In silico approach to predicting protein function

US researchers 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.

In a paper published online this month in Nature Chemical Biology, a research team, led by University of Illinois biochemistry professor John A. Gerlt, used a computational approach to accurately predict a protein's function from its amino acid sequence. Their in silico computer-aided predictions were validated in the laboratory by 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 modelling, the team performed computerised 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 protein's 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.

The research team included scientists from the University of California, San Francisco, and the Albert Einstein College of Medicine.

Source: University of Illinois at Urbana-Champaign