Predicting drug-protein interaction through 3D modelling . A study by Nicholas Firth and colleagues at the Institute of Cancer Research, have developed a way to quickly assess the 3D nature of a large number of molecules, increasing the speed at which desirable drug molecules can be identified.
In the development of drugs, molecules are chosen that will bind to a protein and alter its function. A lock and key analogy can be used where only the drug molecule with the right shape will fit into a “binding site” on the target protein. It is through this binding that the drug has its functions. Recently it has been found that molecules with a highly 3D nature, that is where the atoms that make up the structure, or scaffold, of the protein extend out in all directions, appear to have an advantage in binding to proteins. Additionally, these molecules are likely to dissolve well in water making them easier to use as drugs.
Research, funded by Institute of Cancer Research and Cancer Research UK, uses mathematical algorithms to identify where scaffolding atoms sit in comparison to a planar surface at the centre of the molecule. Highly 3D molecules have atoms furthest from this plane reaching out in multiple directions. This method was used to analyse the structure of thousands of compounds, that have yet to be visualised by structural biology techniques, giving additional information that could be utilised in screening drug molecules for the treatment of a multitude of disorders.
This research is published in the Journal of Chemical Information and Modelling and can be viewed as a free PMC article at http://www.ncbi.nlm.nih.gov/pubmed/23009689
Firth, Nicholas C., Nathan Brown, and Julian Blagg. “Plane of Best Fit: A Novel Method to Characterize the Three-Dimensionality of Molecules.” Journal of Chemical Information and Modeling (2012).