tFolder looks at a peptide sequence and enumerates all possible positions for structures known as beta sheets, which are represented by coloured arrows. The color gradient indicates the sequence position: yellow arrows are toward the beginning of the sequence, followed by green, blue and purple. The most likely structure is the largest one displayed.
By Tyler Irving
Posted September 2011
The process of folding a linear polypeptide into a complete protein with a specialized shape and function is one of nature’s miracles. Computers can model this process using molecular dynamics (MD) but it’s still an enormous task - determining the folding pathway for a single protein can take thousands of hours of processing time. Now a researcher at McGill University has developed a program that could greatly speed up this process.
Jerôme Waldispuhl is an assistant professor in the Department of Computer Science at McGill and has been working in the field of bioinformatics for more than a decade. He’s developed a program called tFolder, which is able to give a rough estimate of the structure for a particular protein in about half an hour. While traditional MD techniques use classical physics laws to compute a sequence of 3D structures, detailing each possible step along the folding pathway, tFolder takes a ‘birds-eye view’ approach. The program uses a coarse-grained energy landscape model that treats each amino acid as a discrete unit, which enables it to quickly enumerate all possible structures and calculate which ones are most likely. “It doesn’t aim to substitute for moleculardynamics, it’s a completely different approach,” says Waldispuhl. "The idea is to sacrifice some precision but, on the other hand, we have a huge gain in terms of calculability.”
Waldispuhl has already tested the model on a polypeptide called protein G, one of the few proteins for which information about the folding pathway is available. He hopes that in the future it could be used to narrow down the list of possible structures for other folding simulations, saving thousands of hours in processing time. The research is published in the Journal of Computational Biology and the software is at http://csb.cs.mcgill.ca/tfolder/.
Photo Credit: Jerome Waldispuhl
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