角鲨烯
药效团
虚拟筛选
酶
ATP合酶
化学
活动站点
立体化学
计算生物学
生物化学
生物
作者
Avani Chokshi,Mahesh T. Chhabria,Pritesh R. Desai
出处
期刊:Current Computer - Aided Drug Design
[Bentham Science]
日期:2018-07-27
卷期号:14 (3): 221-233
被引量:5
标识
DOI:10.2174/1573409914666180507143024
摘要
Introduction: In the present research work, a pharmacophore based virtual screening was performed using Discovery Studio 2.1 for the discovery of some novel molecules as inhibitors of Squalene Synthase Enzyme, a key enzyme in cholesterol biosynthetic pathway. Methods: A quantitative pharmacophore HypoGen was generated and the best HypoGen had two ring aromatic and one hydrogen bond acceptor lipid features. The best HypoGen showed a very good correlation coefficient (r = 0.901) with satisfactory cost analysis. Furthermore, the HypoGen was validated externally by predicting the activity of test set. The developed model was found to be predictive as it showed low error of prediction for test set molecules. The developed model was used as a search query for virtually screening two chemical databases: sample database from catalyst and minimaybridge. Results and Discussion: The best hit with good fit value and low predicted activity was further modified to design novel drug-like molecules, which were able to bind to Squalene synthase enzyme active site. Conclusion: The best scoring molecule, compound 67 showed 53% inhibition of the human Squalene synthase enzyme, isolated from the cell lysates of Human Hepatoma Cell Line, at a dose of 10 mcg with an IC50 value of 9.43 µm. Keywords: Pahrmacophore, squalene synthase, chemical databases, hits, hypogen, hypothesis.
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