QuBiLs-MAS method in early drug discovery and rational drug identification of antifungal agents

The QuBiLs-MAS approach is used for the in silico modelling of the antifungal activity of organic molecules. To this effect, non-stochastic (NS) and simple-stochastic (SS) atom-based quadratic indices are used to codify chemical information for a comprehensive dataset of 2478 compounds having a great structural variability, with 1087 of them being antifungal agents, covering the broadest antifungal mechanisms of action known so far. The NS and SS index-based antifungal activity classification models obtained using linear discriminant analysis (LDA) yield correct classification percentages of 90.73% and 92.47%, respectively, for the training set. Additionally, these models are able to correctly classify 92.16% and 87.56% of 706 compounds in an external test set. A comparison of the statistical parameters of the QuBiLs-MAS LDA-based models with those for models reported in the literature reveals comparable to superior performance, although the latter were built over much smaller and less diverse datasets, representing fewer mechanisms of action. It may therefore be inferred that the QuBiLs-MAS method constitutes a valuable tool useful in the design and/or selection of new and broad spectrum agents against life-threatening fungal infections. © 2015 Taylor & Francis.

• Fecha de publicación: 2015
• Institución: Universidad Tecnológica de Bolívar
• Repositorio: Repositorio Institucional UTB
• Idioma: eng
• OAI Identifier: oai:repositorio.utb.edu.co:20.500.12585/9032
• Acceso en línea: https://hdl.handle.net/20.500.12585/9032
• Palabra clave: Atom-based quadratic indices; Linear discriminant analysis; QSAR model; QuBiLs-MAS software; Vrtual screening, antifungal agent; Antifungal agent; Chemistry; Computer simulation; Discriminant analysis; Drug development; Quantitative structure activity relation; Statistical model; Antifungal Agents; Computer simulation; Discriminant analysis; Drug Discovery; Linear Models; Quantitative Structure-Activity Relationship
• Rights: restrictedAccess
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/