A team of researchers have discovered a new way to track signal pathways and identify allosteric sites in proteins. They accomplished this by using mathematical tools that have been previously used to study electrical grid failures and traffic jams. The findings, which have important implications for medical research, were just published in the journal Nature Communications.
Proteins are biomolecules that perform a number of functions necessary to support life. Many proteins contain active sites, certain spots that can interact with surrounding molecules. Specific molecules can bind to the active site, potentially changing the protein’s shape, function, and other properties. In medicine, these active sites are common targets for drug therapy. For example, a dysfunctional protein can potentially be “fixed” by targeting the active site with the proper medication.
In addition to active sites, proteins also have allosteric sites. These are spots on the protein, sometimes far away from the active site, that are also able to bind to other molecules. These interactions can change how the protein behaves or even completely activate or inactivate the molecule. Allosteric sites are important for fully understanding how a protein works and they are useful in medicine. The problem is that these sites are not always easy to locate and it’s difficult to trace the signals as they move throughout the protein.
A team of researchers used existing mathematical strategies to trace signal pathways and find possible allosteric sites. The mathematical models used in the study are already used to research traffic jams and cascading failures in electrical grids. The models track the activity of chemical bonds throughout the protein, using subtle differences in chemistry to track signals and locate allosteric sites.
The team has successfully used their new mathematical method on existing proteins. The model was accurate in predicting the location of allosteric sites. The researchers are now extending their research to less studied proteins.
R. C. Amor et al. Prediction of allosteric sites and mediating interactions through bond-to-bond propensities. Nature Communications (2016).