Compound Screening with Deep Learning for Neglected Diseases: Leishmaniasis

Abstract

AbstractDeep learning provides a tool for improving screening of candidates for drug re-purposing to treat neglected diseases. We show how a new pipeline can be developed to address the needs of repurposing for Leishmaniasis. In combination with traditional molecular docking techniques, this allows top candidates to be selected and analyzed, including for molecular descriptor similarity.