Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Docking mode of delvardine and its analogues into the p66 domain of HIV-1 reverse transcriptase: screening using molecular mechanics-generalized born/surface area and absorption, distribution, metabolism and excretion properties.

Delvardine and its structural derivatives are important non-nucleoside HIV-1 reverse transcriptase inhibitors (NNRTIs). In this work,15 delvardine analogues were studied. A free energy-of-binding (FEB)expression was developed in the form of an optimized linear combination of van der Waal (vdW), electrostatic, solvation and solvent-accessible surface area (SASA) energy terms. The solvation energy terms estimated by generalized born/surface area (GB/SA) play an important role in predicting the binding affinity of delvardine analogues. Out of 15 derivatives, substitution of CH3 with H at the Y and R positions, as well as substitution of SO2CH3 with only CH2 at the Z position in S2, S8 and S12 analogues, were found to be the most potent (glide score = -7.60, -8.06 and -7.44; pIC50 =7.28, 7.37 and 7.64) in comparison with the template delvardine (which is used currently as the drug candidate). All the three analogues also passed the absorption, distribution,metabolism and excretion (ADME) screening and Lipinski's rule of 5, and have the potential to be used for second-generation drug development. The work demonstrates that dock molecular mechanics-generalized born/surface area (MM-GB/SA-ADME) is a promising approach to predict the binding activity of ligands to the receptor and further screen for a successful candidate drug in a computer-aided rational drug design.