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Designing novel antitrypanosomal agents from a mixed graph‐theoretical substructural approach
Author(s) -
Planche Alejandro Speck,
Scotti Marcus Tulius,
Emerenciano Vicente de Paulo,
López América García,
Pérez Enrique Molina,
Uriarte Eugenio
Publication year - 2010
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.21374
Subject(s) - in silico , trypanosoma cruzi , chagas disease , graph , computer science , set (abstract data type) , computational biology , biology , theoretical computer science , parasite hosting , biochemistry , world wide web , gene , immunology , programming language
Chagas disease is nowadays the most serious parasitic health problem. This disease is caused by Trypanosoma cruzi . The great number of deaths and the insufficient effectiveness of drugs against this parasite have alarmed the scientific community worldwide. In an attempt to overcome this problem, a model for the design and prediction of new antitrypanosomal agents was obtained. This used a mixed approach, containing simple descriptors based on fragments and topological substructural molecular design descriptors. A data set was made up of 188 compounds, 99 of them characterized an antitrypanosomal activity and 88 compounds that belong to other pharmaceutical categories. The model showed sensitivity, specificity and accuracy values above 85%. Quantitative fragmental contributions were also calculated. Then, and to confirm the quality of the model, 15 structures of molecules tested as antitrypanosomal compounds (that we did not include in this study) were predicted, taking into account the information on the abovementioned calculated fragmental contributions. The model showed an accuracy of 100% which means that the “in silico” methodology developed by our team is promising for the rational design of new antitrypanosomal drugs. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010