Structural Information and Drug–Enzyme Interaction of the Non-Nucleoside Reverse Transcriptase Inhibitors Based on Computational Chemistry Approaches

  • Supa HannongbuaEmail author
Part of the Topics in Heterocyclic Chemistry book series (TOPICS, volume 4)


Non-nucleoside reverse transcriptase inhibitors, such as nevirapine, TIBO, HEPT, and efavirenz, are very specific to HIV-1 reverse transcriptase and have few side effects compared to NRTIs. However, mutation of the HIV-1 virus has caused drug resistance to develop and reduce the efficiency of these inhibitors for drug therapy. As the association of NNRTIs with the binding pocket of the enzyme is essential for the inhibition process, this interaction is of high interest. Potential energy surface is used for conformational analysis of these flexible NNRTIs. The interactions between the inhibitor molecules and the surrounding amino acids are the key to determining the binding affinity. Much work has been done by using the 3D-QSAR method, with detailed molecular structural analysis of HIV-1 inhibitors by theoretical calculations, including enzyme–inhibitor interactions. Accurate calculations of detailed interactions are demonstrated by multilayered integration or ONIOM method to give some insight into the particular interaction of the NNRTIs with the residues in the binding site. In addition, molecular dynamics simulations, Monte-Carlo simulations and protein-based inhibitor design methods have been applied extensively on these inhibitors. This review is an attempt to combine various QSAR and CAMD methods on NNRTIs into a common prediction model to support the design of new, more potent inhibitors, in particular, active against mutant enzyme prior to synthesis.

Drug-enzyme interaction Molecular simulations Non-nucleoside  reverse transcriptase inhibitor ONIOM Quantum chemical calculations 



(+/ −)-2,6-Dichloro-α-[(2-acetyl-5-methylphenyl)amino]benzamide

2D, 3D

Two dimensional, three dimensional


Two-dimensional quantitative structure–activity relationships


Three-dimensional quantitative structure–activity relationships






Acquired immunodeficiency syndrome


AMBER force field


Artificial neural network






Aspartic acid


Beck's three-parameter exchange functional with Lee–Yang–Parr correlation


Computer-aided molecular design


Computational chemistry


Correlation-consistent polarized valence double zeta


Correlation-consistent polarized valence triple zeta


Comparative molecular field analysis


Comparative molecular similarity indexes analysis




Density functional theory




Deoxyribonucleic acid


Deoxynucleotide triphosphate


Median effective concentration


Free energy perturbation


Gauge-independent atomic orbital


Glutamic acid






Hartree–Fock theory




Human immunodeficiency virus type 1


Hologram quantitative structure–activity relationships


Median inhibitory concentration


Integrated molecular orbital molecular mechanics








Monte Carlo


Molecular dynamics


Molecular mechanics, Allinger force field version 3


Second-order Møller–Plesset perturbation theory


Human membrane type-4


Nuclear magnetic resonance


Non-nucleoside reverse transcriptase inhibitors


Nucleoside reverse transcriptase inhibitors


Our own N-layered integrated molecular orbital and molecular mechanics method


Peptide having molecular weight 51 kDA


Peptide having molecular weight 66 kDA


Pyrrolyl aryl sulfones


Pharmacophore-based database searching


Potential energy surface






Modified neglect of diatomic overlap, parametric method number 3




Quantum chemistry


Quantum mechanics and molecular mechanics


Quantum mechanics and quantum mechanics


Quantitative structure–activity relationships


Research Collaboratory for Structural Bioinformatics (RCSB), the non-profit consortium that manages the Protein Data Bank (PDB)


Ribonucleic acid


Ribonuclease H


Reverse transcriptase


Steric and electrostatic alignment




Selectivity index


Steered molecular dynamics


Substructural molecular fragments


Self-organizing map












Universal force field




Wild type


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The author thanks Prof. Gupta for his encouragement in writing this review and Prof. Wolschann for many useful suggestions. Financial support from the Thailand Research Fund (BRG4780007) and National Research Council of Thailand (1.AU 49/2547), Postgraduates on Education and Research on Petroleum and Petrochemical Technology and KURDI are gratefully acknowledged. Thanks are due to Patchareenart Saparpakorn for excellent assistance in preparation of the manuscript and to W.J. Holzschuh for reading the manuscript.


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Authors and Affiliations

  1. 1.Department of Chemistry, Faculty of ScienceKasetsart UniversityBangkokThailand

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