Bayesian approach to sequence alignment algorithms for protein structure recognition

Richard A. Goldstein, Zaida Ann Luthey-Schulten, Peter G. Wolynes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A theoretical basis for the alignment of a protein sequence to a set of protein structure templates is presented, based on a Bayesian statistical analysis. The optimal Hamiltonian for this threading is closely related to the Hamiltonian optimized for molecular dynamics based on spin-glass theory. The Bayesian theory provides the optimal penalty functions for insertions and deletions in the alignment, which can be put in the form of a chemical potential. In contrast to standard methods for determining gap penalties, these penalties involve the logarithm of the probability distribution of gaps in alignments against correct templates as compared to the probability distribution of gaps in alignments against random templates, as determined self-consistently. Sequences of unknown proteins can be aligned to known protein structures, identifying similar structural motifs and generating reasonably correct alignments.

Original languageEnglish (US)
Title of host publicationProceedings of the Hawaii International Conference on System Sciences
EditorsJay F. Nunamaker, Ralph H.Jr. Sprague
PublisherPubl by IEEE
Pages306-315
Number of pages10
ISBN (Print)0818650907
StatePublished - Jan 1 1995
EventProceedings of the 27th Hawaii International Conference on System Sciences (HICSS-27). Part 4 (of 5) - Wailea, HI, USA
Duration: Jan 4 1994Jan 7 1994

Publication series

NameProceedings of the Hawaii International Conference on System Sciences
Volume5
ISSN (Print)1060-3425

Other

OtherProceedings of the 27th Hawaii International Conference on System Sciences (HICSS-27). Part 4 (of 5)
CityWailea, HI, USA
Period1/4/941/7/94

ASJC Scopus subject areas

  • Computer Science(all)

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  • Cite this

    Goldstein, R. A., Luthey-Schulten, Z. A., & Wolynes, P. G. (1995). Bayesian approach to sequence alignment algorithms for protein structure recognition. In J. F. Nunamaker, & R. H. J. Sprague (Eds.), Proceedings of the Hawaii International Conference on System Sciences (pp. 306-315). (Proceedings of the Hawaii International Conference on System Sciences; Vol. 5). Publ by IEEE.