Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA.
J Comput Chem. 2011 Feb;32(3):396-405. doi: 10.1002/jcc.21626. Epub 2010 Aug 23.
We adapted existing polymer growth strategies for equilibrium sampling of peptides described by modern atomistic forcefields with a simple uniform dielectric solvent. The main novel feature of our approach is the use of precalculated statistical libraries of molecular fragments. A molecule is sampled by combining fragment configurations-of single residues in this study-which are stored in the libraries. Ensembles generated from the independent libraries are reweighted to conform with the Boltzmann-factor distribution of the forcefield describing the full molecule. In this way, high-quality equilibrium sampling of small peptides (4-8 residues) typically requires less than one hour of single-processor wallclock time and can be significantly faster than Langevin simulations. Furthermore, approximate, clash-free ensembles can be generated for larger peptides (up to 32 residues in this study) in less than a minute of single-processor computing. We discuss possible applications of our growth procedure to free energy calculation, fragment assembly protein-structure prediction protocols, and to "multi-resolution" sampling.
我们采用了现有的聚合物生长策略,以简单的均匀介电溶剂对现代原子力场描述的肽进行平衡采样。我们方法的主要新颖之处在于使用预先计算的分子片段统计库。通过组合存储在库中的单个残基的片段构型来对分子进行采样。从独立库中生成的集合通过重新加权以符合描述整个分子的力场的玻尔兹曼因子分布来进行调整。通过这种方式,对小肽(4-8 个残基)进行高质量的平衡采样通常需要不到一个小时的单处理器挂钟时间,并且可以比 Langevin 模拟快得多。此外,对于更大的肽(在本研究中最多 32 个残基),可以在不到一分钟的单处理器计算时间内生成近似无冲突的集合。我们讨论了我们的生长过程在自由能计算、片段组装蛋白质结构预测协议以及“多分辨率”采样中的可能应用。