Monte Carlo sampling and multivariate adaptive regression splines as tools for QSAR modelling of HIV-1 reverse transcriptase inhibitors

References

• Cihlar , T and Ray , AS . 2010 . Nucleoside and nucleotide HIV reverse transcriptase inhibitors: 25 years after zidovudine . Antivir. Res. , 85 : 39 – 58 .
   PubMed Web of Science ®Google Scholar
• De Clercq , E . 2004 . HIV-chemotherapy and –prophylaxis: New drugs, leads and approaches . Int. J. Biochem. Cell. Biol. , 36 : 1800 – 1822 .
   PubMed Web of Science ®Google Scholar
• De Clercq , E . 2009 . Anti-HIV drugs: 25 compounds approved within 25 years after the discovery of HIV . Inter. J. Antimicrob. Ag. , 33 : 307 – 320 .
   PubMed Web of Science ®Google Scholar
• de Bethune , M . 2010 . Non-nucleoside reverse transcriptase inhibitors (NNRTIs), their discovery, development, and use in treatment of HIV-1 infection: A review of the last 20 years (1989–2009) . Antivir. Res. , 85 : 75 – 90 .
   PubMed Web of Science ®Google Scholar
• Ahgren , C , Backro , K , Bell , FW , Cantrell , AS , Clemens , M , Colacino , JM , Deeter , JB , Engelhardt , JA , Hogberg , M , Jaskunas , SR and Johanssons , NG . 1995 . The PETT series, a new class of potent nonnucleoside inhibitors of human immunodeficiency virus type 1 reverse transcriptase . Antimicrob. Agents Chemother. , 39 : 1329 – 1335 .
   PubMed Web of Science ®Google Scholar
• Pauwels , R , Andries , K , Desmyter , J , Schols , D , Kukla , MJ , Breslin , HJ , Raeymaeckers , A , Van Gelder , J , Woestenborghs , R and Heykants , J . 1990 . Potent and selective inhibition of HIV-1 replication in vitro by a novel series of TIBO derivatives . Nature , 343 : 470 – 474 .
   PubMed Web of Science ®Google Scholar
• Baba , M , Tanakas , H , De Clercq , E , Pauwels , R , Balzarini , J , Schols , D , Nakashima , H , Perno , CF , Walker , RT and Miyasaka , T . 1989 . Highly specific inhibition of human immunodeficiency virus type 1 by a novel 6-substituted acyclouridine derivative . Biochem. Biophys. Res. Commun. , 165 : 1375 – 1381 .
   PubMed Web of Science ®Google Scholar
• Kleim , JP , Bender , R , Billhardt , UM , Meichsner , C , Riess , G , Rosner , M , Winkler , I and Paessens , A . 1993 . Activity of a novel quinoxaline derivative against human immunodeficiency virus type 1 reverse transcriptase and viral replication . Antimicrob. Agents Chemother. , 37 : 1659 – 1664 .
   PubMed Web of Science ®Google Scholar
• Balzarini , J , Pérez-Pérez , MJ , San-Felix , A , Schols , D , Perno , DCF , Vandamme , A , Camarasa , MJ and De Clercq , E . 1992 . 2′,5′-Bis-O-(tert-butyldimethylsilyl)-30-spiro-5′-4′-amino-1′,2′-oxathiole-2′,2′-dioxide) pyrimidine (TSAO) nucleoside analogues: Highly selective inhibitors of human immunodeficiency virus type 1 that are targeted at the viral reverse transcriptase . Proc. Natl. Acad. Sci. U.S.A. , 89 : 4392 – 4396 .
   PubMed Web of Science ®Google Scholar
• Ren , J and Stammers , DK . 2008 . Structural basis for drug resistance mechanism for non-nucleoside inhibitors of HIV reverse transcriptase . Virus Res. , 134 : 157 – 170 .
   PubMed Web of Science ®Google Scholar
• Pungpo , P , Saparpakorn , P , Wolschann , P and Hannongbua , S . 2006 . Computer-aided molecular design of highly potent HIV-1 RT inhibitors: 3D QSAR and molecular docking studies of efavirenz derivatives . SAR QSAR Environ. Res. , 17 : 353 – 370 .
   PubMed Web of Science ®Google Scholar
• Chen , HF , Yao , XJ , Li , Q , Yuan , SG , Panaye , A , Doucet , JP and Fan , BT . 2003 . Comparative study of non nucleoside inhibitors with HIV-1 reverse transcriptase based on 3D-QSAR and docking . SAR QSAR Environ. Res. , 14 : 455 – 474 .
   PubMed Web of Science ®Google Scholar
• Vadivelan , S , Deeksha , TN , Arun , S , Machiraju , PK , Gundla , R , Sinha , BN and Jagarlapudi , SARP . 2011 . Virtual screening studies on HIV-1 reverse transcriptase inhibitors to design potent leads . Eur. J. Med. Chem. , 46 : 851 – 859 .
   Web of Science ®Google Scholar
• Goodarzi , M and Freitas , MP . 2010 . MIA–QSAR coupled to principal component analysis-adaptive neuro-fuzzy inference systems (PCA–ANFIS) for the modelling of the anti-HIV reverse transcriptase activities of TIBO derivatives . Eur. J. Med. Chem. , 45 : 1352 – 1358 .
   PubMed Web of Science ®Google Scholar
• Sapre , NS , Pancholi , N , Gupta , S and Sapre , N . 2008 . Computational modeling of tetrahydroimidazo[4,5,1-jk][1,4]-benzodiazepinone derivatives: An atomistic drug design approach using Kier-Hall electrotopological state (E-state) indices . J. Comp. Chem. , 29 : 1699 – 1706 .
   PubMed Web of Science ®Google Scholar
• Duchowicz , PR , Fernandez , M , Caballero , J , Castro , EA and Fernandez , FM . 2006 . QSAR for non-nucleoside inhibitors of HIV-1 reverse transcriptase . Bioorg. Med. Chem. , 14 : 5876 – 5889 .
   PubMed Web of Science ®Google Scholar
• Medina-Franco , JL , Golbraikh , A , Oloff , S , Castillo , R and Tropsha , A . 2005 . Quantitative structure activity relationship analysis of pyridinone HIV-1 reverse transcriptase inhibitors using the k nearest neighbor method and QSAR-based database mining . J. Comput.-Aid. Mol. Des. , 19 : 229 – 242 .
   PubMed Web of Science ®Google Scholar
• Xu , QS , Daszykowski , M , Walczak , B , Daeyaert , F , de Jonge , MR , Heeres , J , Koymans , LMH , Lewi , PJ , Vinkers , HM , Janssen , PA and Massart , DL . 2004 . Multivariate adaptive regression splines – studies of HIV reverse transcriptase inhibitors . Chemom. Intell. Lab. Syst. , 72 : 27 – 34 .
   Web of Science ®Google Scholar
• Pungpo , P , Punkvang , A , Saparpakorn , P , Wolschann , P and Hannongbua , S . 2009 . Recent advances in NNRTI design: Computer-aided molecular design approaches . Curr. Comput.-Aid. Drug Des. , 5 : 174 – 199 .
   Web of Science ®Google Scholar
• Cruz-Monteagudo , M , PhamThe , H , Cordeiro , MNDS and Borges , F . 2010 . Prioritizing hits with appropriate trade-offs between HIV-1 reverse transcriptase inhibitory efficacy and MT4 blood cells toxicity through desirability-based multiobjective optimization and ranking . Mol. Inform. , 29 : 303 – 321 .
   Web of Science ®Google Scholar
• Distinto , S , Esposito , F , Kirchmair , J , Cardia , CM , Maccioni , E , Alcaro , S , Zinzula , L and Tramontano , E . 2011 . Identification of HIV-1 reverse transcriptase dual inhibitors by a combined shape-, 2D-fingerprint- and pharmacophore-based virtual screening approach . Antivir. Res. , 90 : A21 – A78 .
   Google Scholar
• Wang , Z , Tang , J , Salomon , CE , Dreis , CD and Vince , R . 2010 . Pharmacophore and structure–activity relationships of integrase inhibition, within a dual inhibitor scaffold of HIV reverse transcriptase and integrase . Bioorg. Med. Chem. , 18 : 4202 – 4211 .
   Web of Science ®Google Scholar
• Angeli , L , Bellucci , L and Botta , M . 2010 . Use of docking, cross docking and molecular dynamic simulations to rationalize the activity data of some S-dabos on wild-type and three mutant strains of reverse transcriptase . J. Biotech. , 150 : 105 – 106 .
   Web of Science ®Google Scholar
• Li , H , Li , C , Gui , C , Luo , X , Chen , K , Shen , J , Wang , X and Jiang , H . 2004 . GAsDock: A new approach for rapid flexible docking based on an improved multi-population genetic algorithm . Bioorg. Med. Chem. Lett. , 14 : 4671 – 4676 .
   Web of Science ®Google Scholar
• Darnag , R , Mazouz , ELM , Schmitzer , A , Villemin , D , Jarid , A and Cherqaoui , D . 2010 . Support vector machines: Development of QSAR models for predicting anti-HIV-1 activity of TIBO derivatives . Eur. J. Med. Chem. , 45 : 1590 – 1597 .
   PubMed Web of Science ®Google Scholar
• Hua , R , Doucet , J , Delamar , M and Zhang , R . 2009 . QSAR models for 2-amino-6-arylsulfonylbenzonitriles and congeners HIV-1 reverse transcriptase inhibitors based on linear and nonlinear regression methods . Eur. J. Med. Chem. , 44 : 2158 – 2171 .
   Web of Science ®Google Scholar
• O’Meara , JA , Jakalian , A , LaPlante , S , Bonneau , PR , Coulombe , R , Faucher , AM , Guse , I , Landry , S , Racine , J , Simoneau , B , Thavonekham , B and Yoakim , C . 2007 . Scaffold hopping in the rational design of novel HIV-1 non-nucleoside reverse transcriptase inhibitors . Bioorg. Med. Chem. Lett. , 17 : 3362 – 3366 .
   PubMed Web of Science ®Google Scholar
• Ranise , A , Spallarossa , A , Cesarini , S , Bondavalli , F , Schenone , S , Bruno , O , Menozzi , G , Fossa , P , Mosti , L , Colla , ML , Sanna , G , Murreddu , M , Collu , G , Busonera , B , Marongiu , ME , Pani , A , Colla , PL and Loddo , R . 2005 . Structure-based design, parallel synthesis, structure−activity relationship, and molecular modeling studies of thiocarbamates, new potent non-nucleoside HIV-1 reverse transcriptase inhibitor isosteres of phenethylthiazolylthiourea derivatives . J. Med. Chem. , 48 : 3858 – 3873 .
   PubMed Web of Science ®Google Scholar
• Veelenturf , LPJ . 1995 . Analysis and Applications of Artificial Neural Networks , 2 – 5 . London : Prentice Hall International .
   Google Scholar
• Christianini , N and Shawe-Taylor , J . 2000 . An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods , Cambridge : Cambridge University Press .
   Google Scholar
• Barakat , N and Bradley , AP . 2010 . Rule extraction from support vector machines . Neurocomputing , 74 : 178 – 190 .
   Web of Science ®Google Scholar
• Tu , JV . 1996 . Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes . J. Clin. Epidemiol. , 49 : 1225 – 1231 .
   PubMed Web of Science ®Google Scholar
• Friedman , JH . 1991 . Multivariate adaptive regression splines . Ann. Stat. , 19 : 1 – 141 .
   Web of Science ®Google Scholar
• Jalali-Heravi , M and Mani-Varnosfaderani , A . 2009 . QSAR modeling of 1-(3,3-diphenylpropyl)-piperidinyl amides as CCR5 modulators using multivariate adaptive regression spline and Bayesian regularized genetic neural networks . QSAR Comb. Sci. , 9 : 946 – 958 .
   Google Scholar
• Kalos , MH and Whitlock , PA . 2008 . Monte Carlo Methods , 1 – 5 . Weinheim : Wiley-VCH .
   Google Scholar
• Deming , SN and Morgan , SL . 1994 . Experimental Design: A Chemometric Approach , 1 – 20 . Amsterdam : Elsevier Science .
   Google Scholar
• Pauwels , R , Balzarini , J , Baba , M , Snoeck , R , Schols , D , Herdewijn , P , Desmyter , J and De Clercq , E . 1988 . Rapid and automated tetrazolium-based colorimetric assay for the detection of anti-HIV compounds . J. Virol. Methods , 20 : 309 – 321 .
   PubMed Web of Science ®Google Scholar
• Pannecouque , C , Daelemans , D and Clercq , EDe . 2008 . Tetrazolium-based colorimetric assay for the detection of HIV replication inhibitors: revisited 20 years later, Nat. Protoc. 3 , : 427 – 434 .
   Google Scholar
• Hypercube, Inc., HyperChem; software available at http://www.hyper.com (accessed 2011)
   Google Scholar
• Todeschini , R , Consonni , V , Mauri , A and Pavan , M . Dragon software: calculation of molecular descriptors, Department of Environmental Sciences, University of Milano–Bicocca and Talete SRL; software available at http://disat.unimib.it/chm/Dragon (accessed 2011)
   Google Scholar
• Skolnick , J and Kolinski , A . 1991 . Dynamic Monte Carlo simulations of a new lattice model of globular protein folding, structure and dynamics . J. Mol. Biol. , 221 : 499 – 531 .
   PubMed Web of Science ®Google Scholar
• Agrawal , NJ and Radhakrishnan , R . 2007 . The role of glycocalyx in nanocarrier-cell adhesion investigated using a thermodynamic model and Monte Carlo simulations . J. Phys. Chem. C, , 111 : 15848 – 15856 .
   Web of Science ®Google Scholar
• MATLAB 7.4; software available at http://www.mathworks.com/products/matlab (accessed 2011)
   Google Scholar
• Jekabsons , G . ARESLab: Adaptive regression splines toolbox for Matlab/Octave, version 1.5.1, Institute of Applied Computer Systems, Riga Technical University, 2011; software available at http://www.cs.rtu.lv/jekabsons/regression.html (accessed 2011)
   Google Scholar
• Arteca , GA . 2007 . “ Molecular shape descriptors ” . In Review in Computational Chemistry , Edited by: Lipkowitz , BK and Boyd , D . Vol. 9 , 191 – 253 . New York : VCH .
   Google Scholar
• Hadarug , DI . 2011 . Natural and synthetic HIV-1 non-nucleoside reverse transcriptase inhibitors: A theoretical approach . J. Agro. Process. Technol. , 17 : 360 – 370 .
   Google Scholar
• Karelson , M and Lobanov , VS . 1996 . Quantum-chemical descriptors in QSAR/QSPR studies . Chem. Rev. , 96 : 1027 – 1043 .
   PubMed Web of Science ®Google Scholar
• Wise , SA , Bonnet , WJ , Guenther , FR and May , WE . 1981 . A relationship between reversed-phase C18 liquid chromatographic retention and shape of polycyclic aromatic hydrocarbons . J. Chromatogr. Sci. , 19 : 457 – 465 .
   Web of Science ®Google Scholar
• Schultz , HP , Schultz , EB and Schultz , TP . 1993 . Topological organic chemistry 7, Graph theory, matrix permanents, and topological indices of unsaturated and aromatic hydrocarbons . J. Chem. Inf. Comput. Sci. , 33 : 863 – 867 .
   Google Scholar
• Todeschini , R and Consonni , V . 2000 . Handbook of Molecular Descriptors. Methods and Principles in Medicinal Chemistry , Weinheim : Wiley-VCH .
   Google Scholar
• Osten , DW . 1988 . Selection of optimal regression models via cross-validation . J. Chemom. , 2 : 39 – 48 .
   Google Scholar
• Wold , S . 1991 . Validation of QSARs . Quant. Struct. Act. Relat. , 10 : 191 – 193 .
   Google Scholar
• Golbraikh , A and Tropsha , A . 2002 . Be aware of q2 . J. Mol. Graph. Model. , 20 : 269 – 276 .
   PubMed Web of Science ®Google Scholar
• Hawkins , DM and Kraker , J . 2010 . Deterministic fallacies and model validation . J. Chemom. , 24 : 188 – 193 .
   Web of Science ®Google Scholar
• Jaworska , J and Eriksson , L . 2005 . QSAR applicability domain estimation by projection of the training set in descriptor space: A review . ATLA , 33 : 445 – 459 .
   Google Scholar
• Weaver , S and Gleeson , MP . 2008 . The importance of the domain of applicability in QSAR modelling . J. Mol. Graph. Model. , 26 : 1315 – 1326 .
   PubMed Web of Science ®Google Scholar
• Breiman , L , Friedman , JH , Olshen , RA and Stone , CJ . 1984 . Classification and Regression Trees , Monterey , IL : Wadsworth .
   Google Scholar
• Leardi , R and Gonzales , AL . 1998 . Genetic algorithms applied to feature selection in PLS regression: How and when to use them . Chemom. Intell. Lab. Syst. , 41 : 195 – 207 .
   Web of Science ®Google Scholar
• Jalali-Heravi , M and Shahbazikhah , P . 2008 . Quantitative structure–mobility relationship study of a diverse set of organic acids using classification and regression trees and adaptive neuro-fuzzy inference systems . Electrophoresis , 29 : 363 – 374 .
   PubMed Web of Science ®Google Scholar