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Combining local-structure, fold-recognition, and new fold methods for protein structure prediction.

Kevin Karplus·Rachel Karchin·Jenny Draper·Jonathan Casper·Yael Mandel-Gutfreund·Mark Diekhans·Richard Hughey
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Abstract

This article presents an overview of the SAM-T02 method for protein fold recognition and the UNDERTAKER program for ab initio predictions. The SAM-T02 server is an automatic method that uses two-track hidden Markov models (HMMS) to find and align template proteins from PDB to the target protein. The two-track HMMs use an amino acid alphabet and one of several different local structure alphabets. The UNDERTAKER program is a new fragment-packing program that can use short or long fragments and alignments to create protein conformations. The HMMs and fold-recognition alignments from the SAM-T02 method were used to generate the fragment and alignment libraries used by UNDERTAKER. We present results on a few selected targets for which this combined method worked particularly well: T0129, T0181, T0135, T0130, and T0139.

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AlgorithmsComputational BiologyMarkov ChainsProtein ConformationProtein FoldingProteinsJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, Non-P.H.S.

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Kevin Karplus, Rachel Karchin, Jenny Draper, Jonathan Casper, Yael Mandel-Gutfreund, Mark Diekhans, Richard Hughey. 2003. Combining local-structure, fold-recognition, and new fold methods for protein structure prediction.. https://doi.org/10.1002/prot.10540

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