The world’s most extensive drug screening with CSC’s resources: New machine learning method speeds up screening hundred-fold.

The University of Eastern Finland performed a virtual search of 1.56 billion molecules to test two drug candidates. This was the world’s most extensive screening of its kind.

Professor Antti Poso’s research team were looking for molecules that would react with SurA chaperone and cyclin-G-associated kinase (GAK), two candidates with medicinal effect. The project tested the HASTEN algorithm developed for the screening, and created a new machine learning model.

“The machine that had been trained completed the screening much more quickly than would have been possible with the traditional docking method. While the calculation of docking took a couple of months even using powerful computers, with machine learning the learning process and prediction only took a few days.”

“Obviously it follows that with supercomputers we can take even bigger databases and screen thousands of billions of molecules with this method.”

The research made use of the supercomputing resources, data storage and tool containerisation of the Finnish ELIXIR Node, CSC – IT Center for Science.

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The world’s most extensive drug screening with CSC’s resources: New machine learning method speeds up screening hundred-fold.

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