Reducing the Secondary Structure Bias in the Generalized Born Model via R6 Effective Radii
Reducing the Secondary Structure Bias in the Generalized Born Model via R6 Effective Radii
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DOI：
10.1021/ct100392h
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发表时间：
2010-12-01
影响因子：
5.5
通讯作者：
Onufriev, Alexey V.
中科院分区：
文献类型：
--
作者：
Aguilar, Boris;Shadrach, Richard;Onufriev, Alexey V.
广义Born模型(GB)为计算溶剂化自由能的静电分量(ΔG(El))提供了一种相当准确和高效的方法。在这项工作中，我们开发了一种计算有效出生半径的方法，旨在解决先前报道的GB模型的已知二级结构偏差(Roe等人。J.Phys.化学。B，2007,111,1846-1857)。我们的分析方法，称为AR6，是基于分子体积近似下的垂直杆r垂直杆(-6)(R6)积分。在该方法中，结合了对VDW-体积积分的几个计算效率的修正，以接近每个原子附近的真实分子体积。以丙氨酸十肽的四种构象状态为例，验证了AR6模型预测相对增量G(El)的准确性。由AR6估计的不同构象对之间的G(El)值相对于显式溶剂的变化具有相同的均方根误差，相应的数值PB值也是如此，同时，该模型的均方根误差比Amber包中流行的GB_OBC模型的均方根误差低2倍。对蛋白质和DNA等22种生物分子结构进行的PB处理实验表明，Delta G(El)的相对误差为0.58%，AR6计算的Delta G(El)的均方根误差比GB_OBC的对应值低3倍。然而，AR6模型和GB_OBC模型的计算效率是相当的。R6模型的一个变种，NSR6，基于三角分子表面上的数值精确积分，在一组小的类药物分子上进行了测试(Nicholls等人。J.Med.化学。2008年，51,769-779)。当增加空穴和VDW项来考虑溶剂化能的非极性部分时，只有一个自由参数的模型能够预测总的溶剂化自由能，相对于实验数据的误差在1.73kcal/molRMS以内。在NSR6公式中，非极性贡献的计算特别有效，因为它的VDW部分依赖于相同的垂直杆r垂直杆(-6)积分。
The generalized Born model (GB) provides a reasonably accurate and computationally efficient way to compute the electrostatic component (Delta G(el)) of the solvation free energy. In this work, we have developed a method to compute effective Born radii, which is intended to address the known secondary structure bias of the GB model reported earlier (Roe et al. J. Phys. Chem. B, 2007, 111, 1846-1857). Our analytical approach, termed AR6, is based on the vertical bar r vertical bar(-6) (R6) integration over an approximation to molecular volume. Within the approach, several computationally efficient corrections to the pairwise VDW-volume integration are combined to closely approximate the true molecular volume in the vicinity of each atom. The accuracy of the AR6 model in predicting relative Delta G(el) is tested on four conformational states of alanine decapeptide. Changes in Delta G(el) estimated by AR6 between various pairs of conformational states have the same RMS error relative to the explicit solvent, as do the corresponding numerical PB values; at the same time, the RMS error of the proposed model is 2 times lower than that of the popular GB_OBC model from the AMBER package. Tests against the PB treatment on 22 biomolecular structures including proteins and DNA show that the relative error of Delta G(el) is 0.58%; the RMS error of Delta G(el) computed by AR6 is 3 times lower than the corresponding value for GB_OBC. However, the computational efficiencies of the AR6 and GB_OBC models are comparable. A variant of the R6 model, NSR6, based on numerically exact integration over triangulated molecular surface is tested on a "challenge" set of small drug-like molecules (Nicholls et al. J. Med. Chem. 2008, 51, 769-779). When augmented with cavity and VDW terms to account for the nonpolar part of solvation energy, the model with only one free parameter is capable of predicting the total solvation free energy to within 1.73 kcal/mol RMS error relative to experimental data. Within the NSR6 formulation, computation of the nonpolar contribution is particularly efficient because its VDW part depends on the same vertical bar r vertical bar(-6) integrals.