Integrative modeling core

核心5：集成建模 核心摘要 我们的目标是使项目和其他核心执行基于结构的发现和优化配体， 病毒蛋白靶点。这一目标将通过开发和应用我们独特的综合建模来实现 工具箱来计算目标病毒系统的结构模型，基于来自其他实验室的不同实验数据。 核心和项目。获得这些模型的关键挑战是病毒蛋白的结构异质性， 包括二级结构含量和畴取向的大的变化以及 环和侧链构象。准确，精确，完整的描述和表征这些 多状态是理解和调节配体功能的关键。我们假设， 特别需要对病毒蛋白质的多种构象进行建模：病毒蛋白质组可能已经进化为 利用构象的多样性来提供比不受限制的蛋白质组更多的功能 到少量的短蛋白质。我们将以两种方式应对这一挑战。第一，粗粒结构 模型（目标1），基于来自冷冻电子显微镜，冷冻电子断层扫描， 化学交联和足迹将为原子结构提供必要的步骤;例如，通过 适用于X射线晶体学的变体设计和高分辨率单粒子冷冻的起始模型 EM重建。第二，明确描述病毒蛋白质异质性的多状态原子模型 将根据X射线晶体学（Aim 2）、低温电子显微镜（Aim 3）和 配体构效关系（SAR）研究（目的4）。我们的多状态模型将有助于揭示静态， 动态的，甚至是病毒蛋白的隐蔽结合口袋，这反过来又将促进配体的发现， 优化.所有核心和项目都将依赖我们的模型。

CORE 5: INTEGRATIVE MODELING CORE SUMMARY We aim to enable Projects and other Cores to perform structure-based discovery and optimization of ligands for viral protein targets. This goal will be achieved by developing and applying our unique integrative modeling toolbox to compute structural models of the target viral systems, based on varied experimental data from other Cores and Projects. The key challenge in obtaining these models is structural heterogeneity of viral proteins, including large variations in secondary structure content and domain orientations as well as small variations in loop and side chain conformations. Accurate, precise, and complete description and characterization of these multiple states is key to understanding and modulating their functions with ligands. We hypothesize that explicit modeling of multiple conformations of viral proteins is especially needed: Viral proteomes may have evolved to exploit the multiplicity of conformations for delivering function more than the proteomes that are not constrained to a small number of short proteins. We will address this challenge in two ways. First, coarse-grained structural models (Aim 1), based on limited information from cryo-electron microscopy, cryo-electron tomography, chemical cross-linking, and footprinting, will provide an essential step to atomic structures; for example, via design of variants suitable for X-ray crystallography and starting models for high-resolution single particle cryo- EM reconstruction. Second, multi-state atomic models of viral proteins that explicitly describe their heterogeneity will be computed based on data from X-ray crystallography (Aim 2), cryo-electron microscopy (Aim 3), and ligand structure-activity relationship (SAR) studies (Aim 4). Our multi-state models will help reveal static, dynamic, and even cryptic binding pockets of viral proteins, which, in turn, will facilitate ligand discovery and optimization. All Cores and Projects will rely on our models.