Literature DB >> 16896545

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

Antreas Afantitis1, Georgia Melagraki, Haralambos Sarimveis, Panayiotis A Koutentis, John Markopoulos, Olga Igglessi-Markopoulou.   

Abstract

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

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Year:  2006        PMID： 16896545     DOI： 10.1007/s11030-005-9012-2

Source DB:  PubMed          Journal:  Mol Divers        ISSN： 1381-1991            Impact factor:   2.943


  17 in total

Review 1.  Recognizing molecules with drug-like properties.

Authors:  W P Walters; M A Murcko
Journal:  Curr Opin Chem Biol       Date:  1999-08       Impact factor: 8.822

2.  Application of predictive QSAR models to database mining: identification and experimental validation of novel anticonvulsant compounds.

Authors:  Min Shen; Cécile Béguin; Alexander Golbraikh; James P Stables; Harold Kohn; Alexander Tropsha
Journal:  J Med Chem       Date:  2004-04-22       Impact factor: 7.446

3.  Structure-activity correlation study of HIV-1 inhibitors: electronic and molecular parameters.

Authors:  S Hannongbua; L Lawtrakul; J Limtrakul
Journal:  J Comput Aided Mol Des       Date:  1996-04       Impact factor: 3.686

4.  A novel lead for specific anti-HIV-1 agents: 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine.

Authors:  T Miyasaka; H Tanaka; M Baba; H Hayakawa; R T Walker; J Balzarini; E De Clercq
Journal:  J Med Chem       Date:  1989-12       Impact factor: 7.446

5.  Predicting anti-HIV activity: computational approach using a novel topological descriptor.

Authors:  S Gupta; M Singh; A K Madan
Journal:  J Comput Aided Mol Des       Date:  2001-07       Impact factor: 3.686

6.  Use of artificial neural networks in a QSAR study of anti-HIV activity for a large group of HEPT derivatives.

Authors:  M Jalali-Heravi; F Parastar
Journal:  J Chem Inf Comput Sci       Date:  2000 Jan-Feb

Review 7.  Comparative QSAR based on neural networks for the anti-HIV activity of HEPT derivatives.

Authors:  L Douali; D Villemin; D Cherqaoui
Journal:  Curr Pharm Des       Date:  2003       Impact factor: 3.116

8.  Neural networks: Accurate nonlinear QSAR model for HEPT derivatives.

Authors:  Latifa Douali; Didier Villemin; Driss Cherqaoui
Journal:  J Chem Inf Comput Sci       Date:  2003 Jul-Aug

9.  Prediction of anti-HIV-1 activity of a series of tetrapyrrole molecules.

Authors:  Rozália Vanyúr; Károly Héberger; Judit Jakus
Journal:  J Chem Inf Comput Sci       Date:  2003 Nov-Dec

10.  Relative hydrophobicity and lipophilicity of beta-blockers and related compounds as measured by aqueous two-phase partitioning, octanol-buffer partitioning, and HPLC.

Authors:  Nellie Gulyaeva; Alexander Zaslavsky; Pamela Lechner; Michael Chlenov; Arnon Chait; Boris Zaslavsky
Journal:  Eur J Pharm Sci       Date:  2002-10       Impact factor: 4.384
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  10 in total

1.  A novel RBF neural network training methodology to predict toxicity to Vibrio fischeri.

Authors:  Georgia Melagraki; Antreas Afantitis; Haralambos Sarimveis; Olga Igglessi-Markopoulou; Alex Alexandridis
Journal:  Mol Divers       Date:  2006-06-27       Impact factor: 2.943

2.  A combined LS-SVM & MLR QSAR workflow for predicting the inhibition of CXCR3 receptor by quinazolinone analogs.

Authors:  Antreas Afantitis; Georgia Melagraki; Haralambos Sarimveis; Panayiotis A Koutentis; Olga Igglessi-Markopoulou; George Kollias
Journal:  Mol Divers       Date:  2009-05-30       Impact factor: 2.943

3.  Predictive QSAR workflow for the in silico identification and screening of novel HDAC inhibitors.

Authors:  Georgia Melagraki; Antreas Afantitis; Haralambos Sarimveis; Panayiotis A Koutentis; George Kollias; Olga Igglessi-Markopoulou
Journal:  Mol Divers       Date:  2009-02-10       Impact factor: 2.943

4.  CoMFA and CoMSIA analysis of 2,4-thiazolidinediones derivatives as aldose reductase inhibitors.

Authors:  Hong-Yan Liu; Shu-Shen Liu; Li-Tang Qin; Ling-Yun Mo
Journal:  J Mol Model       Date:  2009-01-09       Impact factor: 1.810

5.  Introducing catastrophe-QSAR. Application on modeling molecular mechanisms of pyridinone derivative-type HIV non-nucleoside reverse transcriptase inhibitors.

Authors:  Mihai V Putz; Marius Lazea; Ana-Maria Putz; Corina Duda-Seiman
Journal:  Int J Mol Sci       Date:  2011-12-20       Impact factor: 5.923

6.  Optimization of biaryl piperidine and 4-amino-2-biarylurea MCH1 receptor antagonists using QSAR modeling, classification techniques and virtual screening.

Authors:  Georgia Melagraki; Antreas Afantitis; Haralambos Sarimveis; Panayiotis A Koutentis; John Markopoulos; Olga Igglessi-Markopoulou
Journal:  J Comput Aided Mol Des       Date:  2007-03-22       Impact factor: 4.179

7.  Molecular Topology for the Search of New Anti-MRSA Compounds.

Authors:  Jose I Bueso-Bordils; Pedro A Alemán-López; Rafael Martín-Algarra; Maria J Duart; Antonio Falcó; Gerardo M Antón-Fos
Journal:  Int J Mol Sci       Date:  2021-05-29       Impact factor: 5.923

8.  Insight into the interactions between novel isoquinolin-1,3-dione derivatives and cyclin-dependent kinase 4 combining QSAR and molecular docking.

Authors:  Junxia Zheng; Hao Kong; James M Wilson; Jialiang Guo; Yiqun Chang; Mengjia Yang; Gaokeng Xiao; Pinghua Sun
Journal:  PLoS One       Date:  2014-04-10       Impact factor: 3.240

9.  Prediction and evaluation of the lipase inhibitory activities of tea polyphenols with 3D-QSAR models.

Authors:  Yi-Fang Li; Yi-Qun Chang; Jie Deng; Wei-Xi Li; Jie Jian; Jia-Suo Gao; Xin Wan; Hao Gao; Hiroshi Kurihara; Ping-Hua Sun; Rong-Rong He
Journal:  Sci Rep       Date:  2016-10-03       Impact factor: 4.379

10.  QSAR for RNases and theoretic-experimental study of molecular diversity on peptide mass fingerprints of a new Leishmania infantum protein.

Authors:  Humberto González-Díaz; María A Dea-Ayuela; Lázaro G Pérez-Montoto; Francisco J Prado-Prado; Guillermín Agüero-Chapín; Francisco Bolas-Fernández; Roberto I Vazquez-Padrón; Florencio M Ubeira
Journal:  Mol Divers       Date:  2009-07-04       Impact factor: 2.943
  10 in total

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