In-silico approaches towards development of model irreversible HIV-1 protease inhibitors

Abstract

AbstractThere is growing evidence for the rapid rise of strains that encode mutant proteases resistant to competitive reversible inhibitors of HIV-1 protease, based on enzyme-substrate interactions and with FDA approval. The inhibition potencies of irreversible inhibitors are less sensitive to mutations so as to inactivate the protein completely by stronger covalent interactions. The development of new irreversible protease inhibitors might be interesting to deal with the future handling of HIV. The mechanisms and binding modes of aziridine based inhibitors have been explored in the present investigations usingin-silicoapproaches: (i) ConfGGS towards structure minimization of model aziridine based inhibitors (ii) Molecular Docking towards predicting the best match between model aziridine based inhibitors and HIV-1 PR (iii) Covalent Docking towards exploring the binding affinity for the covalent interaction between model aziridine based inhibitors and HIV-1 PR (iv) MD Simulation of free enzyme HIV-1 PR and complex with the model aziridine based inhibitors to test and check the quality for the description of inhibition process (v) QM/MM computation to understand the inhibition potency and inhibition reaction at molecular level. Furthermore, ConfGGS/CHARMM has also been used to optimize the reactants and products, obtained from QM/MM computations. The correlation coefficient (R2) values for the dihedral angles of the near optimal structures and QM/MM obtained structures, have been computed and compared for the accuracy and efficacy. The computed results may help and provide assistance for experimental optimizations towards design of more potent protease inhibitors.