Designing novel antitrypanosomal agents from a mixed graph-theoretical substructural approach


Abstract:

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.

Año de publicación:

2010

Keywords:

  • Massive screening
  • Discriminant analysis
  • Antitrypanosomal
  • Graph theoretical descriptors
  • Fragment contributions

Fuente:

scopusscopus

Tipo de documento:

Article

Estado:

Acceso restringido

Áreas de conocimiento:

  • Descubrimiento de fármacos
  • Farmacología
  • Optimización matemática

Áreas temáticas de Dewey:

  • Ciencias de la computación
Procesado con IAProcesado con IA

Objetivos de Desarrollo Sostenible:

  • ODS 3: Salud y bienestar
  • ODS 17: Alianzas para lograr los objetivos
  • ODS 9: Industria, innovación e infraestructura
Procesado con IAProcesado con IA