Validation and use of the MM-PBSA approach for drug discovery
Validation and use of the MM-PBSA approach for drug discovery
复制标题
DOI：
10.1021/jm049081q
复制
发表时间：
2005-06-16
影响因子：
7.3
通讯作者：
Stahl, M
中科院分区：
文献类型：
--
作者：
Kuhn, B;Gerber, P;Stahl, M
MM-PBSA方法已成为计算生物分子复合物结合亲和力的流行方法。已发表的应用实例集中在小的测试集和几个蛋白质，因此，在评估这种方法的一般有效性的相关性有限。为了进一步表征MM-PBSA，我们报告了涉及大量配体和八种不同蛋白质的更广泛的研究。我们的研究结果表明，应用MM-PBSA能量函数到一个单一的，放松的复杂结构是一个足够的，有时更准确的方法比标准的自由能平均分子动力学快照。在单一结构上使用MM-PBSA显示出有价值的（a）作为进一步丰富虚拟筛选结果的后对接过滤器，（B）作为优先化从头设计解决方案的有用工具，和（c）用于区分良好和弱结合剂（Δ pIC（50）>= 2-3），但很少用于再现较小的自由能差异。
The MM-PBSA approach has become a popular method for calculating binding affinities of biomolecular complexes. Published application examples focus on small test sets and few proteins and, hence, are of limited relevance in assessing the general validity of this method. To further characterize MM-PBSA, we report on a more extensive study involving a large number of ligands and eight different proteins. Our results show that applying the MM-PBSA energy function to a single, relaxed complex structure is an adequate and sometimes more accurate approach than the standard free energy averaging over molecular dynamics snapshots. The use of MM-PBSA on a single structure is shown to be valuable (a) as a postdocking filter in further enriching virtual screening results, (b) as a helpful tool to prioritize de novo design solutions, and (c) for distinguishing between good and weak binders (Delta pIC(50) >= 2-3), but rarely to reproduce smaller free energy differences.