Adapting Poisson-Boltzmann to the self-consistent mean field theory: application to protein side-chain modeling.
Adapting Poisson-Boltzmann to the self-consistent mean field theory: application to protein side-chain modeling.
复制标题
DOI：
10.1063/1.3621831
复制
发表时间：
2011-08
期刊：
影响因子：
--
通讯作者：
P. Koehl;H. Orland;M. Delarue
中科院分区：
文献类型：
--
作者：
P. Koehl;H. Orland;M. Delarue
我们提出了蛋白质侧链模型的自一致平均场理论的扩展，其中包括基于泊松-玻尔兹曼（PB）理论的溶剂化效应。在这种方法中，蛋白质用其侧链的多个拷贝来表示。每个拷贝都被赋予一个权重，该权重是基于蛋白质其余部分产生的平均场能量迭代改进的，直到达到自一致性。在每个循环中，计算多拷贝系统的变分自由能；这个自由能包括蛋白质的内能，它解释了vdW和静电相互作用，以及用PB方程计算的溶剂化自由能项。该方法仅在几个周期内收敛，并且在商用个人计算机上只需要几分钟的中央处理单元时间。然后将每个残基的预测构象设置为收敛后权值最高的副本。我们已经在100个高度精细的核磁共振结构的数据库上测试了这种方法，以避免x射线结构固有的晶体堆积问题。使用铅衍生的溶剂化自由能显著提高了表面侧链的预测精度。例如，对表面半胱氨酸、丝氨酸和苏氨酸残基的χ(1)预测精度分别从68%、35%和43%提高到80%、53%和57%。与其他侧链预测算法的比较表明，我们的方法在预测暴露侧链的构象方面始终更好。
We present an extension of the self-consistent mean field theory for protein side-chain modeling in which solvation effects are included based on the Poisson-Boltzmann (PB) theory. In this approach, the protein is represented with multiple copies of its side chains. Each copy is assigned a weight that is refined iteratively based on the mean field energy generated by the rest of the protein, until self-consistency is reached. At each cycle, the variational free energy of the multi-copy system is computed; this free energy includes the internal energy of the protein that accounts for vdW and electrostatics interactions and a solvation free energy term that is computed using the PB equation. The method converges in only a few cycles and takes only minutes of central processing unit time on a commodity personal computer. The predicted conformation of each residue is then set to be its copy with the highest weight after convergence. We have tested this method on a database of hundred highly refined NMR structures to circumvent the problems of crystal packing inherent to x-ray structures. The use of the PB-derived solvation free energy significantly improves prediction accuracy for surface side chains. For example, the prediction accuracies for χ(1) for surface cysteine, serine, and threonine residues improve from 68%, 35%, and 43% to 80%, 53%, and 57%, respectively. A comparison with other side-chain prediction algorithms demonstrates that our approach is consistently better in predicting the conformations of exposed side chains.