In a recent study, researchers at Rice University combined computational techniques and experimental data to predict the structural change at each functional phase of protein. This unique approach could reduce the cost of drug development by reducing processes and errors in the prediction of therapeutic target sites on proteins. The study has appeared online in Proceedings of the National Academy of Sciences.
The most common methods for protein structural analysis currently are X-ray crystallography and nuclear magnetic resonance spectroscopy (NMR), however, these do not provide information about how proteins change their forms from native to functional state. José Onuchic, Harry C & Olga K Wiess Professor of Physics, said the intermediate states have important functions because they’ve been conserved by evolution. BioNews Texas has covered Dr. Onuchic’s unique research work before, such as his findings that even the genetic circuit in bacteria allows choice between individual freedom and collective good — a fascinating discovery.
In his current experiment, Onuchic’s team combined the direct coupling analysis (DCA) based on genomic databases with structure-based models (SBM) for the simulations of intermediate structural changes of proteins. “It has been long known that this information is encoded in these protein sequences, but it has been hard to extract,” said Faruck Morcos, a postdoctoral researcher at Rice and lead author of the paper.
In the study by Onuchic and his colleagues at the Center for Theoretical Biological Physics, they simulated the conformational changes on glutamine-receptor and ligand-binding proteins with DCA and experimental data. DCA allows researchers to predict contacts between amino acids in the proteins based on genetic data. In addition, researchers can compare genetic data among the protein families to search which residues have been co-evolved.