Grid technology to help European cancer research project

The recently launched CancerGrid Project will bring together partners from industry and academia in the first ever large scale application of computer grid technology for finding and developing new anti-cancer agents.

The three-year multidisciplinary research programme funded by the EU will aim to combine new technologies with biology to enrich molecular libraries and increase the likelihood of discovering potential drugs to treat cancer.

"This innovative project utilizes grid-based computing technology for the automated design of chemical libraries, with the goal of discovering potential cancer treatments," said Michael Guaciaro, Ph.D., president and managing director of AMRI, one of the industrial partners in the project.

The project will employ the resources of grid computing to allow the researchers to tap into a powerful network of interconnected workstations able to process large amounts of data and reduce computational time.

Cancer affects millions of people and accounts for 13% of deaths around the world, according to the World Health Organization.

In the human genome, there is an estimated subset of approximately 3,000 genes that encode proteins, including novel cancer-related targets, which could be regulated with drug-like molecules.

The partners in the project will work towards developing specific chemical compound collections ('focused' chemical libraries) that interact with these cancer proteins.

"Our goal is to develop methods for creating chemical libraries containing molecules active against the newly emerging cancer targets," explained Gyorgy Dorman, head of science and technology at AMRI.

"The use of grid-aided technology should substantially increase both the likelihood of finding novel anti-cancer lead compounds, as well as increase the translation of basic knowledge into the application stage," he added.

This project is also expected to produce and validate a technology for in-silico design of chemical libraries and models that predict toxicity and target specificity. Once developed, these libraries will in theory be applicable to any drug discovery project.

For further information, please visit:
http://www.cancergrid.eu

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