Quantitative structure–activity relationship (QSAR) study of interleukin-1 receptor associated kinase 4 (IRAK-4) inhibitor activity by the genetic algorithm and multiple linear regression (GA-MLR) method

References

• Janssens S, Beyaert R. Functional diversity and regulation of different interleukin-1 receptor-associated kinase (IRAK) family members. Mol Cell 2003;11:293–302.
   PubMed Web of Science ®Google Scholar
• Li S, Strelow A, Fontana EJ, Wesche H. IRAK-4: A novel member of the IRAK family with the properties of an IRAK-kinase. Proc Natl Acad Sci USA 2002;99:5567–5572.
   PubMed Web of Science ®Google Scholar
• Medvedev AE, Lentschat A, Kuhns DB, Blanco JC, Salkowski C, Zhang S, Arditi M, Gallin JI, Vogel SN. Distinct mutations in IRAK-4 confer hyporesponsiveness to lipopolysaccharide and interleukin-1 in a patient with recurrent bacterial infections. J Exp Med 2003;198:521–531.
   PubMed Web of Science ®Google Scholar
• Picard C, Puel A, Bonnet M, Ku CL, Bustamante J, Yang K, Soudais C, Dupuis S, Feinberg J, Fieschi C, Elbim C, Hitchcock R, Lammas D, Davies G, Al- Ghonaium A, Al-Rayes H, Al-Jumaah S, Al-Hajjar S, Al-Mohsen IZ, Frayha HH, Rucker R, Hawn TR, Aderem A, Tufenkeji H, Haraguchi S, Day NK, Good RA, Gougerot-Pocidalo MA, Cassanova JL. Pyogenic bacterial infections in humans with IRAK-4 deficiency. Science 2003;299:2076–2079.
   PubMed Web of Science ®Google Scholar
• Li X. IRAK4 in TLR/IL-1R signaling: possible clinical applications. Eur J Immunol 2008;38:614–618.
   PubMed Web of Science ®Google Scholar
• Buckley GM, Ceska TA, Fraser JL, Gowers L, Groom CR, Higueruelo AP, Jenkins K, Mack SR, Morgan T, Parry DM, Pitt WR, Rausch O, Richard MD, Sabin V. IRAK-4 inhibitors. Part II: A structure-based assessment of imidazo[1,2-a]pyridine binding. Bioorg Med Chem Lett 2008;18:3291–3295.
   PubMed Web of Science ®Google Scholar
• Buckley GM, Fosbeary R, Fraser JL, Gowers L, Higueruelo AP, James LA, Jenkins K, Mack SR, Morgan T, Parry DM, Pitt WR, Rausch O, Richard MD, Sabin V. IRAK-4 inhibitors. Part III: A series of imidazo[1,2-a]pyridines. Bioorg Med Chem Lett 2008;18:3656–3660.
   PubMed Web of Science ®Google Scholar
• Buckley GM, Gowers L, Higueruelo AP, Jenkins K, Mack SR, Morgan T, Parry DM, Pitt WR, Rausch O, Richard MD, Sabin V, Fraser JL. IRAK-4 inhibitors. Part 1: a series of amides. Bioorg Med Chem Lett 2008;18:3211–3214.
   PubMed Web of Science ®Google Scholar
• Sammes PG, Taylor JB. Comprehensive Medicinal Chemistry. Oxford: Pergamon Press, 1990:766.
   Google Scholar
• Riahi S, Pourbasheer E, Dinarvand R, Ganjali MR, Norouzi P. Quantitative structure-activity relationship study on the anti-HIV-1 activity of novel 6-naphthylthio HEPT analogs. Chem Biol Drug Des 2008;74:165–172.
   Web of Science ®Google Scholar
• Riahi S, Pourbasheer E, Ganjali MR, Norouzi P. Investigation of different linear and nonlinear chemometric methods for modeling of retention index of essential oil components: Concerns to support vector machine. J Hazard Mater 2009;166:853–859.
   PubMed Web of Science ®Google Scholar
• Riahi S, Pourbasheer E, Ganjali MR, Norouzi P. Support vector machine-based quantitative structure-activity relationship study of cholesteryl ester transfer protein inhibitors. Chem Biol Drug Des 2009;73:558–571.
   PubMed Web of Science ®Google Scholar
• Depczynski U, Frost VJ, Molt K. Genetic algorithms applied to the selection of factors in principal component regression. Anal Chim Acta 2000;420:217.
   Web of Science ®Google Scholar
• Alsberg BK, Marchand-Geneste N, King RD. A new 3D molecular structure representation using quantum topology with application to structure-property relationships. Chemometr Intel Lab 2000;54:75–91.
   Web of Science ®Google Scholar
• Jouanrimbaud D, Massart DL, Leardi R, Denoord OE. Genetic algorithms as a tool for wavelength selection in multivariate calibration. Anal Chem 1995;67:4295–4301.
   Web of Science ®Google Scholar
• Riahi S, Ganjali MR, E Pourbasheer Divsar, F, Norouzi P, Chaloosi M. Development and validation of a rapid chemometrics-assisted spectrophotometry and liquid chromatography methods for the simultaneous determination of the phenylalanine, tryptophan and tyrosine in the pharmaceutical products. Curr Pharm Anal 2008;4:231–237.
   Web of Science ®Google Scholar
• Riahi S, Ganjali MR, Pourbasheer E, Norouzi P. QSRR study of GC retention indices of essential-oil compounds by multiple linear regression with a genetic algorithm. Chromatographia 2008;67:917–922.
   Web of Science ®Google Scholar
• Riahi S, Pourbasheer E, Ganjali MR, Norouzi P, Zeraatkar Moghaddam A. QSPR study of the distribution coefficient property for hydantoin and 5-arylidene derivatives. A genetic algorithm application for the variable selection in the MLR and PLS methods. J Chin Chem Soc 2008;55:1086–1093.
   Web of Science ®Google Scholar
• Riahi S, Ganjali MR, Moghaddam AB, Pourbasheer E, Norouzi P. Development of a new combined chemometrics method, applied in the simultaneous voltammetric determination of cinnamic acid and 3, 4-dihydroxy benzoic acid. Curr Anal Chem 2009;5:42–47.
   Web of Science ®Google Scholar
• Tropsha A, Gramatica P, Gombar VK. The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models. QSAR Comb Sci 2003;22:69–77.
   Google Scholar
• Riahi S, Ganjali MR, Norouzi P, Jafari F. Application of GA-MLR, GA-PLS and the DFT quantum mechanical (QM) calculations for the prediction of the selectivity coefficients of a histamine-selective electrode. Sens. Actuators B 2008;132:13–19.
   Web of Science ®Google Scholar
• Eriksson L, Johansson E, Muller M, Wold S. On the selection of the training set in environmental QSAR analysis when compounds are clustered. J Chemometr 2000;14:599–616.
   Web of Science ®Google Scholar
• Golbraikh A, Shen M, Xiao Z, Xiao Y-D Lee, K-H, Tropsha A. Rational selection of training and test sets for the development of validated QSAR models. J Comput Aided Mol Des 2003;17:241–253.
   PubMed Web of Science ®Google Scholar
• Gramatica P, Pilutti P, Papa E. Validated QSAR prediction of OH tropospheric degradability: splitting into training-test set and consensus modeling. 2004;44:1794–1802.
   Google Scholar
• Riahi S, Pourbasheer E, Dinarvand R, Ganjali MR, Norouzi P. Exploring QSARs for antiviral activity of 4-alkylamino-6-(2-hydroxyethyl)-2-methylthiopyrimidines by support vector machine. Chem Biol Drug Des 2008;72:205–216.
   PubMed Web of Science ®Google Scholar
• Riahi S, Pourbasheer E, Dinarvand R, Ganjali MR, Norouzi P. QSAR Study of 2-(1-Propylpiperidin-4-yl)-1H-Benzimidazole-4-Carboxamide as PARP Inhibitors for Treatment of Cancer. Chem Biol Drug Des 2008;72:575–584.
   PubMed Web of Science ®Google Scholar
• Stewart JPP. MOPAC 6.0: Quantum Chemistry Program Exchange QCPE. No. 455. Bloomington, IN:Indiana University, 1989;250–260.
   Google Scholar
• Katritzky AR. http://www.codessa-pro.com.
   Google Scholar
• Todeschini R, Consonni V, Pavana M. http://www.disat.unimib.it/chm/.
   Google Scholar
• Holland H. Adaption in Natural and Artificial Systems. Ann Arbor, MI: The University of Michigan, 1975;342–375.
   Google Scholar
• Cartwright HM. Applications of Artificial Intelligence in Chemistry. Oxford: Oxford University, 1993;760–765.
   Google Scholar
• Hunger J, Huttner G. Optimization and analysis of force field parameters by combination of genetic algorithms and neural networks. J Comput Chem 1999;20:455–471.
   Web of Science ®Google Scholar
• Ahmad S, Gromiha MM. Design and training of a neural network for predicting the solvent accessibility of proteins. J Comput Chem 2003;24:1313–1320.
   PubMed Web of Science ®Google Scholar
• Waller CL, Bradley MP. Development and validation of a novel variable selection technique with application to multidimensional quantitative structure-activity relationship studies. J Chem Inf Comput Sci 1999;39:345–355.
   Google Scholar
• Aires-de-Sousa J, Hemmer MC, Casteiger J. Prediction of H-1 NMR chemical shifts using neural networks. Anal Chem 2002;74:80–90.
   PubMed Web of Science ®Google Scholar
• The Mathworks. Genetic Algorithm and Direct Search Toolbox Users Guide. Massachusetts: MathWorks, 2002;50–65.
   Google Scholar
• Agrawal VK, Khadikar PV. QSAR prediction of toxicity of nitrobenzenes. Bioorg Med Chem 2001;9:3035–3040.
   PubMed Web of Science ®Google Scholar
• OECD. Guidance Document on the Validation of (Quantitative) Structure–Activity Relationships [(Q)SAR] Models. Paris: Organisation for Economic Co-Operation and Development, 2007;256–278.
   Google Scholar
• Netzeva TI, Worth AP, Aldenberg T, Benigni R, Cronin MTD, Gramatica P, Jaworska JS, Kahn S, Klopman G, CA Marchant Myatt, G, Nikolova- Jeliazkova N, Patlewicz GY, Perkins R, Roberts DW, Schultz TW, Stanton DT, van de Sandt JJM, Tong W, Veith G, Yang C. Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop 52. ATLA-Altern Lab Anim 2005;33:155–173.
   PubMed Web of Science ®Google Scholar
• Eriksson L, Jaworska J, Worth AP, Cronin MTD, McDowell RM, Gramatica P. Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs. Environ Health Perspect 2003;111:1361–1375.
   PubMed Web of Science ®Google Scholar
• Jaworska JS, Nikolova JN, Aldenberg T. QSAR applicability domain estimation by projection of the training set in descriptor space: A review. ATLA-Altern Lab Anim 2005;33:445–459.
   PubMed Web of Science ®Google Scholar
• Todeschini R, Consonni V. Handbook of Molecular Descriptors. Weinheim, Germany: Wiley-VCH, 2000;1–667.
   Google Scholar