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A protein alignment scoring system sensitive at all evolutionary distances

S F Altschul1

  • 1National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894.

Journal of Molecular Evolution
|March 1, 1993
PubMed
Summary
This summary is machine-generated.

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This study introduces a scoring system for protein sequence alignments that uses a range of substitution matrices to detect homologies across all evolutionary distances. Employing the correct matrices significantly improves statistical significance compared to using a single, potentially mismatched matrix.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Evolution

Background:

  • Protein sequence alignments rely on substitution matrices to score amino acid pair similarities.
  • Existing matrices are often tailored to specific evolutionary distances, potentially missing distant homologies.

Purpose of the Study:

  • To develop a scoring system sensitive to all detectable evolutionary distances in protein sequence alignments.
  • To formalize the concept of using a range of substitution matrices for comprehensive homology detection.

Main Methods:

  • Assumed a simple random protein model to demonstrate that substitution matrices are implicitly log-odds matrices.
  • Derived probability distributions from a protein evolution model to construct tailored substitution matrices.
  • Defined and analyzed the statistical behavior of a scoring system designed for variable evolutionary distances.

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Main Results:

  • A single substitution matrix, if mismatched to the evolutionary distance, can drastically reduce statistical significance (by a factor of five).
  • Estimating the appropriate evolutionary distance for an alignment costs minimal information (approx. 2 bits).
  • A scoring system sensitive across all detectable evolutionary distances was formalized and analyzed.

Conclusions:

  • Using a range of substitution matrices adapted to various evolutionary distances is crucial for robust protein homology detection in database searches.
  • The proposed scoring system enhances sensitivity and statistical rigor by accounting for unknown evolutionary distances.
  • Failure to consider evolutionary distance can lead to significant loss of statistical power in identifying protein relationships.