Final Report Summary - GBMTARGET (Targeting Glioblastoma Signalling)
GBMTarget established a computational strategy exploiting polypharmacology to identify drug targets in biological systems implicated in disease. We identified multiple targets in protein networks associated with the disease to thereby enable repositioning of drugs against that disease. The efficacy of the approach was tested by using the platform to identify compounds against gliomas (including glioblastoma multiforme). The novelty of GBMTarget lies in its use of CATH-FunFams, a definition of protein domains developed in the Orengo group to link known and putative drug compounds to biological networks.
We have demonstrated that CATH-FunFams are the druggable entities within protein targets and developed a scheme to associate drugs to protein domains. We have modelled the signalling in gliomas as a network, to identify potential targets, and we proposed drugs active on them based on our drug-domain associations.
Our computational platform is easily extensible to other cancer types and even other diseases, enabling an efficient and cost-effective strategy for the identification of pharmacological targets and the repurposing of drugs.
We have demonstrated that CATH-FunFams are the druggable entities within protein targets and developed a scheme to associate drugs to protein domains. We have modelled the signalling in gliomas as a network, to identify potential targets, and we proposed drugs active on them based on our drug-domain associations.
Our computational platform is easily extensible to other cancer types and even other diseases, enabling an efficient and cost-effective strategy for the identification of pharmacological targets and the repurposing of drugs.