EnzyDock-based Multistate and Multiscale Tools for Covalent Drug Design

项目摘要/摘要 近年来，FDA批准了越来越多的与靶生物共价相关的药物 分子。为了扩大共价抑制剂的开发，技术上更有针对性地发现 这类抑制剂是必需的。还有必要解决对非现场反应性和毒性的关切。 与共价药物有关。这项提议的特别重点是发展多尺度的硅共价 结合强健量子力学和分子力学(QM/MM)势的对接方法 使用EnzyDock对接平台，从而能够显式模拟多步骤化学事件及其 在寻找停靠姿势的过程中做出了积极的贡献。当前的对接方法缺乏以下能力 以与抑制剂的前共价结合模式一致的方式执行共价键的形成 与反应过渡态和共价键模式相同。这种能力的缺乏不仅阻碍了 对弹头-目标反应性的基本了解，但也构成了在硅胶领域取得进展的技术障碍 对接战略。事实上，许多现有的对接计划提供了执行共价对接的能力，但 以一种特别的方式，因为在程序开发的设计阶段没有考虑共价对接。 以克服这一技术挑战为目标，有两个具体目标：目标1是开发多尺度 QM/MM/EnzyDock共价对接方法。在这一开发中，EnzyDock将作为主要的对接 将开发平台和稳健的半经验QM/MM势，并针对每个特定弹头进行校准- 目标反应类型，并与EnzyDock相结合。此外，我们还将开发和实现通用的 QM/MM势框架下改进QM/MM对接体系能级的Born(GB)溶剂化模型 摆姿势。AIM 2将应用在AIM 1中开发的QM/MM/EnzyDock方法来建立有效的工作流程 在大型共价抑制剂数据库的电子筛选中。具体地说，将探讨两个工作流：第一个 工作流基于与预定义的共价连接站点的对接，该站点在大多数共价连接中使用 对接程序。第二个工作流程需要一种动态的共价对接方法，其中共价对接 使用化学信息学在对接过程中动态地搜索和确定配体上的连接位置 与结合口袋中的靶残基进行分析和空间接近。在这项研究中，研究将是有限的 只与半胱氨酸残基反应的弹头，而额外的靶残基、反应类型和 在未来的研究中将考虑弹头，以构建更全面的弹头-目标反应 数据库。因此，这两个工作流程将根据已知结构和 药物-半胱氨酸共价体系的动力学/热力学数据。我们希望在这个项目中开发的方法 将使In硅基共价抑制剂的发现更加有力，并有助于理解亲电靶标 用于弹头设计和选择的反应性。

PROJECT SUMMARY/ABSTRACT In recent years, FDA has approved a growing number of drugs that are covalently linked to target biological molecules. To expand the development of covalent inhibitors, technologies more specific to the discovery of such inhibitors are needed. It is also necessary to address concerns regarding off-site reactivity and toxicity associated with covalent drugs. The particular focus of this proposal is to develop multiscale in silico covalent docking approaches by integrating robust quantum mechanical and molecular mechanical (QM/MM) potentials with the EnzyDock docking platform, thus enabling explicit modeling of multi-step chemical events and their energetic contributions during the search for docked poses. Current docking approaches lack the ability to perform covalent bond formation in a manner consistent with an inhibitor’s pre-covalent binding mode, as well as with the reaction transition state and covalently bonded mode. This wanting ability not only hampers the fundamental understanding of warhead-target reactivity, but also poses a technical barrier for advancing in silico docking strategies. Indeed, many existing docking programs offer the capacity to perform covalent docking but in an ad hoc fashion, as covalent docking was not considered from the design phase of the program development. With the goal to overcome this technical challenge, two specific aims are: AIM 1 is to develop a multiscale QM/MM/EnzyDock covalent docking method. In this development, EnzyDock will serve as the primary docking platform and robust semiempirical QM/MM potentials will be developed, calibrated for each specific warhead- target reaction type and combined with EnzyDock. In addition, we will develop and implement the generalized Born (GB) solvation model with the QM/MM potential framework to improve the energetics of QM/MM-docked poses. AIM 2 will apply the QM/MM/EnzyDock approach developed in AIM 1 to establish effective workflow for in silico screening of large covalent inhibitor databases. Specifically, two workflows will be explored: The first workflow is based on docking with a predefined covalent attachment site, which is employed in most covalent docking programs. The second workflow entails a dynamic approach to covalent docking, in which covalent attachment sites on the ligand are searched and determined on the fly during docking using cheminformatics analysis and spatial proximity with target residues in the binding pocket. In this research, the study will be limited to the warheads that react only with cysteine residues, while additional target residues, reaction types and warheads will be considered in future research to construct a more comprehensive warhead-target reaction database. Thus, the two workflows will be tested and benchmarked against known structures and kinetic/thermodynamic data of drug-Cys covalent systems. We expect that the methods developed in this project will make the in silico covalent inhibitor discovery more powerful and help understand electrophilic-target reactivity for use in warhead design and selection.