In a paper published online this month in the journal Nature Chemical Biology, researchers report that they have developed a way to determine the function of some of the hundreds of thousands of proteins for which amino acid sequence data are available, but whose structure and function remain unknown.
The research team, led by University of Illinois biochemistry professor John A. Gerlt, is the first to use a computational approach to accurately predict a proteins function from its amino acid sequence. Their in silico (computer-aided) predictions were validated in the laboratory by means of enzyme assays and X-ray crystallography.
The new approach involved searching databases of known proteins for those with amino acid sequences that had the greatest homology to the unknown proteins. The researchers then used the three-dimensional structures of the most closely matched known proteins in their analyses of protein function.
Using the structural data obtained from this homology modeling, the team performed computerized docking experiments to quickly evaluate whether the unknown proteins were likely to bind to any of a vast library of potential target molecules, or substrates. Determining which substrate binds to a given protein is vital to understanding the proteins function.
This study describes an integrated approach using experimental techniques, computational techniques and X-ray crystallography for predicting the function of a protein of previously unknown function, Gerlt said.
These methods will speed the task of identifying the biological roles of some of the hundreds of thousands of proteins whose functions have not yet been discovered.
Rather than trying to do (laboratory) experiments on 30,000 compounds to determine if they are substrates, with this approach you might do experiments on 10, Gerlt said.