A New Paradigm for Biomolecular Simulations

生物分子模拟的新范式

• 批准号: 7826315
• 负责人: JIALI GAO
• 金额: $ 45.42万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7826315
• 关键词: Active Sites; Address; Amber; Amino Acids; Area; Binding Sites; Biochemical Process; Biochemical Reaction; Biological; Biology; Biomedical Computing; Biopolymers; Charge; Chemicals; Computational Biology; Computer Simulation; Computer software; Data; Databases; Development; Diffusion; Drug Design; Electronics; Engineering; Environment; Enzymes; Evaluation; Flavoring; Future; Generations; Goals; Grant; Heart; Heating; Ligands; Mechanics; Methods; Modeling; Molecular; Molecular Structure; Performance; Phase; Potential Energy; Property; Protein Dynamics; Protein Engineering; Proteins; Relative (related person); Relaxation; Research; Series; Solutions; Solvents; Surface; System; Systems Biology; Techniques; Technology; Testing; Time; Transition Elements; Water; Work; aqueous; base; biological systems; computerized tools; density; design; dipole moment; electronic structure; functional group; improved; inhibitor/antagonist; intermolecular interaction; models and simulation; molecular dynamics; molecular mechanics; molecular orbital; molecular recognition; neglect; novel; polypeptide; programs; quantum; simulation; theories; tool; vaporization

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (06) Enabling Technologies and specific Challenge Topic, 06-GM-103: Development of predictive methods for molecular structure, recognition, and ligand interaction. Biomedical computation has become a powerful tool for understanding biological properties and function. The goal of computational biology is to make quantitative predictions of biochemical processes with chemical accuracy, i.e., to within one kcal/mol for absolute quantities and 1 kcal/mol for relative quantities. This is a daunting task in view of the complexity and size of biomolecular systems in a cellular environment, and we are still far from achieving this important goal. At the heart of molecular calculation is the potential energy function that describes intermolecular interactions in the system, and often it is the accuracy of the potential energy surface that determines the reliability of the simulation results. Although the current molecular mechanics force fields have been very successful in biomolecular modeling thanks to tremendous efforts in parameterization in the past forty years, the functional forms have hardly changed since the late 1960s. In this project, we propose to develop an electronic structure-based quantum mechanical force field, called the explicit polarization (X-Pol) potential, for obtaining the potential energy surfaces of biomolecular systems containing proteins. This represents a major paradigm change, going beyond the current classical models to the quantum mechanical realm of biomedical computing. The X-Pol potential is based on a hierarchy of approximations that can be developed using semiempirical or ab initio molecular orbital theory or density functional theory. The feasibility of such an explicit quantum mechanical force field has been demonstrated. The proposed research offers a great opportunity for a quantum leap in improving computational accuracy in biomedical simulation, and the computational tools developed in this work will be of general importance to protein engineering and inhibitor design. PUBLIC HEALT RELEVANCE: Biomedical computation has become a powerful tool for understanding biological properties and function. The research described in this proposal aims at the development of a novel computational approach that represents a paradigm change in the way that we describe intermolecular interactions and it is expected to significantly increase the accuracy of computational results. This in turn can help design inhibitors and engineer specialized proteins for biomedical and industrial applications.

描述（由申请人提供）：本申请涉及广泛的挑战领域（06）使能技术和特定的挑战主题，06-GM-103：分子结构、识别和配体相互作用预测方法的开发。生物医学计算已经成为理解生物特性和功能的有力工具。计算生物学的目标是以化学准确度对生化过程进行定量预测，即，绝对量在1 kcal/mol以内，相对量在1 kcal/mol以内。鉴于细胞环境中生物分子系统的复杂性和大小，这是一项艰巨的任务，我们仍然远远没有实现这一重要目标。分子计算的核心是描述系统中分子间相互作用的势能函数，通常是势能面的准确性决定了模拟结果的可靠性。虽然在过去的四十年里，由于在参数化方面的巨大努力，目前的分子力学力场在生物分子建模方面已经非常成功，但自20世纪60年代末以来，功能形式几乎没有改变。在这个项目中，我们建议开发一个基于电子结构的量子力学力场，称为显式极化（X-Pol）势，用于获得含有蛋白质的生物分子系统的势能面。这代表了一个重大的范式转变，超越了当前的经典模型，进入了生物医学计算的量子力学领域。X-Pol势是基于一系列近似，可以使用半经验或从头计算分子轨道理论或密度泛函理论来开发。这种明确的量子力学力场的可行性已得到证明。拟议的研究提供了一个很好的机会，在提高生物医学模拟的计算精度的量子飞跃，在这项工作中开发的计算工具将具有普遍的重要性，蛋白质工程和抑制剂的设计。 公共卫生相关性：生物医学计算已成为理解生物特性和功能的有力工具。本提案中描述的研究旨在开发一种新的计算方法，该方法代表了我们描述分子间相互作用的方式的范式变化，预计将显着提高计算结果的准确性。这反过来可以帮助设计抑制剂和工程专用蛋白质用于生物医学和工业应用。