Only ~1% of all drug candidates against Neglected Tropical Diseases (NTDs)
have reached clinical trials in the last decades, underscoring the need for new, safe and effective
treatments. In such context, drug repositioning, which allows finding novel indications
for approved drugs whose pharmacokinetic and safety profiles are already known,
emerging as a promising strategy for tackling NTDs. Chemogenomics is a direct descendent
of the typical drug discovery process that involves the systematic screening of chemical
compounds against drug targets in high-throughput screening (HTS) efforts, for the identification
of lead compounds. However, different to the one-drug-one-target paradigm, chemogenomics
attempts to identify all potential ligands for all possible targets and diseases. In
this review, we summarize current methodological development efforts in drug repositioning
that use state-of-the-art computational ligand- and structure-based chemogenomics approaches.
Furthermore, we highlighted the recent progress in computational drug repositioning
for some NTDs, based on curation and modeling of genomic, biological, and chemical data.
Additionally, we also present in-house and other successful examples and suggest possible solutions
to existing pitfalls.
Keywords: Neglected tropical diseases, drug repositioning, chemogenomics, similarity search, machine learning,
pharmacophores, protein alignment, docking.
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