Literature DB >> 16766190

QSAR for non-nucleoside inhibitors of HIV-1 reverse transcriptase.

Pablo R Duchowicz1, Michael Fernández, Julio Caballero, Eduardo A Castro, Francisco M Fernández.   

Abstract

By means of QSAR algorithms we model the potency pIC(90) [mM] of 154 non-nucleoside reverse transcriptase inhibitors (NNRTI) of the wild-type HIV-1 virus, considered as the second generation analogues of Efavirenz. In addition, 56 inhibitors of the K-103N viral mutant form are also investigated. A pool of 1494 theoretical molecular descriptors provided mainly by the Dragon 5 software is explored by several methods of variable selection: forward stepwise regression, the replacement method, and the genetic algorithm approach. The optimal models found include up to seven parameters: R = 0.7991, R(l-20%-o) = 0.7233 for the case of wild-type, and R = 0.9261, R(l-5%-o) = 0.8802 for the K-103N mutation.

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Year:  2006        PMID: 16766190     DOI: 10.1016/j.bmc.2006.05.027

Source DB:  PubMed          Journal:  Bioorg Med Chem        ISSN: 0968-0896            Impact factor:   3.641


  6 in total

1.  QSAR analysis on tacrine-related acetylcholinesterase inhibitors.

Authors:  Kai Y Wong; Andrew G Mercader; Laura M Saavedra; Bahareh Honarparvar; Gustavo P Romanelli; Pablo R Duchowicz
Journal:  J Biomed Sci       Date:  2014-09-20       Impact factor: 8.410

2.  Alignment independent 3D-QSAR, quantum calculations and molecular docking of Mer specific tyrosine kinase inhibitors as anticancer drugs.

Authors:  Fereshteh Shiri; Somayeh Pirhadi; Jahan B Ghasemi
Journal:  Saudi Pharm J       Date:  2015-03-31       Impact factor: 4.330

3.  Flavonoids as vasorelaxant agents: synthesis, biological evaluation and quantitative structure activities relationship (QSAR) studies.

Authors:  Xiaowu Dong; Yanming Wang; Tao Liu; Peng Wu; Jiadi Gao; Jianchao Xu; Bo Yang; Yongzhou Hu
Journal:  Molecules       Date:  2011-09-28       Impact factor: 4.411

4.  Chi-MIC-share: a new feature selection algorithm for quantitative structure-activity relationship models.

Authors:  Yuting Li; Zhijun Dai; Dan Cao; Feng Luo; Yuan Chen; Zheming Yuan
Journal:  RSC Adv       Date:  2020-05-27       Impact factor: 4.036

Review 5.  QSPR studies on aqueous solubilities of drug-like compounds.

Authors:  Pablo R Duchowicz; Eduardo A Castro
Journal:  Int J Mol Sci       Date:  2009-06-03       Impact factor: 6.208

6.  Improvement of the Prediction Power of the CoMFA and CoMSIA Models on Histamine H3 Antagonists by Different Variable Selection Methods.

Authors:  Jahan B Ghasemi; Hossein Tavakoli
Journal:  Sci Pharm       Date:  2012-05-24
  6 in total

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