A novel computer program has identified thousands of new targets for existing drugs by comparing the molecular structures of drug compounds and chemicals that occur naturally in the body.
The technique could be used to uncover new applications or reveal potential side effects for drugs already on the market.
"It's a new approach, and it's a totally different from what everyone else has done. That's why it actually works," Nature quoted study author Bryan Roth, a pharmacologist at the University of North Carolina at Chapel Hill as saying.
The most common methods for predicting whether a small molecule binds to various drug targets involves either high-throughput laboratory screening or virtually simulating whether a particular compound fits together with proteins like a key in a lock.
However, the experimental approach is tedious and time consuming, while the computational method relies on the existence of high-resolution protein structures, which are hard to come by for many drug-sensitive proteins.
Last year, German scientists developed a new approach for finding novel drug targets for existing medications by showing that drugs with similar adverse side effects often share a common target protein, even when those drugs are chemically quite different.
In the new study, Roth and Brian Shoichet, a computational chemist at the University of California, San Francisco, have successfully identified new uses for marketed drugs by comparing existing drug compounds with different ligands - biologically active molecules that naturally bind proteins.
They thought that if a drug and ligand have similar three-dimensional structures, then there's a good chance that the drug will bind to the same protein as the ligand.
The researchers' suspicions were proved correct.
They produced chemical 'fingerprints' of more than 3,600 drugs that were either approved or in late-stage clinical trials and some 65,000 ligands that together bind to around 250 protein targets.
They then developed a statistical technique to compare the two types of molecules and singled out nearly 7,000 pairs of predicted drug-target interactions, thousands of which had never been shown before.
The technique provides "a way of giving you decent molecular-based hypotheses for side effects of drugs and a way of looking for new targets for these very special molecules", said Shoichet.
The study has been published in Nature.