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Simultaneous sequence alignment and tree construction using hidden Markov models.

Robert C Edgar1, Kimmen Sjölander

  • 1Department of Bioengineering, University of California, Berkeley, California 94720, USA. bob@drive5.com

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|February 27, 2003
PubMed
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We developed SATCHMO, a novel algorithm for simultaneous protein sequence alignment and phylogenetic tree estimation. This tool aids in identifying conserved protein domains and understanding biological mechanisms, performing comparably to existing methods.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Evolution

Background:

  • Accurate multiple sequence alignments (MSAs) are crucial for phylogenetic tree inference and identifying conserved protein domains.
  • Existing methods often estimate trees and alignments separately, potentially limiting accuracy.
  • Understanding protein domain evolution and function requires robust alignment and treeing methodologies.

Purpose of the Study:

  • To introduce SATCHMO, a novel algorithm that simultaneously estimates phylogenetic trees and generates multiple sequence alignments for protein sequence sets.
  • To utilize Hidden Markov Models (HMMs) within the algorithm for improved alignment and structural prediction.
  • To evaluate SATCHMO's performance against established tools and demonstrate its application in identifying functional protein domains.

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Main Methods:

  • SATCHMO simultaneously infers a phylogenetic tree and generates MSAs for each node.
  • Alignments at each node predict structurally conserved elements, varying in length and amino acid preferences.
  • Hidden Markov Models (HMMs) are generated per node to guide branching, alignment, and region prediction.

Main Results:

  • SATCHMO demonstrates performance comparable to ClustalW and UCSC SAM HMM on the BAliBASE benchmark dataset.
  • The algorithm successfully identified protein domains in potassium channels.
  • These findings have implications for understanding tumor necrosis factor alpha's effect on potassium currents.

Conclusions:

  • SATCHMO offers a powerful, integrated approach for simultaneous tree estimation and multiple sequence alignment.
  • The method effectively predicts conserved protein structures and aids in functional domain identification.
  • This tool holds promise for advancing research in molecular evolution, protein function, and disease mechanisms.