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Articles

4D-QSAR investigation and pharmacophore identification of pyrrolo[2,1-c][1,4]benzodiazepines using electron conformational–genetic algorithm method

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Pages 317-342 | Received 22 Nov 2015, Accepted 30 Mar 2016, Published online: 28 Apr 2016

References

  • L.H. Hurley, DNA and associated targets for drug design, J. Med. Chem. 32 (1989), pp. 2027–2033.
  • D.E. Thurston, Advances in the study of pyrrolo[2,1-c][1,4]benzodiazepine (PBD) antitumour antibiotics in Molecular Aspects of Anticancer Drug–DNA Interactions, S. Neidle and MJ Waring, eds., MacMillan Press, London, 1993, pp. 54–88.
  • M.D. Tendler and S. Korman, “Refuin”: A non-cytotoxic carcinostatic compound proliferated by a thermophilic actinomycete, Nature 199 (1963), p. 501.
  • L.H. Hurley and R.L. Petrusek, Proposed structure of the anthramycin–DNA adduct, Nature. 282 (1979), pp. 529–531.
  • D.J. Abraham, The history of quantitative structure activity relationships, in Burger's Medicinal Chemistry and Drug Discovery, C.D. Selassie, ed., John Wiley and Sons Publishers, New York, NY, 2003, pp. 1–48.
  • E.X. Esposito, A.J. Hopfinger, and J.D. Madura, Methods for applying the quantitative structure-activity relationship paradigm, Meth. Mol. Biol. 275 (2004), pp. 131–213.
  • S.J. Free and J. Wilson, A mathematical contribution to structure activity studies, J. Med. Chem. 7 (1964), pp. 395–399.
  • C. Hansch and T. Fujita, ρ-σ-π Analysis: A method for the correlation of biological activity and chemical structure, J. Am. Chem. Soc. 86 (1964), pp. 1616–1626.
  • R. Cramer, D. Patterson, and J. Bunce, Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins, J. Am. Chem. Soc. 110 (1988), pp. 5959–5967.
  • G. Klebe, Comparative molecular similarity indices analysis: CoMSIA, in 3D QSAR Drug Design, Vol. 3, H. Kubinyi, G. Folkers, and Y.C. Martin, eds., Kluwer Academic Publishers, Newyork, 1998, pp. 87–104.
  • A.J. Hopfinger, S. Wang, J.S. Tokarski, B. Jin, M. Albuquerque, P.J. Madhav, and C. Duraiswami, Construction of 3D-QSAR models using the 4D-QSAR analysis formalism, J. Am. Chem. Soc. 119 (1997), pp. 10509–10524.
  • A. Vedani and M. Dobler, 5D-QSAR: The key for simulating induced fit?, J. Med. Chem. 45 (2002), pp. 2139–2149.
  • A. Vedani, M. Dobler, and M.A. Lill, Combining protein modeling and 6D-QSAR-Simulating the binding of structurally diverse ligands to the estrogen receptor, J. Med. Chem. 48 (2005), pp. 3700–3703.
  • J. Polanski, Receptor dependent multidimensional QSAR for modeling drug-receptor interactions, Curr. Med. Chem. 16 (2009), pp. 3243–3257.
  • A. Kamal, E.V. Bharathi, M.J. Ramaiah, D. Dastagiri, J.S. Reddy, A. Viswanath, and F. Sultana, S.N.C.V.L. Pushpavalli, M. Pal-Bhadra, H.K. Srivastava, G.N. Sastry, A. Juvekar, S. Sen, and S. Zingde, Quinazolinone linked pyrrolo[2,1-c][1,4]benzodiazepine (PBD) conjugates: Design, synthesis and biological evaluation as potential anticancer agents, Bioorg. Med. Chem. 18 (2010), pp. 526–542.
  • D. Antonow and D.E. Thurston, Synthesis of DNA-interactive pyrrolo[2,1-c][1,4]benzodiazepines (PBDs), Chem. Rev. 111 (2011), pp. 2815–2864.
  • L. Cipolla, A.C. Araújo, C. Airoldi, and D. Bini, Pyrrolo[2,1-c][1,4]benzodiazepine as a scaffold for the design and synthesis of anti-tumour drugs, Anticancer Agents Med. Chem. 9 (2009), pp. 1–31.
  • Y. Ohtake, A. Naito, H. Hasegawa, K. Kawano, D. Morizono, M. Taniguchi, Y. Tanaka, H. Matsukawa, K. Naito, T. Oguma, Y. Ezure, and Y. Tsuriya, Novel vasopressin V2 receptor-selective antagonists, pyrrolo[2,1-a]quinoxaline and pyrrolo[2,1-c][1,4]benzodiazepine derivatives, Bioorg. Med. Chem. 7 (1999), pp. 1247–1254.
  • C. Paulussen, K. de Wit, G. Boulet, P. Cos, L. Meerpoel, and L. Maes, Pyrrolo[1,2- α][1,4]benzodiazepines show potent in vitro antifungal activity and significant in vivo efficacy in a Microsporum canis dermatitis model in guinea pigs, J. Antimicrob. Chemother. 69 (2014), pp. 1608–1610.
  • D. Antonow, M. Kaliszczak, G.D. Kang, M. Coffils, A.C. Tiberghien, N. Cooper, T. Barata, S. Heidelberger, C.H. James, M. Zloh, T.C. Jenkins, A.P. Reszka, S. Neidle, S.M. Guichard, D.I. Jodrell, J.A. Hartley, P.W. Howard, and D.E. Thurston, Structure-activity relationships of monomeric C2-aryl pyrrolo[2,1-c][1,4]benzodiazepine (PBD) antitumor agents, J. Med. Chem. 53 (2010), pp. 2927–2941.
  • E. Sarıpınar, N. Geçen, K. Şahin, and E. Yanmaz, Pharmacophore identification and bioactivity prediction for triaminotriazine derivatives by electron conformational-genetic algorithm QSAR method, Eur. J. Med. Chem. 45 (2010), pp. 4157–4168.
  • I.B. Bersuker and A.S. Dimoglo, The electron-topological approach to the QSAR problem, in Reviews in Computational Chemistry, K.B. Lipkowitz and D.B. Boyd, eds., John Wiley and Sons Publisher Inc, New Jersey, 1991, pp. 423–460.
  • I.B. Bersuker, Pharmacophore identification and quantitative bioactivity prediction using the electron-conformational method, Curr. Pharm. Des. 9 (2003), pp. 1575–1606.
  • I.B. Bersuker, S. Bahçeci, and J.E. Boggs, Improved electron-conformational method of pharmacophore identification and bioactivity prediction. Application to angiotensin converting enzyme inhibitors, J. Chem. Inf. Comput. Sci. 40 (2000), pp. 1363–1376.
  • N. Sukumar, G. Prabhu, and P. Saha, Applications of genetic algorithms in QSAR/QSPR Modeling, in Applications of Metaheuristics in Process Engineering, J. Valadi and P. Siarry, eds., Springer International Publishing, Switzerland, 2014, pp. 315–324.
  • E. Yanmaz, E. Sarıpınar, K. Şahin, N. Geçen, and F. Çopur, 4D-QSAR analysis and pharmacophore modeling: Electron conformational-genetic algorithm approach for penicillins, Bioorg. Med. Chem. 19 (2011), pp. 2199–2210.
  • K. Şahin, E. Sarıpınar, E. Yanmaz, and N. Geçen, Quantitative bioactivity prediction and pharmacophore identification for benzotriazines derivatives by electron conformational-genetic algorithm QSAR method, SAR QSAR Environ. Res. 22 (2011), pp. 217–238.
  • N. Geçen, E. Sarıpınar, E. Yanmaz, and K. Sahin, Application of electron conformational–genetic algorithm approach to 1,4-dihydropyridines as calcium channel antagonists: Pharmacophore identification and bioactivity prediction, J. Mol. Model. 18 (2012), pp. 65–82.
  • L. Akyüz, E. Sarıpınar, E. Kaya, and E. Yanmaz, 4D-QSAR study of HEPT derivatives by electron conformational-genetic algorithm method, SAR QSAR Environ Res. 23 (2012), pp. 409–433.
  • L. Akyüz and E. Sarıpınar, Conformation depends on 4D-QSAR analysis using EC–GA method: Pharmacophore identification and bioactivity prediction of TIBOs as non-nucleoside reverse transcriptase inhibitors, J. Enzyme Inhib. Med. Chem. 28 (2013), pp. 776–791.
  • Spartan'10; Wavefunction, Inc.: Irvine, CA, 2011.
  • I.B. Bersuker, QSAR without arbitrary descriptors: The electron-conformational method, J. Comput. Aided. Mol. Des. 22 (2008), pp. 423–430.
  • A.S. Dimoglo, P.F. Vlad, N.M. Shvets, and M.N. Coltsa, Electronic-topolocigal investigations of the relationship between chemical structure and ambergris odor, New J. Chem. 19 (1995), pp. 1217–1226.
  • E. Sarıpınar, Y. Güzel, Ş. Patat, İ. Yıldırım, Y. Akçamur, and A.S. Dimoglo, Electron-topological investigation of structure-antitubercular activity relationship of thiosemicarbazone derivatives, Arzneimittelforschung 46 (1996), pp. 824–828.
  • I.B. Bersuker, S. Bahçeci, J.E. Boggs, and R.S. Pearlman, An electron conformational method of identification of pharmacophore and anti-pharmacophore shielding: Application to rice blast activity, J. Comput. Aided. Mol. Des. 13 (1999), pp. 419–434.
  • MATLAB (ver 7.0), The MathWorks Inc, 3 Apple Hill Drive, Natick, MA 01760-2098.
  • J.H. Holland, Adaptation in Artificial and Natural Systems, University of Michigan Press, Michigan, Ann Arbor, 1975.
  • J. Devillers, Principles of QSAR and Drug Design: Genetic Algorithms in Molecular Modeling, Academic Press, Lyon, 1996.
  • G. Schüürmann, R.U. Ebert, J. Chen, B. Wang, and R. Kuhne, External validation and prediction employing the predictive squared correlation coefficient - test set activity mean vs training set activity mean, J. Chem. Inf. Model. 48 (2008), pp. 2140–2145.
  • V. Consonni, D. Ballabio, and R. Todeschini, Comments on the definition of the Q2 parameter for QSAR validation, J. Chem. Inf. Model. 49 (2009), pp. 1669–1678.
  • N. Chirico and P. Gramatica, Real external predictivity of QSAR models: How to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient, J. Chem. Inf. Model. 51 (2011), pp. 2320–2335.
  • Al H. Makkouk and I.B. Bersuker, and J.E. Boggs, Quantitative drug activity prediction for inhibitors of human breast carcinoma, Int. J Pharm. Med. 18 (2004), pp. 81–89.
  • J.G. Topliss and R.P. Edwards, Chance factors in studies of quantitative structure-activity relationships, J. Med. Chem. 22 (1979), pp. 1238–1244.
  • J. Wan, L. Zhang, and G. Yang, Quantitative structure–activity relationships for phenyl triazolinones of protoporphyrinogen oxidase inhibitors: A density functional theory study, J. Comp. Chem. 25 (2004), pp. 1827–1832.
  • W. Long and P. Liu, Quantitative structure activity relationship modeling for predicting radiosensitization effectiveness of nitroimidazole compounds, J. Radiat. Res. 51 (2010), pp. 563–572.
  • R. Todeschini and V. Consonni, Molecular Descriptors for Chemoinformatics, Vol. 41, Wiley-VCH, Weinheim, 2009, pp. 625–626.
  • A. Golbraikh and A. Tropsha, Beware of q2!, J. Mol. Graph. Model. 20 (2002), pp. 269–276.

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