使用基于文库的聚合物生长方法对全原子肽进行快速取样
Rapid sampling of all-atom peptides using a library-based polymer-growth approach
摘要：
我们适应现有的聚合物生长策略的平衡采样的肽所描述的现代原子力场与隐式溶剂。我们的方法的主要新特点是使用预先计算的分子片段的统计库。通过组合片段构型（在本研究中为单个残基）对分子进行采样，这些片段构型存储在文库中。从独立库生成的合奏重新加权，以符合描述完整分子的力场的玻尔兹曼因子分布。通过这种方式，小肽（4-8个残基）的高质量平衡采样通常需要不到一小时的单处理器挂钟时间，并且可以比Langevin模拟快得多。此外，对于较大的肽（例如，16个残基）在不到一分钟的单处理器计算。我们还描述了一个应用程序的自由能计算，一个“多分辨率”实现的增长过程和应用程序的片段组装蛋白质结构预测协议。
英文摘要：
We adapted existing polymer growth strategies for equilibrium sampling of peptides described by modern atomistic forcefields with implicit solvent. The main novel feature of our approach is the use of pre-calculated 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 but clash-free ensembles can be generated for larger peptides (e.g., 16 residues) in less than a minute of single-processor computing. We also describe an application to free energy calculation, a "multi-resolution" implementation of the growth procedure and application to fragment assembly protein-structure prediction protocols.
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