Department of Biochemistry and Biophysics, School of Medicine, University of North Carolina, Chapel Hill, North Carolina 27599, United States.
J Phys Chem B. 2012 Jul 26;116(29):8375-82. doi: 10.1021/jp2114576. Epub 2012 Feb 10.
Until now it has been impractical to observe protein folding in silico for proteins larger than 50 residues. Limitations of both force field accuracy and computational efficiency make the folding problem very challenging. Here we employ discrete molecular dynamics (DMD) simulations with an all-atom force field to fold fast-folding proteins. We extend the DMD force field by introducing long-range electrostatic interactions to model salt-bridges and a sequence-dependent semiempirical potential accounting for natural tendencies of certain amino acid sequences to form specific secondary structures. We enhance the computational performance by parallelizing the DMD algorithm. Using a small number of commodity computers, we achieve sampling quality and folding accuracy comparable to the explicit-solvent simulations performed on high-end hardware. We demonstrate that DMD can be used to observe equilibrium folding of villin headpiece and WW domain, study two-state folding kinetics, and sample near-native states in ab initio folding of proteins of ∼100 residues.
到目前为止,对于大于 50 个残基的蛋白质,在计算机上观察蛋白质折叠一直是不切实际的。力场精度和计算效率的限制使得折叠问题极具挑战性。在这里,我们使用具有全原子力场的离散分子动力学 (DMD) 模拟来折叠快速折叠的蛋白质。我们通过引入长程静电相互作用来扩展 DMD 力场,以模拟盐桥和序列相关的半经验势能,该势能考虑了某些氨基酸序列形成特定二级结构的自然趋势。我们通过并行化 DMD 算法来提高计算性能。使用少量的商用计算机,我们实现了与在高端硬件上进行的显式溶剂模拟相当的采样质量和折叠精度。我们证明 DMD 可用于观察 villin 头部和 WW 结构域的平衡折叠,研究两态折叠动力学,并在约 100 个残基的蛋白质的从头折叠中采样近天然状态。