Deng Nanjie, Forli Stefano, He Peng, Perryman Alex, Wickstrom Lauren, Vijayan R S K, Tiefenbrunn Theresa, Stout David, Gallicchio Emilio, Olson Arthur J, Levy Ronald M
Center for Biophysics & Computational Biology/ICMS, ‡Department of Chemistry, Temple University , Philadelphia, Pennsylvania19122, United States.
J Phys Chem B. 2015 Jan 22;119(3):976-88. doi: 10.1021/jp506376z. Epub 2014 Sep 17.
Molecular docking is a powerful tool used in drug discovery and structural biology for predicting the structures of ligand-receptor complexes. However, the accuracy of docking calculations can be limited by factors such as the neglect of protein reorganization in the scoring function; as a result, ligand screening can produce a high rate of false positive hits. Although absolute binding free energy methods still have difficulty in accurately rank-ordering binders, we believe that they can be fruitfully employed to distinguish binders from nonbinders and reduce the false positive rate. Here we study a set of ligands that dock favorably to a newly discovered, potentially allosteric site on the flap of HIV-1 protease. Fragment binding to this site stabilizes a closed form of protease, which could be exploited for the design of allosteric inhibitors. Twenty-three top-ranked protein-ligand complexes from AutoDock were subject to the free energy screening using two methods, the recently developed binding energy analysis method (BEDAM) and the standard double decoupling method (DDM). Free energy calculations correctly identified most of the false positives (≥83%) and recovered all the confirmed binders. The results show a gap averaging ≥3.7 kcal/mol, separating the binders and the false positives. We present a formula that decomposes the binding free energy into contributions from the receptor conformational macrostates, which provides insights into the roles of different binding modes. Our binding free energy component analysis further suggests that improving the treatment for the desolvation penalty associated with the unfulfilled polar groups could reduce the rate of false positive hits in docking. The current study demonstrates that the combination of docking with free energy methods can be very useful for more accurate ligand screening against valuable drug targets.
分子对接是药物发现和结构生物学中用于预测配体 - 受体复合物结构的强大工具。然而,对接计算的准确性可能受到诸如评分函数中忽略蛋白质重排等因素的限制;因此,配体筛选可能会产生较高的假阳性命中率。尽管绝对结合自由能方法在准确对结合剂进行排序方面仍存在困难,但我们认为它们可有效地用于区分结合剂和非结合剂,并降低假阳性率。在此,我们研究了一组与HIV - 1蛋白酶瓣上一个新发现的潜在变构位点对接良好的配体。片段与该位点的结合稳定了蛋白酶的封闭形式,这可用于变构抑制剂的设计。来自AutoDock的23个排名靠前的蛋白质 - 配体复合物使用两种方法进行自由能筛选,即最近开发的结合能分析方法(BEDAM)和标准双去耦方法(DDM)。自由能计算正确识别了大多数假阳性(≥83%)并找回了所有已确认的结合剂。结果显示结合剂和假阳性之间的平均差距≥3.7千卡/摩尔。我们提出了一个将结合自由能分解为受体构象宏观状态贡献的公式,这为不同结合模式的作用提供了见解。我们的结合自由能成分分析进一步表明,改进对与未满足极性基团相关的去溶剂化惩罚的处理可以降低对接中的假阳性命中率。当前的研究表明,对接与自由能方法的结合对于针对有价值的药物靶点进行更准确的配体筛选非常有用。