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HMMSTR: a hidden Markov model for local sequence-structure correlations in proteins.
J Mol Biol. 2000 Aug 04; 301(1):173-90.JM

Abstract

We describe a hidden Markov model, HMMSTR, for general protein sequence based on the I-sites library of sequence-structure motifs. Unlike the linear hidden Markov models used to model individual protein families, HMMSTR has a highly branched topology and captures recurrent local features of protein sequences and structures that transcend protein family boundaries. The model extends the I-sites library by describing the adjacencies of different sequence-structure motifs as observed in the protein database and, by representing overlapping motifs in a much more compact form, achieves a great reduction in parameters. The HMM attributes a considerably higher probability to coding sequence than does an equivalent dipeptide model, predicts secondary structure with an accuracy of 74.3 %, backbone torsion angles better than any previously reported method and the structural context of beta strands and turns with an accuracy that should be useful for tertiary structure prediction.

Authors+Show Affiliations

Department of Biology, Rensselaer Polytechnic Institute, Troy, NY 12180-3590, USA.No affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

Language

eng

PubMed ID

10926500

Citation

Bystroff, C, et al. "HMMSTR: a Hidden Markov Model for Local Sequence-structure Correlations in Proteins." Journal of Molecular Biology, vol. 301, no. 1, 2000, pp. 173-90.
Bystroff C, Thorsson V, Baker D. HMMSTR: a hidden Markov model for local sequence-structure correlations in proteins. J Mol Biol. 2000;301(1):173-90.
Bystroff, C., Thorsson, V., & Baker, D. (2000). HMMSTR: a hidden Markov model for local sequence-structure correlations in proteins. Journal of Molecular Biology, 301(1), 173-90.
Bystroff C, Thorsson V, Baker D. HMMSTR: a Hidden Markov Model for Local Sequence-structure Correlations in Proteins. J Mol Biol. 2000 Aug 4;301(1):173-90. PubMed PMID: 10926500.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - HMMSTR: a hidden Markov model for local sequence-structure correlations in proteins. AU - Bystroff,C, AU - Thorsson,V, AU - Baker,D, PY - 2000/8/5/pubmed PY - 2000/9/9/medline PY - 2000/8/5/entrez SP - 173 EP - 90 JF - Journal of molecular biology JO - J Mol Biol VL - 301 IS - 1 N2 - We describe a hidden Markov model, HMMSTR, for general protein sequence based on the I-sites library of sequence-structure motifs. Unlike the linear hidden Markov models used to model individual protein families, HMMSTR has a highly branched topology and captures recurrent local features of protein sequences and structures that transcend protein family boundaries. The model extends the I-sites library by describing the adjacencies of different sequence-structure motifs as observed in the protein database and, by representing overlapping motifs in a much more compact form, achieves a great reduction in parameters. The HMM attributes a considerably higher probability to coding sequence than does an equivalent dipeptide model, predicts secondary structure with an accuracy of 74.3 %, backbone torsion angles better than any previously reported method and the structural context of beta strands and turns with an accuracy that should be useful for tertiary structure prediction. SN - 0022-2836 UR - https://www.unboundmedicine.com/medline/citation/10926500/HMMSTR:_a_hidden_Markov_model_for_local_sequence_structure_correlations_in_proteins_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0022-2836(00)93837-3 DB - PRIME DP - Unbound Medicine ER -