Prioritized Assembly in Protein Conformational Search

蛋白质构象搜索中的优先组装

• 批准号: 7056379
• 负责人: KAIZHI YUE
• 金额: $ 13.02万
• 依托单位: CONFORMATIONAL SEARCH SOLUTIONS
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-05-28 至 2009-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7056379
• 关键词: automated data processing; bioenergetics; bioinformatics; biophysics; chemical registry /resource; computational biology; computer simulation; mathematical model; method development; molecular assembly /self assembly; molecular dynamics; protein folding

DESCRIPTION (provided by applicant): An efficient and effective conformational search method is essential for solving the computational protein folding problem. Prevalent conformational search methods are fast but incomplete. Proposed here is an exhaustive enumeration-based search method that combines a focus on the most promising search paths with a complete coverage of a discretized conformational space. The search is a prioritized building-up process: Structural templates of low energy are generated for short segments of the chain. Structural elements, either templates or individual residues, are added to a growing conformation one at a time. The addition of a structural element is prioritized on its energetical contribution to the conformation as a whole. Simple templates such as tight turns, helices or strands form packing clusters such as hairpins and beta-sheets. A finished conformation is often the assembly of packing clusters. Search efficiency is achieved by pruning unpromising search branches at each building-up step. In phase I, the architecture of prioritized assembly-based search has been implemented, demonstrating the feasibility of the approach. Phase II will develop algorithms for computing tight lower bounds of conformational energy, which are crucial for effective branch-and-bound search, and for integrating exhaustive enumeration with minimization. Phase III, with peer-to-peer parallelization, will develop a comprehensive conformational search program for computational protein folding.

描述（由申请人提供）：高效和有效的构象搜索方法对于解决计算蛋白质折叠问题至关重要。流行的构象搜索方法是快速的，但不完整。这里提出的是一个详尽的枚举为基础的搜索方法，结合了最有前途的搜索路径的离散化构象空间的完整覆盖的重点。搜索是一个优先级的建立过程：为链的短段生成低能量的结构模板。结构元素，无论是模板或单个残基，被添加到一个不断增长的构象一次一个。结构元素的添加优先考虑其对整体构象的能量贡献。简单的模板，如紧转弯，螺旋或股形成包装集群，如发夹和β-片。一个完成的构象往往是组装集群。搜索效率是通过在每个建立步骤修剪无用的搜索分支。 在第一阶段，优先级汇编搜索的架构已经实现，证明了该方法的可行性。第二阶段将开发用于计算构象能量的严格下限的算法，这对于有效的分支定界搜索以及将穷举与最小化相结合至关重要。第三阶段，对等并行化，将开发一个全面的构象搜索程序计算蛋白质折叠。