Computational and theoretical characterization of ligand-protein binding mechanis

配体-蛋白质结合机制的计算和理论表征

• 批准号: 8615026
• 负责人: Chia-en Chang
• 金额: $ 27.06万
• 依托单位: UNIVERSITY OF CALIFORNIA RIVERSIDE
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-30 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8615026
• 关键词: Affinity; Automobile Driving; Behavior; Binding; Binding Proteins; Biology; CDK2 gene; Cell physiology; Cereals; Chemicals; Chemistry; Computer Simulation; Computing Methodologies; Data; Development; Disease; Dissociation; Drug Design; Entropy; Free Association; Free Energy; Functional disorder; Goals; Kinetics; Knowledge; Life; Ligand Binding; Ligands; Link; MAP Kinase Gene; MAPK14 gene; Mediating; Medicine; Methods; Modeling; Molecular; Molecular Models; Motivation; Movement; Pathway interactions; Peptides; Pharmaceutical Preparations; Phase; Phosphopeptides; Play; Population; Process; Property; Protein Binding; Protein Conformation; Protein Dynamics; Proteins; Relative (related person); Research; Role; Safety; Solvents; Structure; Surface; System; Testing; Thermodynamics; Time; Water; Work; base; biological systems; computerized tools; cost; design; drug candidate; drug discovery; drug efficacy; flexibility; functional group; inhibitor/antagonist; innovation; molecular dynamics; molecular modeling; molecular recognition; novel; protein aminoacid sequence; protein function; protein protein interaction; public health relevance; research study; simulation; theories; tool

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.

项目摘要/摘要 这项提议的目标是建立一个更完整的配基-蛋白质图景 通过检查自由态、中间态和束缚态来识别，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、化学和生物科学中发挥着至关重要的作用 医药。探索结合途径和瞬时中间状态 结合将有助于阐明包括结合、变构、诱导配合、门控在内的机制 控制缔合，以及结合的自由能量学，这将在以后指导分子 设计。分子模拟在研究结合方面发挥着越来越大的作用 热力学和动力学，在生物学和化学中都很重要。用于 与实验相结合，模拟整合数据，解释实验； 然后有助于设计具有首选亲和力和/或动力学的新型分子 属性。动力学数据也可以作为关键的区分指标和预测指标 药物疗效和安全性。然而，真正的分子系统是相当复杂的，而且 计算工具通常要么非常耗时，要么过度简化了生物 系统。因此，主要的动机是我们需要项目来进一步开发新的 既高效又准确模拟分子缔合的计算方法 途径以了解结合机制、溶剂效应和动力学 行为。以强大的初步结果和我们开发的现有方法为指导 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)调查水域和自由能景观在结合中的作用 3)新方法的适应和应用，并对多肽进行综合实验。 蛋白质结合，用于研究蛋白质功能和辅助多肽设计。方法是 创新，包括带来新的方法突破，以实现现实 结合途径模型与分子经典观点的拓展 承认。这项拟议的研究意义重大，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，以及 揭示了分子缔合的基本机制。