3D-QSAR and molecular docking studies on pyrazolopyrimidine derivatives as glycogen synthase kinase-3beta inhibitors

Glycogen synthase kinase-3 (GSK-3), a serine/threonine kinase, is a fascinating enzyme with diverse biological actions in intracellular signaling systems, making it an emerging target for diseases such as diabetes mellitus, cancer, chronic inflammation, bipolar disorders and Alzheimer's disease. It is important to inhibit GSK-3 selectively and the net effect of the GSK-3 inhibitors thus should be target specific, over other phylogenetically related kinases such as CDK-2. In the present work, we have carried out three-dimensional quantitative structure activity relationship (3D-QSAR) studies on novel class of pyrazolopyrimidine derivatives as GSK-3 inhibitors reported to have improved cellular activity. Docked conformation of the most active molecule in the series, which shows desirable interactions in the receptor, was taken as template for alignment of the molecules. Statistically significant CoMFA and CoMSIA models were generated using 49 molecules in training set. By applying leave-one-out (LOO) cross-validation study, r(cv)2 values of 0.53 and 0.48 for CoMFA and CoMSIA, respectively and non-cross-validated (r(ncv)2) values of 0.98 and 0.92 were obtained for CoMFA and CoMSIA models, respectively. The predictive ability of CoMFA and CoMSIA models was determined using a test set of 12 molecules which gave predictive correlation coefficients (r(pred)2) of 0.47 and 0.48, respectively, indicating good predictive power. Based upon the information derived from CoMFA and CoMSIA contour maps, we have identified some key features that explain the observed variance in the activity and have been used to design new pyrazolopyrimidine derivatives. The designed molecules showed better binding affinity in terms of estimated docking scores with respect to the already reported systems; hence suggesting that newly designed molecules can be more potent and selective towards GSK-3beta inhibition.     

Molecular Modeling Studies of 4,5-Dihydro-1H-pyrazolo[4,3-h] quinazoline Derivatives as Potent CDK2/Cyclin A Inhibitors Using 3D-QSAR and Docking

CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r(2) (cv) values of 0.747 and 0.518 and r(2) values of 0.970 and 0.934, respectively. 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity.     

基于分子对接的雌激素类化合物与雌激素β受体的CoMSIA研究

采用分子对接方法完成了分子结构复杂多样的74个化合物的叠合,应用比较分子相似性指数分析方法（CoMSIA）研究了化合物与雌激素β受体（ERβ）之间的三维定量结构-活性关系（3D-QSAR）,建立了相关性显著、预测能力强的定量模型（q2=0.533,r2=0.870,rp2re=0.787）。CoMSIA和对接结果从一个侧面揭示了影响雌激素活性的分子结构特征和可能的分子机理。     

新烟碱类结构与活性的COMFA及CoMSIA研究

采用比较分子场分析(comparative molecular field analysis,CoMFA)和比较分子相似性指数分析(comparative similarity indices analysis,CoMSIA)方法,分别对一系列新烟碱类杀虫剂及相关化合物烟碱乙酰胆碱受体激动剂进行了结构与活性关系的研究,构建了CoMFA及CoMSIA模型;该模型具有较好的预报能力和拟合能力,CoMFA:q2=0.563,r2=O.950;CoMSIA:q2=0.657,r2=0.973.通过三维等势图分析得出了对新烟碱类活性影响较大的基团或原子,为新烟碱类化合物的进一步研究提供了依据.