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Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
Published on: April 13, 2022
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A broader context for understanding amino acid alphabet optimality.
Christopher Mayer-Bacon1, Stephen J Freeland1
1Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 25250, USA.
Journal of Theoretical Biology
|March 8, 2021
Summary
The standard 20 amino acids used by life show unusual distribution in size, charge, and hydrophobicity. This study confirms these features are robust, particularly for volume and hydrophobicity, but questions their role in protein sequences.
Area of Science:
- Biochemistry
- Astrobiology
- Origin of Life Studies
Background:
- Prior research suggests unique physicochemical properties of the 20 genetically encoded amino acids.
- Variations in methodologies across studies necessitate a consolidated framework.
Purpose of the Study:
- To unify and clarify the unusual features of the genetically encoded amino acid set.
- To compare the distribution of these amino acids against random samples of plausible alternatives.
Main Methods:
- Utilized quantitative descriptors for size, charge (pKa), and hydrophobicity.
- Compared the distribution of the 20 standard amino acids with random samples of plausible L-α-amino acids.
- Analyzed both the full set and prebiotically plausible subsets of amino acids.
Main Results:
- The standard 20 amino acids exhibit an unusually broad range in volume and even distribution in hydrophobicity.
- Exceptional range and evenness in charge (pKa) were observed for full structures, not sidechains.
- These remarkable features are less pronounced when considering only prebiotically plausible amino acids.
Conclusions:
- The unusual physicochemical properties of the genetically encoded amino acids are robust, especially for volume and hydrophobicity.
- The findings challenge prior interpretations regarding the role of amino acid sidechains in protein sequences.
- Further research is suggested to explore optimality theory in the context of amino acid selection.
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