Estrategia probabilística de combinación de la información para la clasificación y cribado virtual de candidatos a fármaco anticoccidiales
Fecha
2015-06-25
Autores
Escobar Román, Raylen
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Editor
Universidad Central “Marta Abreu” de Las Villas. Centro de Bioactivos Químicos.
Resumen
En el presente trabajo se empleó la Teoría de Dempster-Shafer (TDS) en la implementación de una estrategia conjunta de clasificación y/o cribado virtual de candidatos a fármaco con potencial actividad anti-coccidia, basada en la combinación de la información proveniente de múltiples modelos QSAR derivados de diferentes representaciones de la estructura molecular. El resultado de la aplicación de esta estrategia condujo a un desempeño significativamente superior al uso individual de modelos de clasificación, lográndose porcentajes de exactitud/sensibilidad/especificidad superiores al 94%/86%/96% y 86%/75%/89% en las series de entrenamiento y predicción, respectivamente. A su vez, la aplicación de esta estrategia conjunta condujo a medidas de enriquecimiento significativamente superiores al uso individual de modelos predictivos como herramientas para el cribado virtual. Todos estos resultados sugieren que el empleo la Teoría de Dempster-Shafer (TDS) como base teórica para la implementación de una estrategia conjunta de clasificación y/o cribado virtual puede ser eficientemente empleada en el proceso de descubrimiento y desarrollo de nuevos candidatos a fármaco con potencial actividad anti coccidia y de esta forma contribuir a superar los problemas de resistencia a las terapias actuales.
In the present work, Dempster-Shafer Theory (DST) was employed for the implementation of a combined strategy for classification and/or virtual screening of potential anticoccidial drug candidates, based on the combination of the information provided by multiple QSAR models which are derived from different molecular structure representations. The application of such a strategy lead to a classification performance superior to the individual use of QSAR models, achieving accuracy/sensibility/specificity values over 94%/86%/96% and 86%/75%/89% on training and predicting series, respectively. Parallely, the application of such a strategy lead to values of enrichment metrics significantly superiors to the individual use of QSAR models as virtual screening tools. All these results suggest that the use of DST as the theoretical probabilistic base for the implementation of a combined classification and/or virtual screening strategy can be efficiently employed on the process of discovery and development of novel potential anticoccidial candidates, contributing in this way to overcome the emergence of resistance to current therapies.
In the present work, Dempster-Shafer Theory (DST) was employed for the implementation of a combined strategy for classification and/or virtual screening of potential anticoccidial drug candidates, based on the combination of the information provided by multiple QSAR models which are derived from different molecular structure representations. The application of such a strategy lead to a classification performance superior to the individual use of QSAR models, achieving accuracy/sensibility/specificity values over 94%/86%/96% and 86%/75%/89% on training and predicting series, respectively. Parallely, the application of such a strategy lead to values of enrichment metrics significantly superiors to the individual use of QSAR models as virtual screening tools. All these results suggest that the use of DST as the theoretical probabilistic base for the implementation of a combined classification and/or virtual screening strategy can be efficiently employed on the process of discovery and development of novel potential anticoccidial candidates, contributing in this way to overcome the emergence of resistance to current therapies.
Descripción
Palabras clave
Coccidiosis/prevención & control, Coccidiosis/prevention & control, Drogas Veterinarias, Veterinary Drugs, Diseño de Drogas, Drug Design