Modeling anti-Trypanosoma cruzi activity of N-oxide containing heterocycles

Journal of Chemical Information and Modeling

Volumn 48, Issue 1, 2008, Pages 213-219

  Boiani, Mariana ^a,b   Cerecetto, Hugo ^a   González, Mercedes ^a   Gasteiger, Johann ^b  

^a UNIVERSIDAD DE LA REPÚBLICA   (Uruguay)

^b UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BIOACTIVITY; DISTRIBUTION FUNCTIONS; ELECTRONIC PROPERTIES; QUANTUM CHEMISTRY; RADIAL BASIS FUNCTION NETWORKS; STRUCTURE (COMPOSITION);

CLASSIFICATION RULES; ELECTROPHILIC CHARACTER; HETEROCYCLES;

DRUG PRODUCTS;

ANTIPROTOZOAL AGENT; FUSED HETEROCYCLIC RINGS; OXIDE;

ALGORITHM; ANIMAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; CHEMISTRY; COMPUTER SIMULATION; DRUG DESIGN; DRUG EFFECT; PRINCIPAL COMPONENT ANALYSIS; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REPRODUCIBILITY; TRYPANOSOMA CRUZI;

ALGORITHMS; ANIMALS; ANTIPROTOZOAL AGENTS; COMPUTER SIMULATION; DRUG DESIGN; HETEROCYCLIC COMPOUNDS, 2-RING; MODELS, BIOLOGICAL; NEURAL NETWORKS (COMPUTER); OXIDES; PRINCIPAL COMPONENT ANALYSIS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; REPRODUCIBILITY OF RESULTS; TRYPANOSOMA CRUZI;

EID: 39449112213     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci7002768     Document Type: Article

References (42)

1. World Health Organization. Thirteenth Programme Report. UNDP/ World Bank/World Health Organization programme for research and training in tropical diseases; World Health Organization: Geneva, Switzerland, 1997.
2. Urbina, J. Chemotherapy of Chagas Disease. Curr. Pharm. Des. 2002, 8, 287-295.
3. Cerecetto, H.; Di Maio, R.; González, M.; Risso, M.; Saenz, P.; Seoane, G.; Denicola, A.; Peluffo, G.; Quijano, C.; Olea-Azar, C. 1,2,5-Oxadiazole N-oxide Derivatives and related compounds as Potential Antitrypanosomal Drugs. Structure-Activity Relationships. J. Med. Chem. 1999, 42, 1941-1950.
4. Aguirre, G.; Cerecetto, H.; Di Maio, R.; González, M.; Porcal, W.; Seoane, G.; Denicola, A.; Ortega, M. A.; Aldana, I.; Moge-Vega, A. Benzo[1,2-c] 1,2,5-oxadiazole N-oxide Derivatives as Potential Antitrypanosomal Drugs. Structure-Activity Relationships. Part II. Arch. Pharm. (Weinheim, Ger.) 2002, 335, 15-21.
5. Olea-Azar, C.; Rigol, C.; Mendizábal, F.; Brinones, R.; Cerecetto, H.; Di Maio, R.; González, M.; Porcal, W.; Risso, M. Electrochemical and Microsomal Production of Free Radicals from 1,2,5-oxadiazole N-oxide as Potential Antiprotozoal Drugs. Spectrochim. Acta, Part A 2003, 59, 69-74.
6. Aguirre, G.; Boiani, L.; Cerecetto, H.; Di Maio, R.; González, M.; Porcal, W.; Thomson, L.; Tórtora, V.; Denicola, A.; Möller, M. Benzo-[1,2-c] 1,2,5-oxadiazole N-oxide Derivatives as Potential Antitrypanosomal Drags. Part III. Substituents-Clustering Methodology in the search of new active compounds. Bioorg. Med. Chem. 2005, 13, 6324-6335.
7. Olea-Azar, C.; Rigol, C.; Mendizábal, F.; Cerecetto, H.; Di Maio, R.; González, M.; Porcal, W.; Morello, A.; Repetto, Y.; Maya, J. D. Novel Benzo[1,2-c]1,2,5-oxadizole N-oxide derivatives as Antichagasic Agents: Chemical and Biological Studies. Lett. Drugs Des. Dev. 2005, 2, 294-301.
8. Porcal, W.; Hernandez, P.; Aguirre, G.; Boiani, L.; Boiani, M.; Merlino, A.; Ferreira, A.; Di Maio, R.; Castro, A.; González, M.; Cerecetto, H. Second generation of 5-Ethenylbenzofuroxan derivatives as Inhibitors of Trypanosoma cruzi growth: Synthesis, biological evaluation and stracutre-activity relationships. Bioorg. Med. Chem. 2007, 15, 2768-2781.
9. Aguirre, G.; Boiani, M.; Cerecetto, H.; Gerpe, A.; González, M.; Fernández Sainz, Y.; Denicola, A.; Ochoa de Ocáriz, C; Nogal, J.; Montero, D.; Escário, J. Novel Antiprotozoal Products: Imidazole and Benzimidazole N-Oxide Derivatives and Related Compounds. Arch. Pharm. (Weinheim, Ger.) 2004, 337, 259-270.
10. Boiani, M.; Boiani, L.; Denicola, A.; Torres, S.; Serna, E.; Vera de Bilbao, N.; Sanabria, L.; Yaluff, G.; Nakayama, H.; Rojas de Arias, A.; Vega, C.; Rolan, M.; Gomez-Barrios, A.; Cerecetto, H.; González, M. 2H-Benzimidazole 1,3-dioxide derivatives: A new family of water-soluble anti-trypanosomatid agents. J. Med. Chem. 2006, 49, 3215-3220.
11. Gerpe, A.; Aguirre, G.; Boiani, L.; Cerecetto, H.; González, M.; Olea-Azar, C.; Rigol, C.; Maya, J. D.; Morello, A.; Piro, O.; Arán, V. J.; Azqueta, A.; Lopez de Cerain, A.; Moge-Vega, A.; Rojas de Arias, A.; Yaluff, G. Indazole N-oxide derivatives as antiprotozoal agents: Synthesis, biological evaluation and mechanism of action studies. Bioorg. Med. Chem. 2006, 14, 3467-3480.
12. Aguirre, G.; Cerecetto, H.; Di Maio, R.; Gonzalez, M.; Montoya Alfaro, M. E.; Jaso, A.; Zarranz, B.; Ortega, M. A.; Aldana, I.; Moge-Vega, A. Quinoxaline N,N′-dioxide derivatives and related compounds as growth inhibitors of Trypanosoma cruzi. Structure-activity relationships. Bioorg. Med. Chem. Lett. 2004, 14, 3835-3839.
13. Aguirre, G.; Boiani, L.; Boiani, M.; Cerecetto, H.; Di Maio, R.; González, M.; Porcal, W.; Denicola, A.; Piro, O.; Castellano, E.; Sant'Anna, C. M. R.; Barreiro, E. J. New potent 5-substituted Benzofuroxans as Inhibitors of Trypanosoma cruzi growth. Quantitative Structure-Activity relationship studies. Bioorg. Med. Chem. 2005, 13, 6336-6346.
14. Silverman, R. B. The Organic Chemistry of drug Design and drug Action; Academic Press: San Diego, CA, 1992.
15. Gasteiger, J. A Hierarchy of Structure Representations. In Handbook of Chemoinformatics; Gasteiger, J., Ed.; Wiley-VCH: Weinheim, 2003; pp 1034-1061.
16. Zupan, J.; Gasteiger, J. Neural Networks in Chemistry and Drug Design, 2nd ed.; Wiley-VCH: Weinheim, 1999.
17. Wagner, S.; Hofmann, A.; Siedle, B.; Terfloth, L.; Merfort, I.; Gasteiger, J. Development of a Structural Model for NF-κB Inhibition of Sesquiterpene Lactones Using Self-Organizing Neural Networks. J. Med. Chem. 2006, 49, 2241-2252.
18. Spartan'04 Windows, 1.0.1; Wavefunction, Inc.: Irvine, CA, 2003.
19. Spartan'04 Windows: Tutorial and User's Guide; Wavefunction: Irvine, CA, 2003.
20. Dewar, M. J. S.; Zoebisch, E. G.; Healy, E. F.; Stewart, J. J. P. AM1: A New General Purpose Quantum Mechanical Molecular Model. J. Am. Chem. Soc. 1985, 107, 3902-3909.
21. Storer, J. W.; Giesen, D. J.; Hawkins, G. D.; Lynch, G. C.; Cramer, C. J.; Truhlar, D. G.; Liotard, D. A. Solvation Modeling in Aqueous and Nonaqueous Solvents: New Techniques and a Re-examination of the Claisen Rearrangement. In Structure and Reactivity in Aqueous Solution, ACS Symposium Series; Cramer, C. J., Truhlar, D. G., Eds.; American Chemical Society: Washington, DC, 1994; Vol. 568.
22. Ghose, A. K.; Crippen, G. M. Atomic physicochemical parameters for 3D structure-directed quantitative structure-activity relationships. 2. Modeling dispersive and hydrophobic interactions. J. Chem. Inf. Comput. Sci. 1987, 27, 21-35.
23. Clark, D. E. Rapid calculation of polar molecular surface area and it application to the prediction of transport phenomena. 1. Prediction of intestinal absorption. J. Pharm. Sci. 1999, 88, 807-814.
24. Sadowski, J.; Gasteiger, J. From atoms and bonds to three-dimensional atomic coordinates: automatic model builders. Chem. Rev. 1993, 93, 2567-2581.
25. ADRIANA.Code, 1.0; Molecular Networks GmbH: Erlangen, Germany, 2006. http://www.molecular-networks.com.
26. Hemmer, M. C.; Steinhauer, V.; Gasteiger, J. Deriving the 3D structure of organic molecules from their infrared spectra. Vib. Spectrosc. 1999, 19, 151-164.
27. Hemmer, M. C.; Gasteiger, J. Prediction of Three-dimensional molecular structures using information from infrared spectra. Anal. Chim. Acta 2000, 420, 145-154.
28. Computer program ARDF; Computer-Chemie-Centrum, Universität Erlangen-Nuremberg: Erlangen, Germany 2005.
29. Mazzatorta, P.; Vracko, M.; Jezierska, A.; Benfenati, E. Modeling toxicity by using supervised Kohonen neural networks. J. Chem. Inf. Comput. Sci. 2003, 43, 485-492.
30. SONNIA software 4.1; Molecular Networks GmbH: Erlangen, Germany 2005. http://www.molecular-networks.com.
31. Kohonen, T. Self-Organizing maps, 3rd ed.; Springer: New York, 2001.
32. Witten, I. H.; Frank, E. Data Mining: Practical machine learning tools and techniques, 2nd ed.; Morgan Kaufmann: San Francisco, CA, 2005.
33. Witten, I. H.; Eibe, F. Data Mining: Practical machine learning tools and techniques; Morgan Kaufmann: San Francisco, CA, 2000.
34. Hastie, T.; Tibshirani, R.; Friedman, J. The elements of statistical learning; Springer: New York, 2001.
35. Harrel, F. E. J. Regression Modeling Strategies- With applications to Linear Models, Logistic Regression and Survival Analysis; SpringerVerlag: New York, 2001.
36. Hosmer, D. W.; Lemeshow, S. Applied Logistic Regression, 2nd ed.; John Wiley & Sons, Inc.: 2000.
37. Frimurer, T.; Bywater, R. Improving the odds in discriminating "Drug-like" from "Non Drug-like" compounds. J. Chem. Inf. Comput. Sci. 2000, 40, 1315-1324.
38. Schneider, G.; Wrede, P. Artificial neural networks for computed-based molecular design. Prog. Bioph. Mol. Biol. 1998, 70, 175-222.
39. Cannon, E. O.; Bender, A.; Palmer, D. S.; Mitchell, J. B. O. Chemoinformatic-Based Classification of Prohibited Substances Employed for Doping in Sport. J. Chem. Inf. Model. 2006, 46, 2369-2380.
40. Jolliffe, T. Principal Component Analysis; Springer-Verlag: New York, 1986.
41. Albini, A.; Pietra, S. Heterocyclic N-oxides; CRC Press: Boca Raton, FL, 1991.
42. Baldi, P.; Brunak, S. Bioinformatics: the machine learning approach, 2nd ed.; Cambridge, MA, 2001.