动力学感兴趣。通过这些研究，我们 将提供建模工具，深入了解生物分子功能的调节和机制，并应用于 深度学习方法，以获得对蛋白质通讯和构象变化的新理解。 我们研究病毒衣壳的主要动机是了解病毒衣壳蛋白的决定因素和分子机制。 感染过程导致衣壳脱壳/解体。我们对病毒系统的研究将扩展到 肠道病毒属，包括严重的健康威胁，如脊髓灰质炎病毒，EV-A71和EV-D 68。有 成熟的、未包被的中间体和基因组释放状态的许多高分辨率结构， 肠道病毒使这一研究方向。这些研究的重要结果将包括详细的 关于病毒感染相关过程的结构和能量信息，这将是有价值的 开发针对这些药剂的抗病毒疗法。我们对生物膜的兴趣主要与 双层脂质的组成和形状如何影响脂质的结构、动力学和功能特性， 肽和蛋白质。我们对病毒衣壳和生物膜的研究将涉及多分辨率方法 包括原子解析和粗粒度模型。对于病毒衣壳，粗粒度模型将 先进的研究脱壳和基因组释放和软件将开发和分发， 目的.我们在生物膜方面的工作将得到持续发展和加强的支持， BUMPy软件用于构建具有生物灵感形状的弯曲膜系统。我们还将研究 先天免疫系统的蛋白质成分，我们将在其中使用监督机器学习 从不同的结构或生化状态进行模拟分类的方法。使用这些 方法将使我们能够定义新的集体变量来计算分子的途径和能量学， 识别和激活。对于所有提出的研究，我们将采用先进的多尺度建模方法 并有现有的或确定的新的实验合作者与这些系统的共同利益， 这些问题，在这些调查中合作。

This proposal presents a vision for my research program over the next five years. My lab is engaged in the application and development of multiscale computational methods to study biomolecular systems, with main driver interests in non-enveloped virus capsids, biomembranes and protein dynamics. Through these studies we will provide modeling tools, gain insights into the regulation and mechanisms of biomolecular functions and apply deep learning methods to gain a new comprehension of protein communication and conformational changes. The main motivation in our viral capsid studies is to understand the determinants and molecular mechanisms of infection processes leading to capsid uncoating/disassembly. Our work on virus systems will expand into the genus of Enteroviruses, which include severe health threats such as poliovirus, EV-A71 and EV-D68. There are numerous high resolution structures of mature, uncoating intermediates and genome released states of enteroviruses which enable this research direction. Significant findings from these studies will include detailed structural and energetic information regarding viral infection related processes, which will be valuable in the development of anti-viral therapies against these agents. Our interests in biomembranes are centrally related to how bilayer lipid composition and shape affect the structure, dynamics and functional properties of lipids, peptides and proteins. Our work on virus capsids and biomembranes will involve multi-resolution approaches including atomistically resolved and coarse-grained models. For virus capsids, coarse-grained models will be advanced to study uncoating and genome release and software will be developed and distributed for this purpose. Our work on biomembranes will be supported by the continued development and enhancement of our BUMPy software for constructing curved membrane systems with biologically inspired shapes. We will also study protein components of the innate immune system, where we will employ supervised machine learning approaches to perform classification of simulations from different structural or biochemical states. Using these approaches will allow us to define new collective variables to compute pathways and energetics of molecular recognition and activation. For all the proposed studies we will employ advanced multiscale modeling methods and have existing or identified new experimental collaborators with mutual interest in these systems and questions, to partner with in these investigations.