Computational and theoretical characterization of ligand-protein binding mechanis

描述（由申请人提供）：本提案的目标是通过检查自由，中间和结合状态来建立更完整的配体-蛋白质识别图像，以揭示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、化学和医学等领域都起着重要的作用。探索结合途径和结合过程中的瞬时中间状态将有助于阐明包括结合、变构、诱导配合、门控控制结合和结合的自由能量学在内的机制，这些将指导分子设计。分子模拟在结合热力学和动力学研究中发挥着越来越重要的作用，在生物学和化学中都很重要。模拟与实验结合使用，整合数据，解释实验；然后参与设计具有首选亲和力和/或动力学特性的新分子。动力学数据也可以用作药物疗效和安全性的关键区分和预测因素。然而，真正的分子系统是相当复杂的，计算工具通常要么非常耗时，要么过于简化生物系统。因此，主要的动机是我们需要进一步开发新的计算方法，以有效和准确地模拟分子结合途径，以了解结合机制，溶剂效应和动力学行为。在前期研究成果和现有方法的指导下，提出了三个具体目标：1)开发和应用多尺度方法来模拟配体与蛋白质的结合，以了解结合机制和动力学行为；2)研究水和自由能景观在结合过程中的作用；3)适应和应用新方法，将实验整合到肽-蛋白结合中，研究蛋白质功能，辅助肽设计。该方法是创新的，它涉及带来新的方法突破，使结合途径的现实建模和扩展分子识别的经典观点。本研究为我们研究结合过程、自由能面和溶剂效应提供了计算工具，揭示了分子结合的基本机制，具有重要意义。

DESCRIPTION (provided by applicant): 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 o 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.