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: 6945807
• 负责人: JEFFREY SKOLNICK
• 金额: $ 0.51万
• 依托单位: STATE UNIVERSITY OF NEW YORK AT BUFFALO
• 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 2006-01-09
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6945807
• 关键词: Caenorhabditis elegans; Drosophilidae; Escherichia coli; Mycoplasma; Saccharomyces cerevisiae; active sites; computer program /software; computer simulation; conformation; globular protein; method development; model design /development; molecular dynamics; physical model; protein folding; protein sequence; protein structure

DESCRIPTION (provided by applicant): With the genome sequencing projects providing a deluge of sequences, to utilize this information requires knowledge of the function of all the proteins in a given genome. Because biochemical function is determined by a protein's active site structure, protein structures are becoming essential tools for genome functional annotation. This has spurred structural genomics approaches that aim to develop high-throughput protein structure determination methods. Structure prediction is important not only for target selection in structural genomics but also for genome scale functional prediction. The goal of this project is to improve our TOUCHSTONE tertiary structure prediction algorithm that employs predicted secondary and tertiary restraints by addressing the key issues in protein folding: the lack of potentials that recognize the native state from the myriad of protein like, misfolded structures and the lack effective search conformational algorithms, especially for proteins over 150 residues. The Specific Aims designed to address these problems are: (1) The comprehensive native structure prediction of a representative set of all proteins with solved structures less than 201 residues in length (no pair with more than 35% sequence identity; at present 2282 proteins) will be done. This comprehensive test, made possible due to our new 4,000 processor PC cluster, will establish the full range of validity of TOUCHSTONE and provide a benchmark against which subsequent improvements can be assessed. (2). The model will be reparameterized based on the results from and use of the comprehensive set of decoys provided by (1). Each term in the potential will be examined, relative weights adjusted and where necessary extended or rederived. Due to the large number of native and decoy structures, the greatly improved statistics will allow for the derivation of terms in the potential, (e.g. 3-body secondary structure dependent pair potentials) that was not previously possible. (3). Improved protocols to predict the tertiary restraints that permit the folding of complex topologies will be developed. (4). Methods to select native like structures will be improved, e.g. by a series of simulations where previously generated clustered structures are used to derive restraints for subsequent simulations. (4). The prediction of tertiary structure of all small (<201 residues) proteins in the M. genitalium, E. coli, S. cerevisiae, D.. melanogaster C. elegans, and human genomes will be done. (5). The algorithm will be the object of continual independent testing including participation in future CASPs. The overall goal is to range of validity of our ab initio folding algorithms and to provide significant improvements in the state of the art of tertiary structure prediction.

描述（由申请人提供）：基因组测序项目提供了大量的序列，要利用这些信息，需要了解给定基因组中所有蛋白质的功能。由于生物化学功能是由蛋白质的活性位点结构决定的，蛋白质结构正成为基因组功能注释的重要工具。这刺激了旨在开发高通量蛋白质结构测定方法的结构基因组学方法。结构预测不仅对结构基因组学的靶点选择具有重要意义，而且对基因组尺度的功能预测也具有重要意义。该项目的目标是通过解决蛋白质折叠中的关键问题来改进我们的TOUCHSTONE三级结构预测算法，该算法采用预测的二级和三级约束：缺乏从无数蛋白质样，错误折叠结构中识别天然状态的潜力，以及缺乏有效的搜索构象算法，特别是对于超过150个残基的蛋白质。解决这些问题的具体目标是：(1)对所有已解结构长度小于201个残基的具有代表性的一组蛋白质（没有一对序列同源性超过35%，目前有2282个蛋白质）进行全面的天然结构预测。这个全面的测试，由于我们新的4000处理器PC集群而成为可能，将建立TOUCHSTONE的全面有效性，并提供一个可以评估后续改进的基准。(2)。模型将根据(1)提供的综合诱饵集的结果和使用进行重新参数化。将检查潜力中的每一项，调整相对权重，并在必要时延长或重新推导。由于大量的原生结构和诱饵结构，大大改进的统计将允许在势中推导项（例如3体二级结构依赖的对势），这在以前是不可能的。(3)。将开发改进的协议来预测允许复杂拓扑折叠的三级约束。(4)。选择原生类结构的方法将得到改进，例如，通过一系列模拟，使用先前生成的簇状结构来推导后续模拟的约束。(4)。生殖支原体、大肠杆菌、酿酒链球菌、大肠杆菌等细菌中所有小（<201残基）蛋白的三级结构预测黑腹线虫、秀丽隐杆线虫和人类基因组将完成。(5)。该算法将成为持续独立测试的对象，包括参与未来的casp。总体目标是扩大我们的从头算折叠算法的有效性范围，并在三级结构预测方面提供重大改进。