面向结构预测的蛋白质分子力场发展

项目名称： 面向结构预测的蛋白质分子力场发展

项目编号： No.21203004

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 物理化学

项目作者： 蒋帆

作者单位： 北京大学

项目金额： 18万元

中文摘要： 理论上，一个好的分子力场应该能够进行蛋白质的从头折叠模拟，给出正确的天然态结构和热力学稳定性。然而，与蛋白质结构预测中常用的统计势相比，当前力场模拟的效率依然较低，即使消耗大量计算资源也不一定能得到准确的结果。我们的前期工作利用已知的蛋白质结构数据发展了与粗粒水模型结合的分子力场PACE，最近又优化的现有的OPLS全原子分子力场。这些新力场能够折叠有不同二级结构的多肽和迷你蛋白到实验结构。本项目在此基础上，探索建立一个高效的结合GB隐式溶剂模型的联合原子分子力场。力场参数化的目标包括（1）显式溶剂中的模拟结果（2）晶体结构统计得到的残基的局部构象偏好（3）正确的蛋白质从头折叠模拟（4）从若干诱饵结构中准确的识别出天然态结构。并研究将新方法运用到实际的蛋白质结构的从头预测和同源建模的结构优化上。

中文关键词： 蛋白质折叠；残基特异性力场；结构预测；分子动力学；统计势

英文摘要： In theory, a good force field should successfully achieve ab initio protein folding. However, compared with statistical potentials usually used in protein structure prediction practices,current force field simulations still lack efficiency. Accurrate results can not be guaranteed even by consumming lots of computational resouces. Recently, we developed an united-atom force field coupled with coarse-grained water model, partly based on the known protein structures. More recently, we also improved the OPLS-AA force field using similar strategy. Our newly developed force fields can fold peptides and miniproteins with various secondary structures to their native structures. In this project, based on these preliminary studies, a new united-atom force field coupled with GB implicit solvent model will be estabilished. The targets for the force field paraemterization include (1) simulation results using explit water model (2) local conformational preference of amino acid residues from statistical analysis of protein structures (3) correctly ab initio protein folding simulations (4) accurate discrimination of native structures from many decoys. The new force field will be applied in real practices of template-free protein structure prediction and refinement of homology models.

英文关键词： protein folding；residue-specific force field；structure prediction；molecular dynamics；statistical potential