Protein Structure Prediction Using First Principles

描述(申请人提供)：这个项目的总体目标是提高我们对蛋白质的第一原理结构预测的理解。基于我们先前关于Astro-Fold的研究工作(Klepeis和Floudas，2003c)(见C.2节图1)，拟议的研究旨在开发一个增强的蛋白质结构预测框架。该框架包括(A)用于螺旋链段预测的自由能计算，(B)用于预测β链和β片层拓扑的组合优化方法，(C)用于预测螺旋间三次接触的新建议方法，(D)用于一般情况的新建议方法 (E)根据(a-d)中的预测推导出改进的距离约束，以及提出的新的基于优化的迭代方法，(E)通过ABB确定性全局优化方法和扭角动力学产生低能三级蛋白质结构的系综，以及(F)使用基于高和/或中分辨率诱骗的距离相关力场从低能蛋白质结构的系综中选择预测的三级蛋白质结构的新的拟议方法。我们提出了以下四个具体目标： 具体目标1：研究和开发一种新的方法来预测a-螺旋蛋白和a/b蛋白的螺旋间三级接触。 具体目标2：研究和开发一种新的优化方法来预测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，用于生成用于三级结构预测的附加和改进的距离约束。 具体目标4：研究和开发一个强大的力场，它将能够从搜索三级蛋白质结构产生的高分辨率和/或中分辨率诱饵中区分折叠结构。研究了力保持发展的稳健优化方法。研究、测试和验证整体提出的蛋白质结构预测增强框架。 利用第一性原理预测蛋白质结构不仅对计算生物学和化学具有重要意义，而且对于促进对直接影响药物发现的蛋白质-蛋白质和蛋白质-多肽相互作用的理解也具有重要意义。球蛋白和膜蛋白蛋白质结构预测方法的改进将导致新药物的开发，这将有利于公众的健康。

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.