Last week, researchers presented a computational effort that assesses billions of potential dockings on the basis of drug and protein information held in public databases. “It’s the largest computational docking ever done by mankind,” says Timothy Cardozo, a pharmacologist at New York University’s Langone Medical Center, who presented the project on 19 November at the US National Institutes of Health’s High Risk–High Reward Symposium in Bethesda, Maryland. The result, a website called Drugable (drugable.com) that is backed by the US National Library of Medicine (NLM), is still in testing, but it will eventually be available for free, allowing researchers to predict how and where a compound might work in the body, purely on the basis of chemical structure (see ‘Mining for drugs’).
Cardozo acknowledges that the computations are just an initial step in drug discovery. After predicting whether a protein can bind to a compound, drug developers must test the drug’s action on the same protein in a cell to see what actually happens to the protein’s function, as well as how much of the drug is needed and under what conditions. Then come animal trials and, if researchers are lucky, human trials. But these extra data are often proprietary and held by pharmaceutical companies, says Brian Shoichet, a computational biologist at the University of California, San Francisco. Some public databases such as PubChem, maintained by the NLM, hold the results of automated tests of drugs on proteins in yeast cells, but they contain inaccuracies and false positives, he says.
Project ranks billions of drug interactions : Nature News & Comment