Rational computational approaches to predict novel drug candidates against leishmaniasis

The combination of in silico and in vitro approaches has proven to be useful for the pre-clinical assessment of potential drugs and novel uses for old drugs. This is frequently implemented in the case of neglected tropical diseases, where new effective and safe treatments are needed. In this chapter, we compile several in silico strategies that have been used to look for new treatments towards leishmaniasis, a parasitic disease affecting millions of people worldwide. Different computational methodologies are discussed, including molecular modeling and docking analysis, prediction of novel targets and drugs aided by bioinformatics and machine learning pipelines, ligand-based property predictions, and pharmacokinetic simulations to estimate possible drug doses based on known population data. Additional perspectives per strategy are proposed to guide researchers starting to work in the field.