Analytical Electrostatics: Methods and Biological Applications.

分析静电学：方法和生物学应用。

基本信息

批准号：
7670426
负责人：
ALEXEY VLAD ONUFRIEV
金额：
$ 21.45万
依托单位：
VIRGINIA POLYTECHNIC INST AND ST UNIV
依托单位国家：
美国
项目类别：
财政年份：
2006
资助国家：
美国
起止时间：
2006-08-01 至 2011-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7670426
关键词：
Algorithms Amber Area Biological Biological Process Capsid Cereals Charge Communities Complex Computers DNA Development Electrostatics Elements Ensure Environment Equation Foundations Generations Goals Individual Ionic Strengths Ions Maps Membrane Methodology Methods Modeling Molecular Molecular Models Molecular Structure Morphologic artifacts Nucleosomes Physics Process Property Quantum Mechanics Reaction Research Personnel Ribosomes Scheme Science Shapes Simulate Solutions Solvents Specific qualifier value Speed Testing Theoretical model Time Viral Water base computerized tools drug discovery flexibility improved insight large scale simulation models and simulation molecular dynamics molecular mechanics molecular modeling molecular shape neglect novel programs protein complex simulation success tool

Algorithms Amber Area Biological Biological Process Capsid Cereals Charge Communities Complex Computers DNA Development Electrostatics Elements Ensure Environment Equation Foundations Generations Goals Individual Ionic Strengths Ions Maps Membrane Methodology Methods Modeling Molecular Molecular Models Molecular Structure Morphologic artifacts Nucleosomes Physics Process Property Quantum Mechanics Reaction Research Personnel Ribosomes Scheme Science Shapes Simulate Solutions Solvents Specific qualifier value Speed Testing Theoretical model Time Viral Water base computerized tools drug discovery flexibility improved insight large scale simulation models and simulation molecular dynamics molecular mechanics molecular modeling molecular shape neglect novel programs protein complex simulation success tool

展开

项目摘要

DESCRIPTION (provided by applicant): The broad goals of this project are the development of novel theoretical models and practical computational tools that will improve and facilitate the process of modeling and simulating bio-molecules. The new models will be based on "implicit solvent" approach in which individual water molecules and mobile solvent ions are replaced by a continuous medium with the average properties of the solvent. Currently, the "engine" of the methodology - responsible for the estimation of the key electrostatic interactions - is either the generalized Born (GB) or the Poisson Boltzmann model (PB). The GB model is computationally efficient, but lacks the critical accuracy of the fundamental, but computationally expensive PB approach. Within the proposed approach, exact solutions of the PB equation for typical molecular shapes will serve as the foundation for deriving computationally efficient, analytical models. The models will go beyond the current generation of the generalized Born (GB) models, in both accuracy and efficiency. New important features will be added, such as the ability to compute electrostatic potential at every point in space: potential generated by a bio-molecule is often a key determinant of its function. For large compounds, e.g. multi-protein complexes, viral capsids, the ribosome or the nucleosome, the proposed approach may be the only practical way to generate potential maps with the power of a desktop computer. Approaches specifically targeted to speed-up simulations based on the implicit solvent models will be developed. They will be based upon coarse-graining of the charge distribution and will not have the significant artifacts typical of the "standard" schemes in which interactions beyond a specified distance are neglected. The methods will yield at least a 10-fold increase in computational speed for large bio-molecular structures. The use of the new models will be expanded to applications where the GB model is currently not applied, but where computational speed and accuracy are critical, for example in quantum mechanics-molecular mechanics (QM-MM) calculations on bio-molecules. The fast, analytical models of solvation will become more dependable. The models will be used to gain insights into the molecular mechanism of enhanced flexibility of short DNA fragments. RELEVANCE: Molecular modeling and simulations are nowadays indispensable tools in biomedical science and the drug discovery process. The proposed methods will significantly enhance their accuracy and speed.

描述（由申请人提供）：该项目的广泛目标是开发新颖的理论模型和实用计算工具，这些工具将改善和促进建模和模拟生物分子的过程。新模型将基于“隐式溶剂”方法，在这种方法中，单个水分子和移动溶剂离子被具有溶剂平均特性的连续培养基取代。当前，该方法的“发动机”（负责估计关键静电相互作用的估计）是广义诞生（GB）或泊松玻尔兹曼模型（PB）。 GB模型在计算上是有效的，但缺乏基本且计算昂贵的PB方法的关键准确性。在提出的方法中，典型分子形状的PB方程的精确溶液将成为得出计算高效的分析模型的基础。这些模型将以准确性和效率超出当前一代的广义诞生（GB）模型。将添加新的重要功能，例如在空间中每个点计算静电电势的能力：生物分子产生的电位通常是其功能的关键决定因素。对于大化合物，例如多蛋白络合物，病毒式衣壳，核糖体或核体，所提出的方法可能是唯一使用台式计算机功能生成潜在地图的实际方法。将开发针对基于隐式溶剂模型的加速模拟的方法。它们将基于电荷分布的粗粒度，并且不会具有“标准”方案的典型伪像，在该方案中，其中忽略了指定距离以外的相互作用。对于大型生物分子结构，该方法将至少提高计算速度10倍。新模型的使用将扩展到当前未应用GB模型的应用程序，而是计算速度和准确性至关重要的应用程序，例如在生物分子上的量子力学 - 分子机械（QM-MM）计算中。溶剂化的快速分析模型将变得更加可靠。这些模型将用于洞悉短DNA片段柔韧性的分子机制。相关性：如今，分子建模和模拟是生物医学科学和药物发现过程中必不可少的工具。提出的方法将显着提高其准确性和速度。