Chemistry and Physics Faculty Articles

Document Type

Article

Publication Date

7-16-2021

Publication Title

bioRxiv

Keywords

Bioinformatics

First Page

1

Last Page

23

Abstract

A three-dimensional representation of the twenty proteinogenic amino acids in a physicochemical space is presented. Vectors corresponding to amino acid substitutions are classified based on whether they are accessible via a single-nucleotide mutation. It is shown that the standard genetic code establishes a “choice architecture” that permits nearly independent tuning of the properties related with size and those related with hydrophobicity. This work sheds light on the metarules of evolvability that may have shaped the standard genetic code to increase the probability that adaptive point mutations will be generated. An illustration of the usefulness of visualizing amino acid substitutions in a 3D physicochemical space is shown using data collected from the SARS-CoV-2 receptor binding domain. The substitutions most responsible for antibody escape are almost always inaccessible via single nucleotide mutation, and also change multiple properties concurrently. The results of this research can extend our understanding of certain hereditary disorders caused by point mutations, as well as guide the development of rational protein and vaccine design.

Comments

The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.

Creative Commons License

Creative Commons Attribution-No Derivative Works 4.0 International License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 International License.

DOI

10.1101/2021.07.15.452549

Download

Included in

Chemistry Commons

COinS