Evaluation of binding of potential ADMET/tox screened saquinavir analogues for inhibition of HIV-protease via molecular dynamics and binding free energy calculations

Abstract

Developing novel drug molecules against HIV is a scientific quest necessitated by development of drug resistance against used drugs. We report comparative results of molecular dynamics simulation studies on 11 structural analogues of Saquinavir (SQV) – against HIV-protease that were earlier examined for pharmacodynamic and pharmacokinetic properties. We reported analogues S1, S5 and S8 to qualify the ADMET criterion and may be considered as potential lead molecules. In this study the designed molecules were successively docked with native HIV-protease at AutoDock. Docking scores established relative goodness of the 11 analogues against the benchmark for Saquinavir. The docked complexes were subjected to molecular dynamics simulation studies using GROMACS 4.6.2. Four parameters viz. H-bonding, RMSD, Binding energy and Protein–Ligand Distance were used for comparative analyses of the analogues relative to Saquinavir. The comparison and analysis of the results are indicative that analogues S8, S9 and S1 are promising candidates among all the analogues studied. From our earlier work and present study it is evident that among the three S8 and S1 qualify the ADMET criterion and between S1 and S8, the analogue S8 shows more target efficacy and specificity over S1 and have better molecular dynamics simulation results. Thus, of the 11 de novo Saquinavir analogues, the S8 appears to be the most promising candidate as lead molecule for HIV-protease inhibitor and is best suited for testing under biological system. Further validation of the proposed lead molecules through wet lab studies involving antiviral assays however is required.

Communicated by Ramaswamy H. Sarma

Keywords:

• Analogues
• docking
• HIV protease
• molecular dynamic simulations – Saquinavir

Acknowledgments

AJ was financially supported via Junior Research Fellowship from the University Grants Commission, New Delhi. MD Simulations were performed at the Bioinformatics Infrastructure Facility, College of Veterinary Sciences, Assam Agricultural University, Guwahati, India.