Hydroxyethylamine derivatives as HIV-1 protease inhibitors: a predictive QSAR modelling study based on Monte Carlo optimization

Abstract

Application of HIV-1 protease inhibitors (as an anti-HIV regimen) may serve as an attractive strategy for anti-HIV drug development. Several investigations suggest that there is a crucial need to develop a novel protease inhibitor with higher potency and reduced toxicity. Monte Carlo optimized QSAR study was performed on 200 hydroxyethylamine derivatives with antiprotease activity. Twenty-one QSAR models with good statistical qualities were developed from three different splits with various combinations of SMILES and GRAPH based descriptors. The best models from different splits were selected on the basis of statistically validated characteristics of the test set and have the following statistical parameters: r² = 0.806, Q² = 0.788 (split 1); r² = 0.842, Q² = 0.826 (split 2); r² = 0.774, Q² = 0.755 (split 3). The structural attributes obtained from the best models were analysed to understand the structural requirements of the selected series for HIV-1 protease inhibitory activity. On the basis of obtained structural attributes, 11 new compounds were designed, out of which five compounds were found to have better activity than the best active compound in the series.

Keywords:

• HIV-1 protease inhibitor
• Monte Carlo optimization
• QSAR
• SMILES
• GRAPH
• hybrid descriptor

Acknowledgements

SB sincerely acknowledges All India Council for Technical Education (AICTE), New Delhi, India for awarding Post Graduate GPAT Fellowship. NA is grateful to University Grants Commission (UGC), New Delhi, India for providing Rajiv Gandhi National Fellowship (Grant No. F1-17.1/2014-15/RGNF-2014-15-SC-WES- 73725/SA-III/Website). SG thanks the UGC, New Delhi, India for awarding a UGC-Start up grant (No. F.30-106/2015-BSR). TJ is grateful to Universities with Potential for Excellence (UPE), Phase-II programme of UGC, New Delhi to Jadavpur University, Kolkata, India for financial assistance. The authors are thankful to the authority of Jadavpur University, Kolkata and Dr. Harisingh Gour University, Sagar, India for providing research facilities.