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IBM Research Team Finds New Scoring Function for Protein Structure Prediction

NEW YORK, April 17 – Researchers at IBM’s Computational Biology Center have discovered a pattern in the hydrophobicity of soluble, globular proteins that could help verify whether computer simulations of the shape of a folded protein are correct, the company said Tuesday. 

In a paper in the April 17 issue of the Proceedings of the National Academy of Sciences , IBM researcher David Silverman and his colleagues detail the discovery of the pattern they found in the transition between hydrophobic amino acids on the inside of a protein to hydrophilic amino acids on the outside of a protein. 

Using a mathematical construct called a second-order moment, Silverman first calculated the change in distribution of hydrophobicity for three different globular proteins. He then found that a ratio of two well-defined qualities was approximately the same for all three.

“I think at that point lightning struck,” said Silverman. “I had discovered what some mathematicians or physicists might call an invariant.”

Ajay Royyuru, who heads up structural biology research at IBM Research, said that the invariant could serve as a relatively sensitive scoring function to verify the accuracy of protein structure prediction algorithms. 

“This has enormous relevance in the field of proteomics,” said Royyuru. “Predicting protein structures is a key post-genomic activity because there are a lot of sequences for which we do not know the structure. Improving our ability to predict or even judge our predictions is certainly a very key activity.”

The work is complementary to IBM’s Blue Gene protein-folding project. Royyuru said the findings could guide the project in designing better functions or assessing whether a particular trajectory of folding is progressing correctly. He cautioned, however, that the research is still in its early stages and it’s too soon to predict its full implications. 

The team is now exploring how the ratio behaves as a function of molecular dynamics and folding and how well it serves as a scoring function compared to other scoring functions. They also intend to perform a complete characterization for all 15,000 protein structures in the Protein Data Bank

Silverman has calculated the hydrophobic ratio for 47 globular proteins so far and is currently applying the method to transmembrane and ribosomal proteins to see how well the pattern holds up in other types of proteins. 

“We have to check whether it works for all structures,” Silverman said. “I say, don’t worry. It’s going to work for everything. I haven’t seen one exception.”

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