La información genómica de patógenos ha creado nuevas oportunidades para la identificación de blancos y el desarrollo de fármacos, incluyendo nuevas especies resistentes y multiresistentes. Sin embargo, esta información debe ser integrada cohesivamente para poder ser explotada en su totalidad y fácilmente interrogable.
Available genomic data for pathogens has created new opportunities for target identification and drug discovery, including new species, resistant and multiresistant ones. However, this data must be cohesively integrated to be fully exploited and be easy to interrogate. Our Work in developing tools that include genomic annotation, structural prediction, druggability anayisis, metabolic pathways determination and target prioritization algorithms.
On the other hand when a target is identified we need to develop tools to accurate find a leading compound to inhibit or regulate the function of the desired protein. In our lab we develop bioinformatic tools for drug discovery including bias docking, hot spot identification, high throughput in-silico screening and free energy methods.
We develop web servers that allow genome wide based data consolidation from diverse sources at different processing stages focusing on structural analysis of proteins and the prediction of druggability for potential targets and compound desirability information. By allowing the integration and weighting of this information, this bioinformatic tool aims to facilitate the identification and prioritization of candidate drug targets for pathogens.