Further Development of the FFT-based Method for Atomistic Modeling of Protein Folding and Binding under Crowding: Optimization of Accuracy and Speed.

Further Development of the FFT-based Method for Atomistic Modeling of Protein Folding and Binding under Crowding: Optimization of Accuracy and Speed.
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DOI:
10.1021/ct5001878
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发表时间:
2014-07-08
影响因子:
5.5
通讯作者:
Zhou, Huan-Xiang
Zhou, Huan-Xiang
中科院分区:
化学1区
文献类型:
--
作者:
Qin, Sanbo;Zhou, Huan-Xiang

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最近,我们(Qin, S.; Zhou, H. X. J. Chem. Theory Comput.2013, 9, 4633–4643)开发了基于 FFT 的原子蛋白质-群体相互作用建模方法,以下简称 FMAP。鉴于其在计算拥挤对蛋白质折叠和结合自由能的影响方面的潜在广泛用途,我们的目标是优化 FMAP 的准确性和速度。 FMAP 基于将蛋白质-群体相互作用表达为相关函数,并通过快速傅立叶变换 (FFT) 评估后者。随着离散空间网格间距的减小,FFT 的数值精度会提高,但计算成本也会增加。我们试图通过使用相对较粗的 0.6 Å 网格间距来加速 FMAP 计算,然后纠正离散化误差。该策略针对不同类型的相互作用(硬核排斥、非极性吸引力和静电相互作用)以及广泛的蛋白质聚集系统进行了测试。我们能够通过原子硬核半径膨胀 8% 来校正硬核排斥力和非极性吸引力的数值误差,通过蛋白质原子电荷大小膨胀 5% 来校正静电相互作用的数值误差。校正后的结果具有更高的精度,并且比使用 0.15 Å 的精细网格间距获得的结果提高了 100 倍以上。通过精度和速度的优化,FMAP 可能成为类细胞环境中蛋白质折叠和结合的真实建模的实用工具。
Recently, we (Qin, S.; Zhou, H. X. J. Chem. Theory Comput.2013, 9, 4633–4643) developed the FFT-based method for Modeling Atomistic Proteins–crowder interactions, henceforth FMAP. Given its potential wide use for calculating effects of crowding on protein folding and binding free energies, here we aimed to optimize the accuracy and speed of FMAP. FMAP is based on expressing protein–crowder interactions as correlation functions and evaluating the latter via fast Fourier transform (FFT). The numerical accuracy of FFT improves as the grid spacing for discretizing space is reduced, but at increasing computational cost. We sought to speed up FMAP calculations by using a relatively coarse grid spacing of 0.6 Å and then correcting for discretization errors. This strategy was tested for different types of interactions (hard-core repulsion, nonpolar attraction, and electrostatic interaction) and over a wide range of protein–crowder systems. We were able to correct for the numerical errors on hard-core repulsion and nonpolar attraction by an 8% inflation of atomic hard-core radii and on electrostatic interaction by a 5% inflation of the magnitudes of protein atomic charges. The corrected results have higher accuracy and enjoy a speedup of more than 100-fold over those obtained using a fine grid spacing of 0.15 Å. With this optimization of accuracy and speed, FMAP may become a practical tool for realistic modeling of protein folding and binding in cell-like environments.
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