I-TASSER based atomic-level protein structure prediction

基于 I-TASSER 的原子级蛋白质结构预测

• 批准号: 8247020
• 负责人: Yang Zhang
• 金额: $ 25.59万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2013-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8247020
• 关键词: Algorithms; Amino Acid Sequence; Amino Acids; Attention; Benchmarking; Biochemical; Biological Process; Categories; Computer Simulation; Computers; Development; Distant; Electrostatics; Employment; Goals; Homologous Protein; Hydrogen Bonding; Length; Ligands; Membrane Proteins; Methodology; Modeling; Mutation; Phase; Plant Roots; Preclinical Drug Evaluation; Procedures; Proteins; Research; Research Design; Resolution; Resource Sharing; Rest; Screening procedure; Side; Structure; System; Tertiary Protein Structure; Testing; Training; Vertebral column; Weight; base; improved; knowledge base; programs; protein folding; protein structure; protein structure prediction; research study; simulation; user-friendly; virtual; web site

DESCRIPTION (provided by applicant): Project Summary: Recent years' CASP experiments have seen significant progress on computer-based protein tertiary structure prediction. The state-of-the-art algorithms, such as TASSER, can generate correct folds for 2/3 of single domain proteins without using homologous templates. Most of the models are of low resolution with a root mean square deviation (RMSD) 3-6 Angstroms, which may be useful for protein topology analysis and some level of biological function inference. However, such models are not suitable for reliable ligand screening. The proposed research seeks to develop new methodologies for the atomic-level high-resolution protein structure modeling. The specific aims are: (1) development of a new algorithm, atom-TASSER, for atomic-level protein structure modeling; (2) development of a two-level composite potential for both the low-resolution topology construction and the high-resolution refinement; (3) force field optimization in both structure and sequence phase spaces; (4) large-scale benchmarking of atom-TASSER algorithm. Overall, these studies are designed to extend the range of validity of the reduced modeling approaches, and provide significant improvements in the state-of-the-art of tertiary structure prediction. The goal is to push up the level of accuracy of computer-based modeling, especially for the distant/weakly homologous proteins, so that they can be of real use to new drug screening and biochemical functional inference.

项目内容：近年来，CASP实验在基于计算机的蛋白质三级结构预测方面取得了重大进展。最先进的算法，如TASSER，可以在不使用同源模板的情况下生成2/3的单结构域蛋白的正确折叠。大多数型号都很低 分辨率与均方根偏差（RMSD）3-6埃，这可能是有用的蛋白质拓扑结构分析和一定程度的生物功能推断。然而，这样的模型不适合可靠的配体筛选。该研究旨在为原子级高分辨率蛋白质结构建模开发新的方法。具体目标是：（1）开发了一种新的蛋白质原子级结构建模算法atom-TASSER;（2）开发了一种用于低分辨率拓扑结构构建和高分辨率精细化的两级复合势;（3）结构和序列相空间的力场优化;（4）atom-TASSER算法的大规模基准测试。总的来说，这些研究旨在扩大简化建模方法的有效性范围，并在最先进的三级结构预测中提供显着的改进。其目标是提高基于计算机的建模的准确性，特别是对于远/弱同源蛋白质，以便它们可以真实的用于 新药筛选和生化功能推断。