COMPUTER SIMULATION THEORY OF GLOBULAR PROTEIN DYNAMICS

球状蛋白质动力学的计算机模拟理论

• 批准号: 6385656
• 负责人: JEFFREY SKOLNICK
• 金额: $ 20.75万
• 依托单位: DONALD DANFORTH PLANT SCIENCE CENTER
• 依托单位国家: 美国
• 财政年份: 1986
• 资助国家: 美国
• 起止时间: 1986-12-01 至 2002-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6385656
• 关键词: computer program /software; computer simulation; conformation; globular protein; method development; model design /development; molecular dynamics; physical model; protein folding; protein sequence; protein structure

One of the most important unsolved problems of computational biology is the inability to predict the three-dimensional structure of a protein from its amino acid sequence. In practice, the solution to the protein folding problem demands that two interrelated problems be simultaneously addressed. Potentials that recognize the native state from the myriad of misfolded conformations partly surmounting both problems. A means of secondary and tertiary restraint information to funnel the molecule towards native-like regions. However, such approaches typically generate two to three low energy topologies. Thus, we propose to develop improved protocols to predict secondary structure and tertiary restraints from multiple sequence information. Furthermore, since native state topology generation and section is also crucially dependent on the non-restraint, empirical contributions to the potential, these terms must also be improved. In particular, side chain burial will be more adequately described and local sequence alignments will be employed to develop much more sensitive pair potentials. Furthermore, once low energy topologies are generated, self-consistent tertiary restraints will be derived so that less distorted native-like conformations will be generated. This should enhance the energetic selectivity for native-like as well as by developing computationally more efficient reduced protein sampling techniques as well as by developing computationally more efficient reduced protein models. To establish the range of validity of this approach to tertiary structure prediction, application will be made to large number of sequences of known as well as unknown structure. Significant, independent testing of this algorithm will be done by participating in blind prediction, contests, including CASP3, by making blind predictions of other proteins, and by disseminating all software to other investigators over the Internet.

计算生物学最重要的未解决问题之一是无法从氨基酸序列预测蛋白质的三维结构。在实践中，蛋白质折叠问题的解决方案需要同时解决两个相互关联的问题。从无数错误折叠的构象中识别天然状态的潜力部分克服了这两个问题。二级和三级约束信息的手段，以漏斗分子向天然样区域。然而，这样的方法通常产生两到三个低能量拓扑。因此，我们建议开发改进的协议来预测二级结构和三级限制从多个序列信息。此外，由于原生状态拓扑生成和截面也关键地依赖于对势的非约束、经验贡献，因此这些项也必须改进。特别是，侧链掩埋将得到更充分的描述和本地序列比对将开发更敏感的对电位。此外，一旦产生低能量拓扑结构，自洽的三级约束将被导出，从而产生较少扭曲的天然样构象。这应该通过开发计算上更有效的简化蛋白质采样技术以及开发计算上更有效的简化蛋白质模型来增强对天然样蛋白的能量选择性。为了建立这种方法的有效性范围的三级结构预测，应用程序将作出大量的序列已知以及未知的结构。该算法的重要独立测试将通过参与盲预测、竞赛（包括CASP3）、对其他蛋白质进行盲预测以及通过互联网向其他研究者传播所有软件来完成。