From drugs to targets: Reverse engineering the virtual screening process on a proteomic scale

Phenotypic screening is a powerful technique that allowed the discovery of antimicrobials to fight infectious diseases considered deadly less than century ago. In high throughput phenotypic assays, thousands compounds are tested for their capacity inhibit microbial growth in-vitro . After an active compound found, identifying molecular target next step. Knowing specific key understanding its mechanism action, and essential future drug development. Moreover, this knowledge allows developers design new generations drugs with increased efficacy reduced side effects. However, identification known usually very difficult task. present work, we reverse virtual strategy, can help researchers working in field, predict set putative targets exhibit antimicrobial The strategy combines chemical similarity methods, prioritization based on essentiality data, molecular-docking. These steps be tailored according researchers’ needs pathogen’s available information. Our results show using only approach, method capable retrieving potential half compounds. even low threshold whenever domains retrieved, correct domain among those retrieved more 80% queries. Prioritizing by criteria us further reduce, up 3–4 times, number targets. Lastly, docking able identify ranked top two about thirds cases. Bias improves predictive slightly scenario. We expect integrate presented context Target Pathogen database make it wide community discovery.