title: LRFragLib: an effective algorithm to identify fragments for de novo protein structure prediction.
abstract: The quality of fragment library determines the efficiency of fragment assembly, an approach that is widely used in most de novo protein-structure prediction algorithms. Conventional fragment libraries are constructed mainly based on the identities of amino acids, sometimes facilitated by predicted information including dihedral angles and secondary structures. However, it remains challenging to identify near-native fragment structures with low sequence homology.
  
  
  
  We introduce a novel fragment-library-construction algorithm, LRFragLib, to improve the detection of near-native low-homology fragments of 7-10 residues, using a multi-stage, flexible selection protocol. Based on logistic regression scoring models, LRFragLib outperforms existing techniques by achieving a significantly higher precision and a comparable coverage on recent CASP protein sets in sampling near-native structures. The method also has a comparable computational efficiency to the fastest existing techniques with substantially reduced memory usage.
  
  
  
  The source code is available for download at http://166.111.152.91/Downloads.html.
  
  
  
  hgong@tsinghua.edu.cn.
  
  
  
  Supplementary data are available at Bioinformatics online.
authors: MOE Key Laboratory of Bioinformatics, School of Life Sciences.|Beijing Innovation Center of Structural Biology, Tsinghua University, Beijing 100084, China.
authors: Tong
authors: T
authors: Wang
authors: Institute for Glycomics and School of Information and Communication Technology, Griffith University, Gold Coast, QLD 4222, Australia.
authors: Yuedong
authors: Y
authors: Yang
authors: Institute for Glycomics and School of Information and Communication Technology, Griffith University, Gold Coast, QLD 4222, Australia.
authors: Yaoqi
authors: Y
authors: Zhou
authors: MOE Key Laboratory of Bioinformatics, School of Life Sciences.|Beijing Innovation Center of Structural Biology, Tsinghua University, Beijing 100084, China.
authors: Haipeng
authors: H
authors: Gong
mesh_terms: D000465:Algorithms; D020169:Caspases / Q000737:chemistry; D019295:Computational Biology / Q000379:methods*; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D011506:Proteins; D020169:Caspases