Theory and Modeling of Noncovalent Binding

非共价结合的理论和建模

• 批准号: 8279313
• 负责人: MICHAEL K. GILSON
• 金额: $ 37.11万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2014-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8279313
• 关键词: Affinity; Binding; Binding Proteins; Binding Sites; Biology; Biophysics; Case Study; Catalysis; Chemicals; Computer Simulation; Computer software; Development; Drug or Chemical; Engineering; Entropy; Enzymes; Equation; Equilibrium; Evaluation; FDA approved; Free Energy; Generations; Goals; Grant; Guidelines; Immune system; Ligand Binding; Ligands; Mechanical Stress; Medical; Medicine; Metabolism; Methods; Modeling; Molecular; Molecular Conformation; Motion; Mutation; Pattern; Pharmaceutical Preparations; Physics; Process; Protein Binding; Protein Engineering; Proteins; RGD (sequence); Regulation; Research; Research Personnel; Scientist; Shapes; Signal Transduction; Site; Solvents; Speed; Stress; Structure; System; Testing; Therapeutic; Time; Work; biological systems; design; engineering design; improved; insight; molecular recognition; public health relevance; receptor; receptor binding; simulation; small molecule; software development; theories; tool

DESCRIPTION (provided by applicant): The proposed research, which is purely theoretical and computational, has three main parts, all focused on aspects of the phenomenon of molecular recognition, which is of basic and practical importance in biology and medicine. The first part concerns miniature receptor molecules, called hosts, which are used today to stabilize and deliver many drugs and which also show promise as medications in their own right. We plan to provide other scientists with new, tested software to help them design these miniature receptors and thereby speed the development of new medications. We also plan to carry out simulations of these molecules in order to develop a better understanding of how they work and also to gain insight into how larger receptors, such as many proteins, bind drugs. The second part is to study the changes in entropy that occur when molecules bind. In recent work, we have found that changes in entropy associated with the motions of receptors and the molecules they bind (ligands) can have a surprisingly strong influence on how tightly they bind each other. However, we do not yet understand these entropy changes well enough to make them work in our favor when designing tight-binding receptors and ligands. We plan to further develop our method of computing these entropy changes from computer simulations, and then use the method to develop a better understanding of them. For example, we would like to be able to predict when modifying a ligand to make it more rigid, and therefore lower in entropy, will increase its affinity. In addition, we plan to incorporate the new entropy calculations into software for computing binding affinities which we hope will help researchers design new drugs. The third part is to develop a new idea of applying the concept of stress to molecular biophysics. Materials scientists have come up with equations for computing the stress in a material from an atomistic computer simulation, and we think these equations can tell us something useful about how hosts, proteins and other molecules work. For one thing, we hypothesize that if receptor- ligand binding produces localized stress, then modifying the ligand to reduce this stress might increase the binding affinity. Thus, computing stress might help with the design of tight-binding ligands. We also hypothesize that, when a ligand binds an allosteric protein, a protein whose conformation shifts on binding, the mechanism of the shape change involves propagation of a wave of stress from the binding site. If we can understand how proteins change conformation, this would help us to re-engineer them for medical and industrial uses. PUBLIC HEALTH RELEVANCE: This project applies chemical theory and computer modeling to the phenomenon of molecular recognition. Our overall goal is to develop a better understanding of what makes specific molecules bind each other, and to incorporate this understanding into software that will be useful in protein engineering and the design of new medications.

描述（由申请人提供）：拟议的研究，这是纯粹的理论和计算，有三个主要部分，都集中在分子识别现象的方面，这是生物学和医学的基础和实践的重要性。第一部分涉及微型受体分子，称为宿主，今天用于稳定和递送许多药物，并且也显示出作为药物本身的前景。我们计划为其他科学家提供新的、经过测试的软件，帮助他们设计这些微型受体，从而加快新药的开发。我们还计划对这些分子进行模拟，以便更好地了解它们如何工作，并深入了解更大的受体（如许多蛋白质）如何结合药物。第二部分是研究分子结合时熵的变化。在最近的工作中，我们发现与受体及其结合的分子（配体）的运动相关的熵的变化可以对它们相互结合的紧密程度产生令人惊讶的强烈影响。然而，我们还没有足够好地理解这些熵变，使它们在设计紧密结合的受体和配体时对我们有利。我们计划进一步发展我们的方法来计算这些熵的变化，从计算机模拟，然后使用该方法来开发一个更好的理解他们。例如，我们希望能够预测何时修饰配体使其更刚性，从而降低熵，将增加其亲和力。此外，我们计划将新的熵计算纳入计算结合亲和力的软件中，我们希望这将有助于研究人员设计新药。第三部分提出了将应激概念应用于分子生物物理学的新思路。材料科学家已经提出了计算原子计算机模拟材料中应力的方程，我们认为这些方程可以告诉我们一些关于宿主、蛋白质和其他分子如何工作的有用信息。首先，我们假设如果受体-配体结合产生局部应力，那么修饰配体以减少这种应力可能会增加结合亲和力。因此，计算应力可能有助于设计紧密结合的配体。我们还假设，当配体结合变构蛋白质时，这种蛋白质的构象在结合时发生变化，形状变化的机制涉及从结合位点传播应力波。如果我们能够理解蛋白质如何改变构象，这将有助于我们重新设计它们用于医疗和工业用途。 公共卫生相关性：该项目将化学理论和计算机建模应用于分子识别现象。我们的总体目标是更好地理解是什么使特定分子相互结合，并将这种理解纳入软件中，这将有助于蛋白质工程和新药设计。