CONICET | Buscador de Institutos y Recursos Humanos

The volume of biological, chemical and functional data deposited in the publicdomain is growing rapidly, thanks to next generation sequencing, andhighly-automated screening technologies. However, there is still a large dataimbalance between model, well-funded organisms and pathogens causingneglected diseases (NDs). We developed a chemogenomics resource, (TDRTargets, tdrtargets.org), that aims to organize and integrate heterogeneouslarge datasets with a focus on drug discovery for human pathogens. Thedatabase also hosts chemical and genomic data from other organisms toleverage data for comparative and inference-based queries. One of the majorimpacts of TDR Targets is to facilitate target and chemical prioritizations byallowing users to formulate complex queries across diverse query spaces.In this communication we will highlight new data and functionality updates inTDR Targets. In this release, the database has been updated to integrate dataon >2 million bioactive compounds; 20 pathogen genomes; and 30 completegenomes from model organisms and other related pathogens. Furthermore, thedata was also used to populate a recently developed network model(Berenstein AJ, 2016) to produce i) a novel druggability metric for targets basedon the connectivity in the network to bioactive compounds, ii) to guide newprioritization strategies for both targets and compounds, and iii) to visually aid inthe navigation across target/compound spaces in the web interface. Thisnetwork model connects protein (target) nodes to compounds, based oncurated bioactivity annotations. It also connects proteins to other proteins basedon shared annotations, and compounds to other compounds based onchemical similarity and substructure metrics. This chemogenomic networkfacilitates a number of inferences, such as inferring plausible targets for orphandrugs or candidate compounds for orphan targets. Funded by ANPCyT-GlaxoArgentina (PICTO-Glaxo-2013-0067).