GtoPdb has been traditionally focused on the pharmacology associated with human diseases (i.e. we have not been funded to cover anti-infectives). In 2017 we have been exploring possible funding opportunities to extend into expert curation of anti-infectives, particularly in the light of the antibiotic resistance threat and expanding drug discovery efforts for neglected tropical diseases (NTDs). Consequently, for this release we have added a selection of entries as a proof of concept for how well our current data model would accommodate these new types of relationship mappings “off the bat”. These are now under a new category of “Anti-infective targets“. A snapshot of the six new entries is show below.
We curated three antimalarials, two antivirals and one antibiotic, some of which have the ligand in PDB entries. By and large, this pilot was successful and we would be pleased to get feedback from interested parties. A number of technical challenges were encountered but most of these were “domain inherent” rather than GtoPdb data model issues per se. Examples include the sub-species and strain multiplexing of the target sequences. This results in having to map the authors described ligand activity data to TrEMBL entries (sometimes with equivocalities as to the exact isolate sequence) rather than to the deeper annotated Swiss-Prot entries avaialble for some reference pathogen proteomes with completed gene naming. We also ran in to the multi-enzyme “string of pearls” problem where large polypeptides encode for multiple functional domains, more than one of which that can be (or have been) targeted by different inhibitors. Classically, this is the case for the viral polyprotein precursor proteins but in this set also for the polyketide synthase entry shown below.
This was derived from a recent 2017 Cell paper “Development of a Novel Lead that Targets M. tuberculosis Polyketide Synthase 13” (PMID 28669536). Should we be sucessful in being resourced to expand in this domain we can already envisage tweaks to our existing data model and curation processes that could address some these domain-specific challenges. For example, we can specify ligand-targeted domains not only by InterPro coordinates in UniProt entries but also by getting the TrEMBL entries “promoted” to Swiss-Prot to enhance the domain annotation cross-references.
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