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Applying pattern recognition methods to analyze the molecular properties of a homologous series of nitrogen mustard agents

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Abstract

The purpose of this research was to analyze the pharmacological properties of a homologous series of nitrogen mustard (N-mustard) agents formed after inserting 1 to 9 methylene groups (-CH2-) between 2-N(CH2CH2Cl)2 groups. These compounds were shown to have significant correlations and associations in their properties after analysis by pattern recognition methods including hierarchical classification, cluster analysis, nonmetric multi-dimensional scaling (MDS), detrended correspondence analysis, K-means cluster analysis, discriminant analysis, and self-organizing tree algorithm (SOTA) analysis. Detrended correspondence analysis showed a linear-like association of the 9 homologs, and hierarchical classification showed that each homolog had great similarity to at least one other member of the series—as did cluster analysis using paired-group distance measure. Nonmetric multi-dimensional scaling was able to discriminate homologs 2 and 3 (by number of methylene groups) from homologs 4, 5, and 6 as a group, and from homologs 7, 8, and 9 as a group. Discriminant analysis, K-means cluster analysis, and hierarchical classification distinguished the high molecular weight homologs from low molecular weight homologs. As the number of methylene groups increased the aqueous solubility decreased, dermal permeation coefficient increased, Log P increased, molar volume increased, parachor increased, and index of refraction decreased. Application of pattern recognition methods discerned useful interrelationships within the homologous series that will determine specific and beneficial clinical applications for each homolog and methods of administration.

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References

  1. Gareth T. Medicinal Chemistry. New York, NY: John Wiley and Sons; 2000.

    Google Scholar 

  2. Silverman R. The Organic Chemistry of Drug Design and Drug Action. San Diego, CA: Academic Press; 1992.

    Google Scholar 

  3. Pratt W, Ruddon R, Ensminger W, Maybaum J. The Anticancer Drugs. New York, NY: Oxford University Press; 1994.

    Google Scholar 

  4. Gringauz A. Introduction to Medicinal Chemistry. New York, NY: Wiley-VCH; 1997.

    Google Scholar 

  5. King F. Medicinal Chemistry Principles and Practice. Cambridge, UK: Royal Society of Chemistry; 2001.

    Google Scholar 

  6. Pain A, Samanta S, Dutta S, et al. Synthesis and evaluation of substituted naphthalimide nitrogen mustards as rationally designed anticancer compounds. Acta Pol Pharm. 2003;60:285–291.

    CAS  Google Scholar 

  7. Pain A, Samanta S, Dutta S, et al. Evaluation of napromustine, a nitrogen mustard derivative of naphthalimide, as a rationally designed mixed-function anticancer agent. Exp Oncol. 2002;24: 173–179.

    CAS  Google Scholar 

  8. Faissat L, Martin K, Chavis C, Montero J, Lucas M. New nitrogen mustards structurally related to (L)-Carnitine. Bioorg Med Chem. 2003;11:325–334.

    Article  CAS  Google Scholar 

  9. Fousteris MA, Koutsourea AI, Arsenou ES, Papageorgiou A, Mourelato D, Nikolaropoulos SS. Antileukemic and cytogenetic effects of modified and non-modified esteric steroidal derivatives of 4-methyl-3-bis(2-chloroethyl)amino benzoic acid (4-Me-CABA). Anticancer Res. 2002;22:2293–2299.

    CAS  Google Scholar 

  10. Papageorgiou A, Nikolaropoulos S, Arsenou E, et al. Enhanced cytogenetic and antineoplastic effects by the combined action of 2 esteric steroidal derivatives of nitrogen mustards. Chemotherapy. 1999;45:61–67.

    Article  CAS  Google Scholar 

  11. Baraldi P, Romagnoli R, Giovanna P, Nunez M, Bingham J, Hartley J. Benzoyland cinnamoyl nitrogen mustard derivatives of benzoheterocyclic analogues of thetallimustine: synthesis and antitumor activity. Bioorg Med Chem. 2002;10:1611–1618.

    Article  CAS  Google Scholar 

  12. Chen Z, Wan W, Xu D. Studies on the synthesis of tetrapyrrole nitrogen mustards and their directed dual anti-tumor activities. J Chin Pharm Sci. 1998;7:230–231.

    CAS  Google Scholar 

  13. O’Conner C, Denny W, Fan J, Gravatt G, Grigor B, McLennan D. Hydrolysis and alkylating reactivity of aromatic nitrogen mustards. J Chem Soc. 1991;12:1933–1939.

    Google Scholar 

  14. Palmer B, Wilson W, Cliffe S, Denny W. Hypoxia-selective antitumor agents. 5. Synthesis of water-soluble nitroaniline mustards with selective cytotoxicity for hypoxic mammalian cells. J Med Chem. 1992;35:3214–3222.

    Article  CAS  Google Scholar 

  15. Catsoulacos P, Camoutsis C, Pelecanou M. Antileukemic activity of homo-azasteroidal esters of the isomers of N,N-bis(2-chloroethyl) aminocinnamic acid. Eur J Med Chem. 1991;26:659–661.

    Article  CAS  Google Scholar 

  16. Hartley J, Preti C, Wyatt M, Lee M. Design, synthesis and biological evaluation of benzoic acid mustard derivatives of imidazole-containing and C-terminal carboxamide analogs of distamycin. Drug Des Discov. 1995;12:323–335.

    CAS  Google Scholar 

  17. Brooks N, McHugh P, Lee M, Hartley J. The role of base excision repair in the repair of DNA adducts formed by a series of nitrogen mustard-containing analogues of distamycin of increasing binding site size. Anticancer Drug Des. 1999;14:11–18.

    CAS  Google Scholar 

  18. Kovalenko S. Effect of basicity and details of chemical structure on the mutagenic activity of nitrogen mustards. Genetika. 1972; 8:100–103.

    CAS  Google Scholar 

  19. Bartzatt R, Donigan L. Two identical twin nitrogen mustard agents that express rapid alkylation activity at physiological pH 7.4 and 37°C. Lett Drug Des Discov. 2004;1:78–83.

    Article  Google Scholar 

  20. Herroro J, Valencia A, Dopazo J. A hierarchical unsupervised growing neural network for clustering gene expression patterns. Bioinformatics. 2001;17:126–136.

    Article  Google Scholar 

  21. Palm K, Stenberg P, Luthman K, Artursson P. Polar molecular surface properties predict the intestinal absorption of drugs in humans. Pharm Res. 1997;14:568–571.

    Article  CAS  Google Scholar 

  22. Ertl P, Bernhard R, Selzer P. Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug transport properties. J Med Chem. 2000;43: 3714–3717.

    Article  CAS  Google Scholar 

  23. Clark D. Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 2. Prediction of blood-brain barrier penetration. J Pharm Sci. 1999;88:815–821.

    Article  CAS  Google Scholar 

  24. Hansch C, Leo A, Hockman D. Exploring QSAR: Hydrophobic, Electronic, and Steric Constants. ACS Professional Reference Book. Washington, DC: The American Chemical Society; 1995.

    Google Scholar 

  25. Johnson R, Wichern D. Applied Multivariate Statistical Analysis. Englewood Cliffs, NJ: Prentice Hall Inc; 1992.

    Google Scholar 

  26. Dundteman G. Introduction to Multivariate Analysis. Beverly Hills, CA: Sage Publication; 1994.

    Google Scholar 

  27. Anderberg M. Cluster Analysis for Applications. San Diego, CA: Academic Press; 1973.

    Google Scholar 

  28. Schiffman S, Reynolds M, Young F. Introduction to Multidimensional Scaling: Theory, Methods, and Applications. New York, NY: Academic Press; 1981.

    Google Scholar 

  29. Lipinski A, Lombardo F, Dominy B, Feeney P. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev. 1997;23:3–25.

    Article  CAS  Google Scholar 

  30. Greenacre MJ. Correspondence Analysis in Practice. London, UK: Academic Press; 1993.

    Google Scholar 

  31. Hardy I, Cook W. Predictive and correlative techniques for the design, optimization and manufacture of solid dosage forms. J Pharm Pharmacol. 2002;55:3–18.

    Article  Google Scholar 

  32. Mareno M, Magalhaes N, Cavalcanti C, Alves A. Hierarchical cluster analysis applied to drug design. Quim Nova. 1996; 19:594–599.

    Google Scholar 

  33. Fossler M, Chang K, Young D. The use of cluster analysis in pharmacokinetics. Acta Pharm Jugosl. 1990;40:225–236.

    CAS  Google Scholar 

  34. Wermuth CG. The Practice of Medicinal Chemistry. San Diego, CA: Academic Press; 1996.

    Google Scholar 

  35. Aboul-Fadl T, Mahfouz N. Metronidazole twin ester prodrugs. 2. Non identical twin esters of metronidazole and some antiprotozoal halogenated hydroxy-quinoline derivatives. Sci Pharm. 1998;66:309–324.

    CAS  Google Scholar 

  36. Mahfouz N, Aboul-Fadl T, Diab A. Metronidazole twin ester prodrugs: synthesis, physiochemical properties, hydrolysis kinetics and antigiardial activity. Eur J Med Chem. 1998;33:675–683.

    Article  CAS  Google Scholar 

  37. Rinaki E, Valsami G, Macheras P. Quantitative biopharmaceutics classification system: the central role of dose/solubility ratio. Pharm Res. 2003;20:1917–1925.

    Article  CAS  Google Scholar 

  38. Lobenberg R, Amidon G. Modern bioavailability, bioequivalence and biopharmaceutics classification system: new scientific approaches to international regulatory standards. Eur J Pharm Biopharm. 2000; 50:3–12.

    Article  CAS  Google Scholar 

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Correspondence to Ronald Bartzatt.

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Published: April 14, 2006

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Bartzatt, R., Donigan, L. Applying pattern recognition methods to analyze the molecular properties of a homologous series of nitrogen mustard agents. AAPS PharmSciTech 7, 35 (2006). https://doi.org/10.1208/pt070235

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  • DOI: https://doi.org/10.1208/pt070235

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