publication . Article . Other literature type . 2013

Protein threading using context-specific alignment potential

Jianzhu Ma; Sheng Wang; Feng Zhao; Jinbo Xu;
Open Access
  • Published: 21 Jun 2013 Journal: Bioinformatics, volume 29, pages i257-i265 (issn: 1367-4803, eissn: 1460-2059, Copyright policy)
  • Publisher: Oxford University Press (OUP)
Abstract
Motivation: Template-based modeling, including homology modeling and protein threading, is the most reliable method for protein 3D structure prediction. However, alignment errors and template selection are still the main bottleneck for current template-base modeling methods, especially when proteins under consideration are distantly related. Results: We present a novel context-specific alignment potential for protein threading, including alignment and template selection. Our alignment potential measures the log-odds ratio of one alignment being generated from two related proteins to being generated from two unrelated proteins, by integrating both local and globa...
Subjects
free text keywords: Statistics and Probability, Computational Theory and Mathematics, Biochemistry, Molecular Biology, Computational Mathematics, Computer Science Applications, Sequence alignment, Smith–Waterman algorithm, Multiple sequence alignment, Computer science, Threading (protein sequence), Structural alignment, Homology modeling, Bioinformatics, Loop modeling, Alignment-free sequence analysis, Ismb/Eccb 2013 Proceedings Papers Committee July 21 to July 23, 2013, Berlin, Germany, Original Papers, Protein Structure and Function
Related Organizations
Funded by
NSF| CAREER: Exact and Approximate Algorithms for 3D Structure Modeling of Protein-Protein Interactions
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1149811
  • Funding stream: Directorate for Computer & Information Science & Engineering | Division of Computing and Communication Foundations
,
NSF| Algorithm and Web Server for Low-homology Protein Threading
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 0960390
  • Funding stream: Directorate for Biological Sciences | Division of Biological Infrastructure
33 references, page 1 of 3

Akutsu, T, Miyano, S. On the approximation of protein threading. Theor. Comput. Sci.. 1999; 210: 261-275 [OpenAIRE]

Alexandrov, NN. Fast protein fold recognition via sequence to structure alignment and contact capacity potentials. Pac. Symp. Biocomput.. 1996: 53-72 [PubMed]

Biegert, A, Söding, J. Sequence context-specific profiles for homology searching. Proc. Natl. Acad. Sci. USA. 2009; 106: 3770-3775 [OpenAIRE] [PubMed]

Dayhoff, MO, Dayhoff, MO. A model of evolutionary change in proteins. Atlas of Protein Sequence and Structure. 1978

Eddy, SR. Profile hidden Markov models. Bioinformatics. 1998; 14: 755-763 [OpenAIRE] [PubMed]

Eskin, E, Snir, S. Incorporating homologues into sequence embeddings for protein analysis. J. Bioinform. Comput. Biol.. 2007; 5: 717-738 [OpenAIRE] [PubMed]

Godzik, A. Topology fingerprint approach to the inverse protein folding problem. J. Mol. Biol.. 1992; 227: 227-238 [PubMed]

Henikoff, S, Henikoff, JG. Amino acid substitution matrices from protein blocks. Proc. Natl. Acad. Sci. USA. 1992; 89: 10915-10919 [OpenAIRE] [PubMed]

Holm, L, Sander, C. Protein structure comparison by alignment of distance matrices. J. Mol. Biol.. 1993; 233: 123-138 [PubMed]

Jaroszewski, L. FFAS03: a server for profile–profile sequence alignments. Nucleic Acids Res.. 2005; 33: W284-W288 [OpenAIRE] [PubMed]

Jones, DT. A new approach to protein fold recognition. Nature. 1992; 358: 86-89 [PubMed]

Kabsch, W, Sander, C. Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers. 1983; 22: 2577-2637 [OpenAIRE] [PubMed]

Lathrop, RH, Smith, TF. Global optimum protein threading with gapped alignment and empirical pair score functions. J. Mol. Biol.. 1996; 255: 641-666 [PubMed]

Liu, DC, Nocedal, J. On the limited memory BFGS method for large scale optimization. Math. Program.. 1989; 45: 503-528 [OpenAIRE]

Ma, J. A conditional neural fields model for protein threading. Bioinformatics. 2012; 28: i59-i66 [OpenAIRE] [PubMed]

33 references, page 1 of 3
Abstract
Motivation: Template-based modeling, including homology modeling and protein threading, is the most reliable method for protein 3D structure prediction. However, alignment errors and template selection are still the main bottleneck for current template-base modeling methods, especially when proteins under consideration are distantly related. Results: We present a novel context-specific alignment potential for protein threading, including alignment and template selection. Our alignment potential measures the log-odds ratio of one alignment being generated from two related proteins to being generated from two unrelated proteins, by integrating both local and globa...
Subjects
free text keywords: Statistics and Probability, Computational Theory and Mathematics, Biochemistry, Molecular Biology, Computational Mathematics, Computer Science Applications, Sequence alignment, Smith–Waterman algorithm, Multiple sequence alignment, Computer science, Threading (protein sequence), Structural alignment, Homology modeling, Bioinformatics, Loop modeling, Alignment-free sequence analysis, Ismb/Eccb 2013 Proceedings Papers Committee July 21 to July 23, 2013, Berlin, Germany, Original Papers, Protein Structure and Function
Related Organizations
Funded by
NSF| CAREER: Exact and Approximate Algorithms for 3D Structure Modeling of Protein-Protein Interactions
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1149811
  • Funding stream: Directorate for Computer & Information Science & Engineering | Division of Computing and Communication Foundations
,
NSF| Algorithm and Web Server for Low-homology Protein Threading
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 0960390
  • Funding stream: Directorate for Biological Sciences | Division of Biological Infrastructure
33 references, page 1 of 3

Akutsu, T, Miyano, S. On the approximation of protein threading. Theor. Comput. Sci.. 1999; 210: 261-275 [OpenAIRE]

Alexandrov, NN. Fast protein fold recognition via sequence to structure alignment and contact capacity potentials. Pac. Symp. Biocomput.. 1996: 53-72 [PubMed]

Biegert, A, Söding, J. Sequence context-specific profiles for homology searching. Proc. Natl. Acad. Sci. USA. 2009; 106: 3770-3775 [OpenAIRE] [PubMed]

Dayhoff, MO, Dayhoff, MO. A model of evolutionary change in proteins. Atlas of Protein Sequence and Structure. 1978

Eddy, SR. Profile hidden Markov models. Bioinformatics. 1998; 14: 755-763 [OpenAIRE] [PubMed]

Eskin, E, Snir, S. Incorporating homologues into sequence embeddings for protein analysis. J. Bioinform. Comput. Biol.. 2007; 5: 717-738 [OpenAIRE] [PubMed]

Godzik, A. Topology fingerprint approach to the inverse protein folding problem. J. Mol. Biol.. 1992; 227: 227-238 [PubMed]

Henikoff, S, Henikoff, JG. Amino acid substitution matrices from protein blocks. Proc. Natl. Acad. Sci. USA. 1992; 89: 10915-10919 [OpenAIRE] [PubMed]

Holm, L, Sander, C. Protein structure comparison by alignment of distance matrices. J. Mol. Biol.. 1993; 233: 123-138 [PubMed]

Jaroszewski, L. FFAS03: a server for profile–profile sequence alignments. Nucleic Acids Res.. 2005; 33: W284-W288 [OpenAIRE] [PubMed]

Jones, DT. A new approach to protein fold recognition. Nature. 1992; 358: 86-89 [PubMed]

Kabsch, W, Sander, C. Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers. 1983; 22: 2577-2637 [OpenAIRE] [PubMed]

Lathrop, RH, Smith, TF. Global optimum protein threading with gapped alignment and empirical pair score functions. J. Mol. Biol.. 1996; 255: 641-666 [PubMed]

Liu, DC, Nocedal, J. On the limited memory BFGS method for large scale optimization. Math. Program.. 1989; 45: 503-528 [OpenAIRE]

Ma, J. A conditional neural fields model for protein threading. Bioinformatics. 2012; 28: i59-i66 [OpenAIRE] [PubMed]

33 references, page 1 of 3
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