Tropical Journal of Pharmaceutical Research

Original Research Article | OPEN ACCESS

In-silico design of novel 4-aminoquinolinyl analogs as potential anti-malaria agents using quantitative structure-activity relationships and ADMET approach

Bo Wu¹, Jiao-Long Wang², Liang Li³, Chun-Jie Wu², Chong-Bo Zhao^1,4

¹Department of Pharmaceutics, College of Pharmacy, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi; ²School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137; ³Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu 610075; ⁴Department of Pharmaceutics, College of Pharmacy, Engineering Technology Research Center of Shaanxi Administration of Chinese Herbal Pieces, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi, PR China.

For correspondence:- Chong-Bo Zhao Email: zhao_chongbo@126.com Tel:+862938185072

Accepted: 31 December 2019 Published: 01 February 2020

Citation: Wu B, Wang J, Li L, Wu C, Zhao C. In-silico design of novel 4-aminoquinolinyl analogs as potential anti-malaria agents using quantitative structure-activity relationships and ADMET approach. Trop J Pharm Res 2020; 19(1):169-181 doi: 10.4314/tjpr.v19i1.25

© 2020 The authors.
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Abstract

Purpose: To design and screen for potential anti-malaria agents based on a series of 4-aminoquinolinyl analogues.

Methods: Molecular fingerprint analysis was used for molecular partitioning of training and test sets. Acquired training sets were used for CoMFA and CoMSIA model construction after good alignment was achieved. Partial least squares analysis combined with external validation were used for model evaluation. Deep analysis of acquired contour maps was performed to summarize the substituent property requirements for further rational molecular design. Using the chosen models, activity prediction and subsequent ADMET investigation were performed to discover novel designed compounds with the desired properties.

Results: Three different set partitions for model establishment were obtained using fingerprint-based selection. Partition 02 offered an optimal CoMFA model (r² = 0.964, q² = 0.605 and r^2pred = 0.6362) and the best CoMSIA model (r² = 0.955, q² = 0.585 and r²_pred = 0.6403). Based on contour map analysis, a series of compounds were designed for activity prediction. Two of the compounds (wmx09, wmx25) were chosen for their ideal predicted biological activities. Subsequent ADMET investigation indicated that these compoundss have acceptable drug-like characteristics.

Conclusion: The screening reveals that compounds wmx09 and wmx25 have strong potential as anti-malaria agents.

Keywords: Malaria, 4-Aminoquinolinyl, Molecular fingerprint, QSAR, ADMET