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New Tool Allows for Flexible Matching to Track Distantly Related Proteins

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When it comes to simulating real-world conditions, most protein alignment algorithms fall short. Three researchers from Tufts University and MIT developed a new alignment tool that allows the protein to twist or move during the alignment process, more closely matching biological conditions. Lenore Cowen, from the Tufts computer science department, says her group is interested in related proteins that may be evolutionarily distant and in what those proteins' functions may be. Since no program allowed them to model proteins as they wanted, Cowen and MIT's Matt Menke and Bonnie Berger made their own program. "None of them did what we actually needed to do quite well enough when the structures were just evolutionarily a little bit too far away. We were very arrogant. We said, 'Oh well, we'll just write our own,'" says Cowen.

Their program, called Matt for "multiple alignment with translation and twists," is an alignment fragment pair chaining program that allows for local flexibility. "Most previous methods had taken these protein crystal structures as rigid bodies and they aligned the rigid bodies, but the protein is only a rigid structure when you crystallize it. They actually are somewhat flexible," Cowen says. So instead, their program allows for a certain amount of rotation and translation.

After a year and half of development, Cowen and her team ran benchmark tests of Matt on datasets from Homstrad and SABmark, common standard benchmarking programs, versus other alignment tools. Matt performed as well as other tools on Homstad but better on SABmark, which includes proteins that are more distantly related, as the authors reported recently in PLoS Computational Biology. "We're able to capture similarity even when the structures are starting to really not be that similar," Cowen says. Matt outputs its data in FASTA or PDB format, and can also output a rasmol script so users can view the protein alignment as an animated movie. The program is open-source and freely available from the Tufts or MIT websites under a GPL license.

Next up for Matt is adding support for partial alignments so it can show only the proteins that line up out of a larger group. The researchers are also adding in sequence information to appeal to users who prefer to look at sequence and alignment simultaneously.

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