Open access data on the behaviors of druggable proteins is expected to aid cancer translational research

New data made available through publicly accessible database canSAR is anticipated to help support target validation in drug discovery

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Scientists from Cancer Research UK Cancer Therapeutics Unit, at The Institute of Cancer Research (London, UK), have made publicly available the data that emerged from their recent study into distinctive behaviors of druggable proteins in cellular networks. The data, which is accessible via canSAR, an integrated knowledgebase that brings together multidisciplinary information from across biology, chemistry, pharmacology, structural biology, cellular networks and clinical annotations, is anticipated to aid cancer translational research by providing a new set of druggability predictors, which are intended to enhance the target validation process.

Recognizing that the protein interaction environment is largely overlooked in target selection during drug discovery, and is something that may be important in defining the role that the protein plays, the team embarked on a study into the human interactome. First analyzing a large representation of the human interactome, comprising almost 90,000 interactions between 13,345 proteins, the group assessed these interactions using an extensive set of topological, graphical and community parameters. Led by Bissan Al-Lazikani, the team identified behaviors that distinguish the protein interaction environments of drug targets from the general interactome, in addition to clear distinctions between the network environment of cancer-drug targets and targets from other therapeutics areas. Based on the network parameters, the team built a predictive methodology to prioritize potential drug targets alone, which they then validated using current FDA-approved drug targets.

The team anticipate that the predictive models will provide an objective, interactome-based target prioritization methodology, which will serve to complement existing structure-based and ligand-based prioritization methods. With all interactome-based predictions alongside other druggability predictors available within the public canSAR resource (, it is hoped that the data will aid in drug discovery efforts. Bissan Al-Lazikani commented: “Our aim is that cancer scientists will be armed with the data they need to carry out life-saving research into the most exciting drugs of the future."

The team is now applying for funding to extend and enhance the capability, capacity and user-friendliness of these resources.

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Hannah Coaker

Contributor, Future Science Group

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