Aksakal Fatma, Shvets Natali, Khairullina Veronika, Dimoglo Anatholy
Department of Environmental Engineering, Faculty of Engineering, Gebze Technical University, P.O. Box: 141, Gebze 41400, Kocaeli/Turkey.
Mini Rev Med Chem. 2016;16(7):579-94. doi: 10.2174/1389557515666151016124503.
Structural and electronic factors influencing the inhibition of cyclooxygenase-1 and -2 (COX-1/COX-2) were studied by means of Electronic-Topological Method combined with Neural Networks (ETM-NN), molecular docking and Density Functional Theory (DFT). A series of structurally diverse compounds containing 209 molecules were classified in accordance with their inhibiting properties, as selectively inhibiting and non-selectively inhibiting COX-2 receptor agents (110 and 99 molecules, correspondingly). The results obtained from the ETM-NN calculations gave us possibility of selecting those pharmacophoric molecular fragments, which allow for the search of new selective inhibitors of COX-2 with high probability of realization. The final selection of pharmacophores and anti-pharmacophores found was taken as a basis for a system designed for the COX-2 inhibitory activity prediction. Analysis of the electron density distribution showed that more effective binding with COX-2 receptor was observed for selective inhibitors. To make an assessment of these interactions, calculations of stabilization energies were carried out for the ligand-receptor complexes. From the results of the docking and from the analysis of electronic structures of active sites of enzymes, some peculiarities of ligand-receptor binding and its influence on the selectivity of the COX-2 relative to COX-1 inhibition were elucidated. 95% of compounds were recognized correctly, as the most active ones, by the system of prediction designed. Thus, the system being the result of the study is capable of predicting the selective inhibitory activity of COX-2 successfully. As a consequence, it can be used both for computer screening and synthesis of potent inhibitors of COX-2 with molecular skeletons that may vary considerably.
采用电子拓扑方法结合神经网络(ETM-NN)、分子对接和密度泛函理论(DFT),研究了影响环氧化酶-1和-2(COX-1/COX-2)抑制作用的结构和电子因素。根据抑制特性,将一系列包含209个分子的结构多样的化合物分类为选择性抑制和非选择性抑制COX-2受体的药物(分别为110个和99个分子)。ETM-NN计算结果使我们有可能选择那些药效团分子片段,从而有很大概率寻找到新的COX-2选择性抑制剂。所发现的药效团和反药效团的最终选择被用作设计COX-2抑制活性预测系统的基础。电子密度分布分析表明,选择性抑制剂与COX-2受体的结合更有效。为了评估这些相互作用,对配体-受体复合物进行了稳定能计算。从对接结果和酶活性位点的电子结构分析中,阐明了配体-受体结合的一些特点及其对COX-2相对于COX-1抑制选择性的影响。所设计的预测系统正确识别了95%的化合物为活性最高的化合物。因此,该研究结果所形成的系统能够成功预测COX-2的选择性抑制活性。因此,它可用于计算机筛选和合成具有可能有很大差异的分子骨架的COX-2强效抑制剂。