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Structure-derived substitution matrices for alignment of distantly related sequences
A Prlić1, F S Domingues, M J Sippl
1Center of Applied Molecular Engineering, Institute for Chemistry and Biochemistry, University of Salzburg, Jakob-Haringerstrasse 3, A-5020 Salzburg, Austria.
Protein Engineering
|August 31, 2000
Summary
New substitution matrices derived from protein structures improve sequence alignment for distantly related proteins. These structure-derived matrices enhance the accuracy of inferring evolutionary and functional relationships.
Area of Science:
- Bioinformatics
- Computational Biology
- Structural Biology
Background:
- Sequence alignment is crucial for understanding protein relationships.
- Alignment quality relies heavily on the chosen substitution matrix.
- Existing matrices may not effectively capture relationships in distantly related proteins.
Purpose of the Study:
- To develop novel substitution matrices using structural information.
- To evaluate the performance of these structure-derived matrices against existing ones.
- To assess the impact of evolutionary divergence on alignment accuracy.
Main Methods:
- Deriving substitution matrices from structural superimpositions of protein pairs.
- Comparing performance of new matrices with 12 established matrices.
- Analyzing the influence of evolutionary relationships on alignment results.
Main Results:
- Structure-derived matrices demonstrated superior performance for distantly related sequences.
- Matrices derived from structural data are effective for remote homology detection.
- Evolutionary distance significantly impacts the accuracy of sequence alignment.
Conclusions:
- Novel substitution matrices based on protein structure improve sequence alignment.
- These matrices are particularly valuable for comparing proteins with low sequence similarity.
- The findings offer a more robust method for inferring evolutionary and functional connections.