Abstract
Background: Design of inhibitors for HIV-1 reverse transcriptase inhibition (HIV-1 RT) is one of the successful chemotherapies for the treatment of HIV infection. Among the inhibitors available for HIV-1 RT, non-nucleoside reverse transcriptase inhibitors (NNRTIs) have shown to be very promising and clinically approved drugs. However, the efficiency of many of these drugs has been reduced by the drug-resistant variants of HIV-1 RT. The aim of the current review is to provide a summary of lead optimization strategies from the 3D-QSARs studies on NNRTI class from the past 21 years (1995 to 2016).
Methods: The conformation dependent-alignment based (CoMFA and CoMSIA) methods have been proven very successful ligand based strategy in the drug design. Here, CoMFA and CoMSIA studies reported for structurally distinct NNRTIs including thiazolobenzimidazole, dipyridodiazepinone, 1,1,3-trioxo [1,2,4]-thiadiazine, formimidoester disulfides, thiocarbamate, thiazolidinone derivatives, etc. have been discussed in detail. In addition, we explore the position of the functional groups that drive the protein-ligand interaction.
Results: The structure-activity relationship (SAR) revealed from CoMFA and CoMSIA studies of these drug classes is not only in agreement with the structure-based method but also provides an efficient way of lead optimization. In addition to molecular docking experiments, protein-ligand interaction fingerprints were calculated in order to understand the common binding mode of NNRTI compounds.
Conclusion: Overall, this review enlightens the protein-ligand interactions with a detailed SAR discussion for chemotypes. Such discussion will help medicinal chemist to gain a better understanding for the design of novel and promising NNRTI candidates.
Keywords: HIV-1, reverse transcriptase, NNRTI, SAR, 3D-QSAR, CoMFA, CoMSIA.
Current Medicinal Chemistry
Title:HIV-1 Non-Nucleoside Reverse Transcriptase Inhibitors: SAR and Lead Optimization Using CoMFA and CoMSIA Studies (1995-2016)
Volume: 24 Issue: 34
Author(s): Murugesan Vanangamudi, Vasanthanathan Poongavanam and Vigneshwaran Namasivayam *
Affiliation:
- Pharmaceutical Institute, Pharmaceutical Chemistry I, University of Bonn, An der Immenburg 4, D-53121 Bonn,Germany
Keywords: HIV-1, reverse transcriptase, NNRTI, SAR, 3D-QSAR, CoMFA, CoMSIA.
Abstract: Background: Design of inhibitors for HIV-1 reverse transcriptase inhibition (HIV-1 RT) is one of the successful chemotherapies for the treatment of HIV infection. Among the inhibitors available for HIV-1 RT, non-nucleoside reverse transcriptase inhibitors (NNRTIs) have shown to be very promising and clinically approved drugs. However, the efficiency of many of these drugs has been reduced by the drug-resistant variants of HIV-1 RT. The aim of the current review is to provide a summary of lead optimization strategies from the 3D-QSARs studies on NNRTI class from the past 21 years (1995 to 2016).
Methods: The conformation dependent-alignment based (CoMFA and CoMSIA) methods have been proven very successful ligand based strategy in the drug design. Here, CoMFA and CoMSIA studies reported for structurally distinct NNRTIs including thiazolobenzimidazole, dipyridodiazepinone, 1,1,3-trioxo [1,2,4]-thiadiazine, formimidoester disulfides, thiocarbamate, thiazolidinone derivatives, etc. have been discussed in detail. In addition, we explore the position of the functional groups that drive the protein-ligand interaction.
Results: The structure-activity relationship (SAR) revealed from CoMFA and CoMSIA studies of these drug classes is not only in agreement with the structure-based method but also provides an efficient way of lead optimization. In addition to molecular docking experiments, protein-ligand interaction fingerprints were calculated in order to understand the common binding mode of NNRTI compounds.
Conclusion: Overall, this review enlightens the protein-ligand interactions with a detailed SAR discussion for chemotypes. Such discussion will help medicinal chemist to gain a better understanding for the design of novel and promising NNRTI candidates.
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Cite this article as:
Vanangamudi Murugesan , Poongavanam Vasanthanathan and Namasivayam Vigneshwaran*, HIV-1 Non-Nucleoside Reverse Transcriptase Inhibitors: SAR and Lead Optimization Using CoMFA and CoMSIA Studies (1995-2016), Current Medicinal Chemistry 2017; 24 (34) . https://dx.doi.org/10.2174/0929867324666170705122851
DOI https://dx.doi.org/10.2174/0929867324666170705122851 |
Print ISSN 0929-8673 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-533X |
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