Protein Structure Prediction Using First Principles

使用第一原理预测蛋白质结构

• 批准号: 7683007
• 负责人: Christodoulos Achilleus Floudas
• 金额: $ 24.54万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-05-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7683007
• 关键词: Address; Amino Acids; Arts; Benchmarking; Binding; CASP7 gene; Chemistry; Computational Biology; Derivation procedure; Development; Event; Free Energy; Generations; Lead; Membrane Proteins; Methods; Modeling; Peptides; Pharmaceutical Preparations; Proteins; Public Health; Research; Resolution; Structure; Tertiary Protein Structure; Testing; Uncertainty; Work; base; beta pleated sheet; blind; combinatorial; drug discovery; improved; novel; novel strategies; protein structure; protein structure prediction; public health relevance; restraint; stem

DESCRIPTION (provided by applicant): The overall aim of this project is to improve our understanding of first principles structure prediction of proteins. Based upon our earlier research work on the Astro-Fold (Klepeis and Floudas, 2003c) (see Figure 1 in section C.2), the proposed research is directed towards the development of an enhanced framework for protein structure prediction. This framework consists of (a) free energy calculations for helical segment prediction, (b) a combinatorial optimization approach for the prediction of beta strands and beta sheet topology, (c) a new proposed approach for predicting inter-helical tertiary contacts, (d) a new proposed approach for general residue-residue contact prediction, (e) the derivation of improved distance restraints from predictions in (a-d), and a new proposed optimization-based iterative approach, (e) the generation of an ensemble of low energy tertiary protein structures via the aBB deterministic global optimization approach and torsional angle dynamics, and (f) a new proposed approach for the selection of the predicted tertiary protein structure, from the ensemble of low energy protein structures, using a distance dependent force field developed based on high and/or medium resolution decoys. We put forward the following four specific aims: Specific Aim 1: Investigate and develop a novel approach for the prediction of inter-helical tertiary contacts for a-helical proteins, and a/b proteins. Specific Aim 2: Investigate and develop a novel optimization method for the prediction of residue-residue contacts in alpha helical, alpha/beta and beta proteins. Specific Aim 3: Investigate a new iterative optimization-based approach for the generation of additional and improved distance restraints for the tertiary structure prediction. Specific Aim 4: Study and develop a powerful force field which will be able to discriminate the folded structure among high resolution and/or medium resolution decoys generated from the search of tertiary protein structures. Study a robust optimization approach for the force held development. Investigate, test, and validate the overall proposed enhanced framework for protein structure prediction. PUBLIC HEALTH RELEVANCE The protein structure prediction using first principles is not only of fundamental importance to computational biology and chemistry, but also of major importance for advancing the understanding of protein-protein and protein-peptide interactions which have a direct impact on drug discovery. Improvements of predictive methods for the elucidation of protein structures for globular and membrane proteins will lead into development of novel drugs which will benefit the public health.

描述（由申请人提供）：该项目的总体目标是提高我们对蛋白质第一原理结构预测的理解。基于我们早期对 Astro-Fold 的研究工作（Klepeis 和 Floudas，2003c）（参见 C.2 节中的图 1），拟议的研究旨在开发用于蛋白质结构预测的增强框架。该框架包括（a）用于螺旋段预测的自由能计算，（b）用于预测β链和β片拓扑的组合优化方法，（c）用于预测螺旋间三级接触的新提出的方法，（d） ）一种新的通用方法 残基-残基接触预测，(e) 从 (a-d) 中的预测导出改进的距离限制，以及新提出的基于优化的迭代方法，(e) 通过 aBB 确定性生成低能量三级蛋白质结构的集合全局优化方法和扭转角动力学，以及（f）一种新提出的方法，用于使用距离相关力从低能蛋白质结构的集合中选择预测的三级蛋白质结构基于高分辨率和/或中分辨率诱饵开发的场。我们提出以下四个具体目标： 具体目标 1：研究并开发一种新方法来预测 a-螺旋蛋白和 a/b 蛋白的螺旋间三级接触。 具体目标 2：研究并开发一种新的优化方法，用于预测 α 螺旋、α/β 和 β 蛋白中的残基-残基接触。 具体目标 3：研究一种新的基于迭代优化的方法，为三级结构预测生成附加和改进的距离约束。 具体目标 4：研究和开发强大的力场，能够区分从三级蛋白质结构搜索中生成的高分辨率和/或中等分辨率诱饵中的折叠结构。研究强制开发的稳健优化方法。研究、测试和验证总体提出的蛋白质结构预测增强框架。 公共健康相关性使用第一原理的蛋白质结构预测不仅对计算生物学和化学具有根本重要性，而且对于增进对蛋白质-蛋白质和蛋白质-肽相互作用的理解也非常重要，这些相互作用对药物发现有直接影响。阐明球状蛋白和膜蛋白结构的预测方法的改进将导致新药物的开发，从而造福公众健康。