An interactive visualization tool to explore the biophysical properties of amino acids and their contribution to substitution matrices

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Abstract

Background: Quantitative descriptions of amino acid similarity, expressed as probabilistic models of evolutionary interchangeability, are central to many mainstream bioinformatic procedures such as sequence alignment, homology searching, and protein structural prediction. Here we present a web-based, user-friendly analysis tool that allows any researcher to quickly and easily visualize relationships between these bioinformatic metrics and to explore their relationships to underlying indices of amino acid molecular descriptors. Results: We demonstrate the three fundamental types of question that our software can address by taking as a specific example the connections between 49 measures of amino acid biophysical properties (e.g., size, charge and hydrophobicity), a generalized model of amino acid substitution (as represented by the PAM74-100 matrix), and the mutational distance that separates amino acids within the standard genetic code (i.e., the number of point mutations required for interconversion during protein evolution). We show that our software allows a user to recapture the insights from several key publications on these topics in just a few minutes. Conclusion: Our software facilitates rapid, interactive exploration of tree interconnected topics: (i) the multidimentional molecular descriptors of the twenty proteinaceous amino acids, (ii) the correlation of these biophysical measurements with observed patterns of amino acid substitution, and (iii) the causal basis for differences between any two observed patterns of amino acid substitution. This software acts as an intuitive bioinformatic tool that can guide more comprehensive statistical analyses to a diverse of specific research questions. © 2006 Bulka el al; licensee BioMed Central Ltd.

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Bulka, B., desJardins, M., & Freeland, S. J. (2006). An interactive visualization tool to explore the biophysical properties of amino acids and their contribution to substitution matrices. BMC Bioinformatics, 7. https://doi.org/10.1186/1471-2105-7-329

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