Poongavanam Vasanthanathan, Steinmann Casper, Kongsted Jacob
Department of Physics, Chemistry and Pharmacy, University of Southern Denmark, Odense M, Denmark.
PLoS One. 2014 Jun 4;9(6):e98659. doi: 10.1371/journal.pone.0098659. eCollection 2014.
Quantum mechanical (QM) calculations have been used to predict the binding affinity of a set of ligands towards HIV-1 RT associated RNase H (RNH). The QM based chelation calculations show improved binding affinity prediction for the inhibitors compared to using an empirical scoring function. Furthermore, full protein fragment molecular orbital (FMO) calculations were conducted and subsequently analysed for individual residue stabilization/destabilization energy contributions to the overall binding affinity in order to better understand the true and false predictions. After a successful assessment of the methods based on the use of a training set of molecules, QM based chelation calculations were used as filter in virtual screening of compounds in the ZINC database. By this, we find, compared to regular docking, QM based chelation calculations to significantly reduce the large number of false positives. Thus, the computational models tested in this study could be useful as high throughput filters for searching HIV-1 RNase H active-site molecules in the virtual screening process.
量子力学（QM）计算已被用于预测一组配体对HIV-1逆转录酶相关核糖核酸酶H（RNH）的结合亲和力。与使用经验评分函数相比，基于QM的螯合计算显示出对抑制剂结合亲和力预测的改进。此外，进行了完整蛋白质片段分子轨道（FMO）计算，并随后分析了各个残基对整体结合亲和力的稳定/去稳定能量贡献，以便更好地理解真阳性和假阳性预测。在基于一组训练分子成功评估这些方法之后，基于QM的螯合计算被用作ZINC数据库中化合物虚拟筛选的过滤器。由此，我们发现，与常规对接相比，基于QM的螯合计算可显著减少大量假阳性。因此，本研究中测试的计算模型可作为高通量过滤器，用于在虚拟筛选过程中搜索HIV-1核糖核酸酶H活性位点分子。
