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Updated: Jul 12, 2026
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Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
Published on: August 16, 2017
Empirical determination of effective gap penalties for sequence comparison
1Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA 22908, USA.
Bioinformatics (Oxford, England)
|November 9, 2002
Summary
Empirically derived gap penalties improve protein sequence similarity searches. Optimal penalties vary with evolutionary distance, enhancing alignment accuracy for distant homologs and tandem repeats.
Area of Science:
- Bioinformatics
- Computational Biology
- Structural Bioinformatics
Background:
- Lack of a guiding theory for gap penalty selection in local sequence alignment.
- Need for empirical determination of optimal gap penalties for protein similarity searches.
Purpose of the Study:
- Determine effective gap penalties for protein sequence similarity searches using substitution matrices.
- Establish a relationship between optimal gap penalties and evolutionary distance (Point Accepted Mutations - PAMs).
Main Methods:
- Embedding real and simulated protein homologs into a searchable database.
- Systematically searching the database to identify gap penalties yielding the best statistical significance for distant homologs.
Main Results:
- The optimal gap opening penalty (q+r) is dependent on evolutionary distance, while the gap extension penalty (r) remains constant.
- Optimal gap penalties are defined by the formula: q=25-0.1 * (target PAM distance), r=5 for matrices scaled in 1/3 bit units.
- These penalties improve expectation values by over an order of magnitude for short sequences.
Conclusions:
- Provides an empirical foundation for selecting gap penalties in protein sequence alignment.
- Demonstrates the behavior of optimal gap penalties as a function of evolutionary distance.
- Enhances the alignment of proteins with tandemly repeated short sequences.
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