SAR and QSAR studies: Modelling of new DAPY derivatives

Thakur, Abhishek; Thakur, Mamta; Bharadwaj, Arpan; Thakur, Suprajnya

doi:10.1016/j.ejmech.2007.04.005

Cited by 10 publications

(1 citation statement)

References 11 publications

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“…Until now only one QSAR analysis was published by Thakur et al [16]; their study was limited to a 2D QSAR analysis and they didn't take into consideration the bioactive conformation of these molecules that adopt a butterfly-like conformation at the binding site of the protein [17]. So their obtained model doesn't reflect the conformational space of the inhibitor in the protein and it might not be suitable to elaborate new inhibitors with improved activity.…”

Section: Introductionmentioning

confidence: 97%

2D and 3D QSAR studies of diarylpyrimidine HIV-1 reverse transcriptase inhibitors

Rebehmed

Barbault

Teixeira

et al. 2008

J Comput Aided Mol Des

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2D and 3D QSAR studies were applied on a set of 28 diarylpyrimidine derivatives to model and understand their HIV-1 reverse transcriptase (RT) inhibitory activities. Special cares were taken to build our set of molecules according to their bioactive conformations which is crucial to elaborate good QSAR models. 2D QSAR was performed using the heuristic method in CODESSA which had led to a linear model (R (2) = 0.928 and s (2) = 0.015) between the inhibitory activity and five descriptors. CoMFA and CoMSIA models were established using SYBYL package of programs. The better predictive ability of the CoMSIA model (q (2) = 0.730) over the CoMFA model (q (2) = 0.597) was assigned to the large contribution of hydrogen-bonding interactions to the inhibitory activity. CoMSIA physicochemical properties are in agreement with the 2D QSAR descriptors. The CoMSIA PLS contour surfaces were mapped to the binding pocket of the RT and showed that the results obtained by the 2D and 3D models are in respect with the protein environment. This link permitted us to validate our model and give important insights for the structure activity interpretations. These results will guide further structural modification and prediction of new HIV-1 RT inhibitors.

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Section: Introductionmentioning

confidence: 97%

2D and 3D QSAR studies of diarylpyrimidine HIV-1 reverse transcriptase inhibitors

Rebehmed

Barbault

Teixeira

et al. 2008

J Comput Aided Mol Des

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Pyrimidine‐Based Kinase Inhibitors in Cancer Chemotherapy

Mah

2012

Bioactive Heterocyclic Compound Classes

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HIV‐1 NNRTIs: structural diversity, pharmacophore similarity, and impliations for drug design

Zhan

Chen

et al. 2011

Medicinal Research Reviews

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125

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Nonnucleoside reverse transcriptase inhibitors (NNRTIs) nowadays represent very potent and most promising anti-AIDS agents that specifically target the HIV-1 reverse transcriptase (RT). However, the effectiveness of NNRTI drugs can be hampered by rapid emergence of drug-resistant viruses and severe side effects upon long-term use. Therefore, there is an urgent need to develop novel, highly potent NNRTIs with broad spectrum antiviral activity and improved pharmacokinetic properties, and more efficient strategies that facilitate and shorten the drug discovery process would be extremely beneficial. Fortunately, the structural diversity of NNRTIs provided a wide space for novel lead discovery, and the pharmacophore similarity of NNRTIs gave valuable hints for lead discovery and optimization. More importantly, with the continued efforts in the development of computational tools and increased crystallographic information on RT/NNRTI complexes, structure-based approaches using a combination of traditional medicinal chemistry, structural biology, and computational chemistry are being used increasingly in the design of NNRTIs. First, this review covers two decades of research and development for various NNRTI families based on their chemical scaffolds, and then describes the structural similarity of NNRTIs. We have attempted to assemble a comprehensive overview of the general approaches in NNRTI lead discovery and optimization reported in the literature during the last decade. The successful applications of medicinal chemistry strategies, crystallography, and computational tools for designing novel NNRTIs are highlighted. Future directions for research are also outlined.

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SAR and QSAR studies: Modelling of new DAPY derivatives

Cited by 10 publications

References 11 publications

2D and 3D QSAR studies of diarylpyrimidine HIV-1 reverse transcriptase inhibitors

2D and 3D QSAR studies of diarylpyrimidine HIV-1 reverse transcriptase inhibitors

Pyrimidine‐Based Kinase Inhibitors in Cancer Chemotherapy

HIV‐1 NNRTIs: structural diversity, pharmacophore similarity, and impliations for drug design

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