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Updated: Feb 8, 2026

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
An evolutionary model motivated by physicochemical properties of amino acids reveals variation among proteins
1Department of Biology and Genetics Institute, University of Florida, Gainesville, FL, USA.
Motivation:
The relative rates of amino acid interchanges over evolutionary time are likely to vary among proteins. Variation in those rates has the potential to reveal information about constraints on proteins. However, the most straightforward model that could be used to estimate relative rates of amino acid substitution is parameter-rich and it is therefore impractical to use for this purpose.
Results:
A six-parameter model of amino acid substitution that incorporates information about the physicochemical properties of amino acids was developed. It showed that amino acid side chain volume, polarity and aromaticity have major impacts on protein evolution. It also revealed variation among proteins in the relative importance of those properties. The same general approach can be used to improve the fit of empirical models such as the commonly used PAM and LG models.
Availability And Implementation:
Perl code and test data are available from https://github.com/ebraun68/sixparam.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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