Computational and theoretical characterization of ligand-protein binding mechanis

项目总结/摘要 这项提案的目标是建立一个更完整的配体-蛋白质的图片 通过研究自由态、中间态和束缚态， 结合机制和动力学行为的原因和时间。 非共价分子识别在生物学、化学和生物技术中起着至关重要的作用。 药探索结合途径和过程中的瞬态中间态 结合将有助于阐明包括结合、变构、诱导适应、门控 控制协会，和结合的自由能，这将在以后引导分子 的设计.分子模拟在研究结合过程中发挥着越来越重要的作用 热力学和动力学，在生物学和化学中都很重要。用于 仿真与实验相结合，综合数据，解释实验; 然后有助于设计具有优选亲和力和/或动力学的新分子 特性.动力学数据也可以用作关键的区分和预测因素， 药物疗效和安全性。然而，真实的分子系统是相当复杂的， 计算工具通常要么非常耗时，要么过于简化生物学模型。 系统因此，主要的动机是，我们需要项目，以进一步开发新的 计算方法，既有效又准确地模拟分子缔合 途径，以了解结合机制，溶剂效应和动力学 行为根据我们的初步结果和现有方法， 小组，提出了三个具体目标：1）开发和应用多尺度方法， 建立配体-蛋白质结合模型，以了解结合机制和动力学 行为; 2）调查沃茨和自由能景观在结合中的作用 3）适应和应用新的方法，并将实验整合到肽- 蛋白质结合研究蛋白质功能和辅助肽设计。该方法是 创新，它涉及带来新的方法上的突破，使现实的 结合途径的建模和扩展分子的经典观点 识别.这项研究具有重要意义，因为它提供了计算 我们研究结合过程、自由能表面和溶剂效应的工具， 揭示了分子缔合的基本机制。

Project Summary/Abstract The goal of this proposal is to build a more complete picture of ligand-protein recognition by examining free, intermediate and bound states in order to reveal the why and when of binding mechanisms and kinetic behavior. Non-covalent molecular recognition plays a crucial role in biology, chemistry and medicine. Exploring binding pathways and the transient intermediate states during binding will help elucidate mechanisms that include binding, allostery, induced fit, gated control associations, and the free energetics of binding, which will later guide molecular designs. Molecular simulations play an increasing role in studying binding thermodynamics and kinetics, important in both biology and chemistry. Used in combination with experiments, simulations integrate data and interpret experiments; then contribute to the design of novel molecules with preferred affinities and/or kinetic properties. Kinetic data also can be used as a critical differentiator and predictor for drug efficacy and safety. However, real molecular systems are quite complicated, and computational tools usually are either very time-consuming or over-simplify a biological system. Therefore, the major motivation is that we need projects to further develop new computational methods to both efficiently and accurately model molecular association pathways in order to understand the binding mechanisms, solvent effects and kinetic behavior. Guided by strong preliminary results and existing methods developed by our group, three specific aims are proposed: 1) Develop and apply multi-scale methods to model ligand-protein binding in order to understand binding mechanisms and kinetic behavior; 2) Investigate the role of waters and free energy landscape in binding processes; 3) Adapt and apply the new methods and integrate experiments to peptide- protein binding to study protein function and assist peptide design. The approach is innovative that it involves bringing new methodological breakthroughs to enable realistic modeling of binding pathways and expanding the classical view of molecular recognition. The proposed research is significant, because it provides computational tools for us to study binding processes, free energy surfaces and solvent effects, and reveals fundamental mechanisms of molecular association.