k-nearest neighbor molecular field analysis based 3D-QSAR and in silico ADME/T studies of cinnamoyl derivatives as HIV-1 integrase inhibitors

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• 作者：V. K. Srivastav ; M. Tiwari
• 关键词：Cinnamoyl derivatives ; HIV ; 1 IN inhibition ; 3D ; QSAR ; kNN ; MFA ; ADME/T
• 刊名：Medicinal Chemistry Research
• 出版年：2015
• 出版时间：February 2015
• 年：2015
• 卷：24
• 期：2
• 页码：684-700
• 全文大小：2,604 KB
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• 刊物主题：Pharmacology/Toxicology; Biochemistry, general; Cell Biology;
• 出版者：Springer US
• ISSN：1554-8120

文摘

A three-dimensional quantitative structure activity relationship (3D-QSAR) study was carried out on a dataset of 62 cinnamoyl derivatives as human immunodeficiency virus-1 integrase (HIV-1 IN) inhibitors using k-nearest neighbor molecular field analysis (kNN-MFA). QSAR models were developed using stepwise-forward selection (SWF), genetic algorithm (GA), and simulated annealing (SA) variable selection approaches. Selected QSAR models were validated internally [using cross-validated squared correlation coefficient (q 2)] and externally [using predicted squared correlation coefficient (pred_r 2) and Y randomization] to determine their predictive ability. SA-kNN-MFA model (q 2?=?0.7669, pred_r 2?=?0.7566) was considered as the best model due to its better predictive ability (higher pred_r 2 value) as compared to SWF-kNN-MFA (q 2?=?0.8956, pred_r 2?=?0.5905) and GA-kNN-MFA (q 2?=?0.6431, pred_r 2?=?0.7525) models in external validation. Steric and electrostatic field descriptors were favorable for HIV-1 IN inhibition activity in the best model. HIV-1 IN inhibition activity of an external dataset containing 22 compounds was predicted to check the applicability domain of developed models. Drug-likeness and in silico absorption, distribution, metabolism, excretion, and toxicity (ADME/T) studies were also performed to determine the pharmacokinetic and toxicity profile of dataset compounds. Subsequently, HIV-1 IN inhibition activity of 53 proposed compounds was predicted using developed models and their ADME/T properties were also calculated. Results of the present study suggested that 3D-QSAR model developed by SA-kNN-MFA method may be helpful to understand the structural requirement for HIV-1 IN inhibition and may support the designing of potent antiretroviral agents.