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QSAR study on hERG inhibitory effect of kappa opioid receptor antagonists by linear and non-linear methods

Medicinal Chemistry Research volume 22, pages 4047–4058 (2013)Cite this article

Abstract

The kappa opioid receptor antagonists have been studied for their quantitative structure–activity relationships. A dataset containing 45 inhibitors of the human ether-a-go–go voltage-gated ion-channel with known inhibitory was used. The whole dataset was divided into a training set and a test set based on of K-means clustering technique. Multiple linear regressions were employed to model the relationships between molecular descriptors and biologic activity of molecules using stepwise and genetic algorithm methods as variable selection tools. A comparison between the attained results indicated the superiority of the genetic algorithm over the stepwise multiple regression method in the feature selection. Support vector machine was also employed to model the non-linear structure–activity relationships. The models were validated using leave-one-out cross-validation, Y-randomization test, and applicability domain. The results showed that the linear model does not perform as well as the non-linear model in terms of predictive ability. The results suggest that the shape, relative negative charge, atomic masses, atomic polarizability, and atomic electronegativity are the main independent factors contributing to the hard inhibitory of the studied compounds.

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References

  • Ackley MA, Hurley RW, Virnich DE, Hammond DL (2001) A cellular mechanism for the antinociceptive effect of a kappa opioid receptor agonist. Pain 91:377–388

    Article  PubMed  CAS  Google Scholar 

  • Agrawal VK, Khadikar PV (2001) QSAR prediction of toxicity of nitrobenzenes. Bioorg Med Chem 9:3035–3040

    Article  PubMed  CAS  Google Scholar 

  • Brugel TA, Smith RW, Balestra M, Becker C, Daniels T, Hoerter TN, Koether GM, Throner SR, Panko LM, Folmer JJ, Cacciola J, Hunter AM, Liu RF, Edwards PD, Brown DG, Gordon J, Ledonne NC, Pietras M, Schroeder P, Sygowski LA, Hirata LT, Zacco A, Peters MF (2010a) Discovery of 8-azabicyclo 3.2.1 octan-3-yloxy-benzamides as selective antagonists of the kappa opioid receptor. Part 1. Bioorg Med Chem Lett 20:5847–5852

    Article  PubMed  CAS  Google Scholar 

  • Brugel TA, Smith RW, Balestra M, Becker C, Daniels T, Koether GM, Throner SR, Panko LM, Brown DG, Liu RF, Gordon J, Peters MF (2010b) SAR development of a series of 8-azabicyclo 3.2.1 octan-3-yloxy-benzamides as kappa opioid receptor antagonists. Part 2. Bioorg Med Chem Lett 20(18):5405–5410

    Article  PubMed  CAS  Google Scholar 

  • Carlezon WA, Beguin C, DiNieri JA, Baumann MH, Richards MR, Todtenkopf MS, Rothman RB, Ma ZZ, Lee DYW, Cohen BM (2006) Depressive-like effects of the kappa-opioid receptor agonist salvinorin A on behavior and neurochemistry in rats. J Pharmacol Exp Ther 316:440–447

    Article  PubMed  CAS  Google Scholar 

  • Cavalli A, Poluzzi E, De Ponti F, Recanatini M (2002) Toward a pharmacophore for drugs inducing the long QT syndrome: insights from a CoMFA study of HERG K+ channel blockers. J Med Chem 45:3844–3853

    Article  PubMed  CAS  Google Scholar 

  • Ekins S, Crumb WJ, Sarazan RD, Wikel JH, Wrighton SA (2002) Three-dimensional quantitative structure-activity relationship for inhibition of human ether-a-go–go-related gene potassium channel. J Pharmacol Exp Ther 301:427–434

    Article  PubMed  CAS  Google Scholar 

  • Eriksson L, Jaworska J, Worth AP, Cronin MTD, McDowell RM, Gramatica P (2003) Methods for reliability and uncertainty assessment and for applicability evaluations of classification- and regression-based QSARs. Environ Health Perspect 111:1361–1375

    Article  PubMed  CAS  Google Scholar 

  • Everitt B (1993) Cluster analysis, 3rd edn. E. Arnold, London

    Google Scholar 

  • Fields H (2004) State-dependent opioid control of pain. Nat Rev Neurosci 5:565–575

    Article  PubMed  CAS  Google Scholar 

  • Gilbert PE, Martin WR (1976) The effects of morphine and nalorphine-like drugs in the nondependent, morphine-dependent and cyclazocine-dependent chronic spinal dog. J Pharmacol Exp Ther 198:66–82

    PubMed  CAS  Google Scholar 

  • Gramatica P (2007) Principles of QSAR models validation: internal and external. QSAR Comb Sci 26:694–701

    Article  CAS  Google Scholar 

  • Habibi-Yangjeh A, Pourbasheer E, Danandeh-Jenagharad M (2008a) Prediction of basicity constants of various pyridines in aqueous solution using a principal component-genetic algorithm-artificial neural network. Monatsh Chem 139:1423–1431

    Article  CAS  Google Scholar 

  • Habibi-Yangjeh A, Pourbasheer E, Danandeh-Jenagharad M (2008b) Prediction of melting point for drug-like compounds using principal component-genetic algorithm-artificial neural network. Bull Kor Chem Soc 29:833–841

    Article  CAS  Google Scholar 

  • Knoll AT, Meloni EG, Thomas JB, Carroll FI, Carlezon WA (2007) Anxiolytic-like effects of kappa-opioid receptor antagonists in models of unlearned and learned fear in rats. J Pharmacol Exp Ther 323:838–845. doi:10.1124/jpet.107.127415

    Article  PubMed  CAS  Google Scholar 

  • Leonard JT, Roy K (2006) On selection of training and test sets for the development of predictive QSAR models. QSAR Comb Sci 25:235–251

    Article  CAS  Google Scholar 

  • Mague SD, Pliakas AM, Todtenkopf MS, Tomasiewicz HC, Zhang Y, Stevens WC, Jones RM, Portoghese PS, Carlezon WA (2003) Antidepressant-like effects of kappa-opioid receptor antagonists in the forced swim test in rats. J Pharmacol Exp Ther 305:323–330

    Article  PubMed  CAS  Google Scholar 

  • Martin WR, Eades CG, Thompson JA, Huppler RE, Gilbert PE (1976) The effects of morphine- and nalorphine-like drugs in the nondependent and morphine-dependent chronic spinal dog. J Pharmacol Exp Ther 197:517–532

    PubMed  CAS  Google Scholar 

  • Massart DL, Vandeginste BG, Buydens LM, De Jong S, Lewi PJ, Smeyers-Verbeke J (1998) Handbook of chemometrics and qualimetrics data handling in science and technology, vol 20. Elsevier, Amsterdam

  • McLaughlin JP, Marton-Popovici M, Chavkin C (2003) kappa opioid receptor antagonism and prodynorphin gene disruption block stress-induced behavioral responses. J Neurosci 23:5674–5683

    PubMed  CAS  Google Scholar 

  • Netzeva TI, Worth AP, Aldenberg T, Benigni R, Cronin MTD, Gramatica P, Jaworska JS, Kahn S, Klopman G, Marchant CA, Myatt G, Nikolova-Jeliazkova N, Patlewicz GY, Perkins R, Roberts DW, Schultz TW, Stanton DT, van de Sandt JJM, Tong WD, Veith G, Yang CH (2005) 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 33:155–173

    CAS  Google Scholar 

  • Portoghese PS, Nagase H, Lipkowski AW, Larson DL, Takemori AE (1988) Binaltorphimine-related bivalent ligands and their kappa opioid receptor antagonist selectivity. J Med Chem 31:836–841

    Article  PubMed  CAS  Google Scholar 

  • Pourbasheer E, Riahi S, Ganjali MR, Norouzi P (2009) Application of genetic algorithm-support vector machine (GA-SVM) for prediction of BK-channels activity. Eur J Med Chem 44:5023–5028

    Article  PubMed  CAS  Google Scholar 

  • Pourbasheer E, Riahi S, Ganjali MR, Norouzi P (2010a) QSAR study on melanocortin-4 receptors by support vector machine. Eur J Med Chem 45:1087–1093

    Article  PubMed  CAS  Google Scholar 

  • Pourbasheer E, Riahi S, Ganjali MR, Norouzi P (2010b) 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. J Enzym Inhib Med Chem 25:844–853

    Article  CAS  Google Scholar 

  • Pourbasheer E, Riahi S, Ganjali MR, Norouzi P (2011) QSAR study of C allosteric binding site of HCV NS5B polymerase inhibitors by support vector machine. Mol Divers 15:645–653

    Article  PubMed  CAS  Google Scholar 

  • Riahi S, Pourbasheer E, Dinarvand R, Ganjali MR, Norouzi P (2008) Exploring QSARs for antiviral activity of 4-alkylamino-6-(2-hydroxyethyl)-2-methylthiopyrimidines by support vector machine. Chem Biol Drug Des 72:205–216

    Article  PubMed  CAS  Google Scholar 

  • Riahi S, Pourbasheer E, Ganjali MR, Norouzi P (2009) 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 166:853–859

    Article  PubMed  CAS  Google Scholar 

  • Roche O, Trube G, Zuegge J, Pflimlin P, Alanine A, Schneider G (2002) A virtual screening method for prediction of the hERG potassium channel liability of compound libraries. ChemBioChem 3:455–459

    Article  PubMed  CAS  Google Scholar 

  • Roy K, Mandal AS (2008) Development of linear and nonlinear predictive QSAR models and their external validation using molecular similarity principle for anti-HIV indolyl aryl sulfones. J Enzym Inhib Med Chem 23:980–995

    Article  CAS  Google Scholar 

  • Shapiro S, Guggenheim B (1998) Inhibition of oral bacteria by phenolic compounds—Part 1. QSAR analysis using molecular connectivity. Quant Struct-Act Relat 17:327–337

    Article  CAS  Google Scholar 

  • Thomas JB, Atkinson RN, Rothman RB, Fix SE, Mascarella SW, Vinson NA, Xu H, Dersch CM, Lu YF, Cantrell BE, Zimmerman DM, Carroll FI (2001) Identification of the first trans-(3R,4R)-dimethyl-4-(3-hydroxyphenyl)piperidine derivative to possess highly potent and selective opioid kappa receptor antagonist activity. J Med Chem 44:2687–2690

    Article  PubMed  CAS  Google Scholar 

  • Todeschini R (2007) Milano Chemometrics and QSPR Group, http://www.disat.unimib.it/chm

  • Todeschini R, Consonni V (2000) Handbook of molecular descriptors. Methods and principles in medicinal chemistry, vol 11. Wiley-VCH, Weinheim

  • Vapnik VN (2000) The nature of statistical learning theory. Statistics for engineering and information science, 2nd edn. Springer, New York

  • Vink R, Portoghese PS, Faden AI (1991) Kappa-opioid antagonist improves cellular bioenergetics and recovery after traumatic brain injury. Am J Physiol 261:R1527–R1532

    PubMed  CAS  Google Scholar 

  • Wang WJ, Xu ZB, Lu WZ, Zhang XY (2003) Determination of the spread parameter in the Gaussian kernel for classification and regression. Neurocomputing 55:643–663

    Article  Google Scholar 

  • Yap YG, Camm AJ (1999) Arrhythmogenic mechanisms of non-sedating antihistamines. Clin Exp Allergy 29:174–181

    Article  PubMed  CAS  Google Scholar 

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Authors and Affiliations

  1. Center of Excellence in Electrochemistry, Faculty of Chemistry, University of Tehran, P. O. Box 14155-6455, Tehran, Iran

    Eslam Pourbasheer, Abolghasem Beheshti, Mohammad Reza Ganjali & Parviz Norouzi

  2. Department of Chemistry, Yasouj University, Yasouj, Iran

    Habibollah Khajehsharifi

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  1. Eslam Pourbasheer
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  2. Abolghasem Beheshti
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  3. Habibollah Khajehsharifi
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  4. Mohammad Reza Ganjali
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  5. Parviz Norouzi
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Correspondence to Eslam Pourbasheer.

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Pourbasheer, E., Beheshti, A., Khajehsharifi, H. et al. QSAR study on hERG inhibitory effect of kappa opioid receptor antagonists by linear and non-linear methods. Med Chem Res 22, 4047–4058 (2013). https://doi.org/10.1007/s00044-012-0412-4

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  • DOI: https://doi.org/10.1007/s00044-012-0412-4

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