Fragment-HMM: a new approach to protein structure prediction.

Protein Science : a Publication of the Protein Society
Shuai Cheng LiMing Li

Abstract

We designed a simple position-specific hidden Markov model to predict protein structure. Our new framework naturally repeats itself to converge to a final target, conglomerating fragment assembly, clustering, target selection, refinement, and consensus, all in one process. Our initial implementation of this theory converges to within 6 A of the native structures for 100% of decoys on all six standard benchmark proteins used in ROSETTA (discussed by Simons and colleagues in a recent paper), which achieved only 14%-94% for the same data. The qualities of the best decoys and the final decoys our theory converges to are also notably better.

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Citations

Jun 30, 2010·Journal of Computational Biology : a Journal of Computational Molecular Cell Biology·Feng ZhaoJinbo Xu
Aug 29, 2012·Briefings in Bioinformatics·Mehdi MaadooliatJianhua Z Huang
May 30, 2009·Bioinformatics·Babak AlipanahiMing Li
Oct 29, 2010·Journal of Bioinformatics and Computational Biology·Yuzhong ZhaoMing Li
Feb 18, 2011·Journal of Bioinformatics and Computational Biology·Babak AlipanahiMing Li
Jan 15, 2010·BMC Bioinformatics·Shuai Cheng Li, Yen Kaow Ng
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Dec 3, 2013·Bioinformatics·Xuefeng CuiMing Li
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Oct 26, 2011·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Shuai Cheng LiMing Li
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Sep 20, 2017·BMC Bioinformatics·Haiou LiJianlin Cheng

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