PHENOTHERA: exploiting repositories of high throughput/content screening data to estimate therapeutic potential of a gene or a pathway

Understanding therapeutic potential of a gene or a pathway for the treatment of a specific disease is of paramount importance. At the moment, initial evidences that a gene or a pathway may represent a promising therapeutic target are based on experimentally verified differential expression of the gene/protein/pathway between disease/normal conditions. However, whether differential expression is a reason or a consequence of a disease remains unclear in majority of cases, and, therefore, targeting the gene might not be therapeutically relevant. Here, we propose a principle to estimate a gene/protein/pathway therapeutic potential from high throughput/content screening data

Using plethora of high throughput/content screening data we have implemented online tool (PHENOTHERA). PHENOTHERA integrates data from target oriented High Throughput Screens (HTS) to define for each screened protein sets of compounds that inhibit/activate it. These sets is used next to link activity versus the protein with High Content phenotipycal Screens (HCS). In this case we got direct evidences that targeting the protein increases chances for a potential drug to produce desired cell phenotypic transformation in vivo bioassays.

Next, using Pathways (Gene Ontology) database information on grouping genes into pathways (GO terms) we define sets of molecules inhibiting/activating pathways/GO terms by uniting sets of molecules targeting corresponding proteins. Similar, we used these sets to link pathway/GO term to HCS.

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