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Selecting the Right Similarity-Scoring Matrix.

William R Pearson1

  • 1University of Virginia School of Medicine, Charlottesville, Virginia.

Current Protocols in Bioinformatics
|February 11, 2014
PubMed
Summary
This summary is machine-generated.

Choosing the right protein similarity scoring matrices (like BLOSUM62) is crucial for evolutionary analysis. Deep matrices suit sensitive, full-length searches, while shallow matrices are better for short domains or recent evolutionary relationships.

Keywords:
BLOSUM matricesPAM matricessequence alignmentsimilarity scoring matrices

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Protein similarity searching programs like BLASTP, SSEARCH, and FASTA utilize scoring matrices to identify evolutionary relationships.
  • Scoring matrices vary in effectiveness based on evolutionary distances, with "deep" matrices (e.g., BLOSUM62) targeting distant relationships and "shallow" matrices (e.g., VTML) targeting recent ones.

Purpose of the Study:

  • To discuss the theoretical foundations guiding the selection of protein and DNA similarity scoring matrices and gap penalties.
  • To provide guidance on choosing appropriate scoring matrices for different evolutionary scales and search objectives.

Main Methods:

  • The study discusses the principles behind different scoring matrices, including BLOSUM62, BLOSUM50, and VTML series.
  • It examines the trade-offs between sensitivity, alignment length, and potential overextension associated with deep versus shallow matrices.
  • The role of match/mismatch parameters in DNA searches for defining evolutionary look-back times and domain boundaries is also considered.

Main Results:

  • "Deep" scoring matrices (BLOSUM62, BLOSUM50) offer high sensitivity for full-length protein sequences but may require longer alignments and risk overextension.
  • "Shallow" scoring matrices are more effective for identifying short protein domains or for searches focusing on recently diverged organisms.
  • The choice of scoring matrix and gap penalties directly impacts the accuracy and scope of evolutionary inferences.

Conclusions:

  • Deep scoring matrices are recommended for sensitive searches using full-length protein sequences.
  • Shallow scoring matrices are preferable for analyzing short domains or when a restricted evolutionary perspective is needed.
  • Optimal selection of scoring matrices and gap penalties is essential for accurate protein and DNA similarity searches across various evolutionary scales.