Patel Pallav D, Patel Maulik R, Kaushik-Basu Neerja, Talele Tanaji T
Department of Pharmaceutical Sciences, College of Pharmacy and Allied Health Professions, St. John's University, Jamaica, New York 11439, USA.
J Chem Inf Model. 2008 Jan;48(1):42-55. doi: 10.1021/ci700266z. Epub 2007 Dec 13.
The urgent need for novel HCV antiviral agents has provided an impetus for understanding the structural requisites of NS5B polymerase inhibitors at the molecular level. Toward this objective, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) of 67 HCV NS5B polymerase inhibitors were performed using two methods. First, ligand-based 3D QSAR studies were performed based on the lowest energy conformations employing the atom fit alignment method. Second, receptor-based 3D QSAR models were derived from the predicted binding conformations obtained by docking all NS5B inhibitors at the allosteric binding site of NS5B (PDB ID: 2dxs). Results generated from the ligand-based model were found superior (r2cv values of 0.630 for CoMFA and 0.668 for CoMSIA) to those obtained by the receptor-based model (r2cv values of 0.536 and 0.561 for CoMFA and CoMSIA, respectively). The predictive ability of the models was validated using a structurally diversified test set of 22 compounds that had not been included in a preliminary training set of 45 compounds. The predictive r2 values for the ligand-based CoMFA and CoMSIA models were 0.734 and 0.800, respectively, while the corresponding predictive r2 values for the receptor-based CoMFA and CoMSIA models were 0.538 and 0.639, respectively. The greater potency of the tryptophan derivatives over that of the tyrosine derivatives was interpreted based on CoMFA steric and electrostatic contour maps. The CoMSIA results revealed that for a NS5B inhibitor to have appreciable inhibitory activity it requires hydrogen bond donor and acceptor groups at the 5-position of the indole ring and an R substituent at the chiral carbon, respectively. Interpretation of the CoMFA and CoMSIA contour maps in context of the topology of the allosteric binding site of NS5B provided insight into NS5B-inhibitor interactions. Taken together, the present 3D QSAR models were found to accurately predict the HCV NS5B polymerase inhibitory activity of structurally diverse test set compounds and to yield reliable clues for further optimization of the benzimidazole derivatives in the data set.
对新型丙型肝炎病毒（HCV）抗病毒药物的迫切需求推动了在分子水平上理解NS5B聚合酶抑制剂结构要求的研究。为实现这一目标，使用两种方法对67种HCV NS5B聚合酶抑制剂进行了比较分子场分析（CoMFA）和比较分子相似性指数分析（CoMSIA）。首先，基于最低能量构象，采用原子拟合比对方法进行基于配体的三维定量构效关系（3D QSAR）研究。其次，基于受体的3D QSAR模型是从通过将所有NS5B抑制剂对接至NS5B的变构结合位点（蛋白质数据银行ID：2dxs）获得的预测结合构象推导而来。发现基于配体的模型产生的结果优于基于受体的模型（CoMFA的交叉验证r2值为0.630，CoMSIA的交叉验证r2值为0.668，而CoMFA和CoMSIA基于受体的模型交叉验证r2值分别为0.536和0.561）。使用一组结构多样的22种化合物（未包含在45种化合物的初步训练集中）对模型的预测能力进行了验证。基于配体的CoMFA和CoMSIA模型的预测r2值分别为0.734和0.800，而基于受体的CoMFA和CoMSIA模型的相应预测r2值分别为0.538和0.639。基于CoMFA的空间和静电等高线图解释了色氨酸衍生物比酪氨酸衍生物具有更高效力的原因。CoMSIA结果表明，对于一种NS5B抑制剂要有可观的抑制活性，它分别需要在吲哚环的5位有氢键供体和受体基团以及在手性碳上有一个R取代基。结合NS5B变构结合位点的拓扑结构对CoMFA和CoMSIA等高线图的解释提供了对NS5B-抑制剂相互作用的深入了解。综上所述，发现当前的3D QSAR模型能够准确预测结构多样的测试集化合物的HCV NS5B聚合酶抑制活性，并为进一步优化数据集中的苯并咪唑衍生物提供可靠线索。
