3C-like蛋白酶抑制剂的构效关系、分子对接和分子动力学

QSAR,Molecular Docking and Molecular Dynamics of 3C-like Protease Inhibitors

3C-like蛋白酶是中东呼吸综合征冠状病毒(MERS-Co V)等其它冠状病毒的繁殖过程中极为重要的蛋白酶。它已成为人类在抗冠状病毒领域中的研究热点。本文基于计算生物学方法对与MERS-Co V同属的蝙蝠冠状病毒HKU4(HKU4-Co V)的43个肽类3C-like蛋白酶抑制剂分子,建立三维定量构效关系(3D-QSAR)模型。在基于配体叠合的基础上,发现比较分子相似性指数分析法(Co MSIA)中的四个场组合(位阻场、静电场、氢键供体场与氢键受体场)为最优的模型(Q2=0.522,R2ncv=0.996,R2pre=0.904;Q2:交叉验证相关系数,R2ncv:非交叉验证相关系数,R2pre:验证集分子的预测值相关系数),并借助该模型通过分子对接(docking)与分子动力学(MD)方法阐明了配受体结合作用。实验结果表明:(1)基于最优的Co MSIA模型基础上的三维等势图形象地说明了分子基团的位阻作用、静电作用、氢键供体与氢键受体作用对分子生物活性的影响;(2)分子对接研究结果显示了疏水性以及结晶水、氨基酸His166和Glu169在配体和受体结合过程中产生重要作用;(3)分子动力学模拟进一步验证了分子对接模型的可靠性,并发现了两个新的关键氨基酸Ser24与Gln192,它们与配体产生了两个较强的氢键。此外,根据这些结果,一些新的具有潜在抑制活性的肽类化合物作为3C-like蛋白酶抑制剂被获得。以上结果能够帮助深入了解3C-like蛋白酶与肽类抑制剂的作用机理,并且能够为今后的抗MERS-Co V药物设计提供有价值的参考。

3C-like protease is an extremely important protease involved in the multiplicative process of coronaviruses, including the deadly Middle East respiratory syndrome coronavirus （MERS-CoV）. 3C-like protease has become a hot research topic in the field of coronavirology. For the first time, a set of ligand- and receptor- based three-dimensional quantitative structure-activity relationships （3D-QSAR） models were carried out via comparative molecular field analysis （CoMFA） and comparative molecular similarity indices analysis （CoMSIA） to explore the structure-activity correlation of 43 peptidomimetic inhibitors of the 3C-like protease of the bat coronavirus HKU4 （HKU4-CoV）, which belongs to the same 2c lineage as MERS-CoV and shows high sequence similarity with MERS-CoV. Based on the ligand-based alignment, an optimal CoMSIA model （yielded by steric, electrostatic, H-bond donor and H-bond acceptor fields） was obtained with good predictive power of （22 = 0.522, R2pre, = 0.996 and R2pre = 0.904 （Q2： cross-validated correlation coefficient,R2pre： non-cross-validated correlation coefficient, R2pre： predicted correlation coefficient for the test set of compounds）. Molecular docking and molecular dynamics simulations were performed according to this model to further determine the interaction mechanism between ligands and the receptor. The experimental results show： （1） based on the optimal CoMSIA model, the 3D contour maps vividly illustrate that the molecular biological activity is influenced by the steric, electrostatic, H-bond donor and H-bond acceptor interactions of molecular groups. （2） Based on the docking analysis, hydrophobicity, crystal water, His166 and Glu169 have important roles in the ligands and receptor binding process. （3） Molecular dynamics （MD） simulations were carried out for further verification of the reliability of the docking model, and provide two new key residues, Ser24 and Gin192, which have two strong hydrogen bonds with the ligands. Some new compounds were obtained based on the modeling that are potential peptidomimetic inhibitors of 3C-like protease. These results help establish the binding mechanism between 3C-like protease and peptidomimetic inhibitors, and provide a valuable reference for future anti-MERS-CoV drug design.