Water plays an active role in many fundamental phenomena in cellular systems such as molecular recognition, folding and conformational equilibria, reaction kinetics and phase partitioning. Hence, our ability to account for the energetics of these processes is highly dependent on the models we use for calculating solvation effects. For example, theoretical prediction of protein-ligand binding modes (i.e., docking) and binding affinities (i.e., scoring) requires an accurate description of the change in hydration that accompanies solute binding. In this review, we discuss the challenges of constructing solvation models that capture these effects, with an emphasis on continuum models and on more recent developments in the field. In our discussion of methods, relatively greater attention will be given to boundary element solutions to the Poisson equation and to nonpolar solvation models, two areas that have become increasingly important but are likely to be less familiar to many readers. The other focus will be upon the trending efforts for evaluating solvation models in order to uncover limitations, biases, and potentially attractive directions for their improvement and applicability. The prospective and retrospective performance of a variety of solvation models in the SAMPL blind challenges will be discussed in detail. After just a few years, these benchmarking exercises have already had a tangible effect in guiding the improvement of solvation models.

译文

水在细胞系统中的许多基本现象中起着积极作用,例如分子识别,折叠和构象平衡,反应动力学和相分配。因此,我们解释这些过程的能量学的能力在很大程度上取决于我们用于计算溶剂化效应的模型。例如,蛋白质-配体结合模式 (即对接) 和结合亲和力 (即评分) 的理论预测需要准确描述伴随溶质结合的水合变化。在这篇综述中,我们讨论了构建捕获这些影响的溶剂化模型的挑战,重点是连续模型和该领域的最新发展。在我们对方法的讨论中,将相对更多地关注泊松方程的边界元解和非极性溶剂化模型,这两个领域已变得越来越重要,但许多读者可能不太熟悉。另一个重点将放在评估溶剂化模型的趋势上,以发现局限性,偏见以及其改进和适用性的潜在吸引力方向。将详细讨论SAMPL盲挑战中各种溶剂化模型的前瞻性和回顾性表现。短短几年后,这些基准测试工作已经在指导溶剂化模型的改进方面产生了切实的效果。

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