Potential molecular targets of the anti-HIV drug nelfinavir have been identified, and may explain why the drug is also effective as a cancer therapy. Findings will be published in the open-access journal PLoS Computational Biology on 28th April 2011.
Nelfinavir is a protease inhibitor that prevents replication of the HIV virus. It has also been found to have a positive effect on a number of solid tumor types but the mechanism of how the drug worked in humans was unclear. Researchers from the University of California San Diego and the City University of New York (CUNY) combined a wide array of computational techniques to investigate the molecular mechanisms underlying nelfinavir's observed anti-cancer effect and found that there are weak interactions with a multitude of molecular targets, rather than a strong interaction with a single target.
While drug molecules are designed to bind to targeted proteins in order to achieve a therapeutic effect, small drug molecules can also attach to off-target proteins with similar binding sites. The result may be unwanted side effects or, as in the case of nelfinavir, a secondary and positive effect. Philip E. Bourne, professor of pharmacology at UCSD Skaggs School of Pharmacy and Pharmaceutical Sciences, and his colleagues suggest that it is the collective effect of these weak interactions that leads to the clinical efficacy of nelfinavir.
The computational methods used by the researchers are a useful way of searching for potential drug targets: "Computer analysis allows us to search for other binding sites that match a particular drug-binding site – like looking for other locks that can be opened by the same key," said Lei Xie, associate professor at Hunter College, CUNY. However, it is a particularly complex route to validation of drug targets. Prof. Bourne adds "This is indeed challenging, but it is hard not to believe that this broad-based systems approach represents the future of drug discovery, at least as far as small-molecule drugs are concerned."
Journal
PLoS Computational Biology