Khalique Newaz1,2,3, Gabriel Wright1,3, Jacob Piland1,2,3, Jun Li4, Patricia L Clark5, Scott J Emrich6, Tijana Milenković1,2,3. 1. Department of Computer Science and Engineering. 2. Center for Network and Data Science. 3. Eck institute for Global Health. 4. Department of Applied and Computational Mathematics and Statistics. 5. Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA. 6. Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA.
Abstract
MOTIVATION: Most amino acids are encoded by multiple synonymous codons, some of which are used more rarely than others. Analyses of positions of such rare codons in protein sequences revealed that rare codons can impact co-translational protein folding and that positions of some rare codons are evolutionarily conserved. Analyses of their positions in protein 3-dimensional structures, which are richer in biochemical information than sequences alone, might further explain the role of rare codons in protein folding. RESULTS: We model protein structures as networks and use network centrality to measure the structural position of an amino acid. We first validate that amino acids buried within the structural core are network-central, and those on the surface are not. Then, we study potential differences between network centralities and thus structural positions of amino acids encoded by conserved rare, non-conserved rare and commonly used codons. We find that in 84% of proteins, the three codon categories occupy significantly different structural positions. We examine protein groups showing different codon centrality trends, i.e. different relationships between structural positions of the three codon categories. We see several cases of all proteins from our data with some structural or functional property being in the same group. Also, we see a case of all proteins in some group having the same property. Our work shows that codon usage is linked to the final protein structure and thus possibly to co-translational protein folding. AVAILABILITY AND IMPLEMENTATION: https://nd.edu/∼cone/CodonUsage/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Most amino acids are encoded by multiple synonymous codons, some of which are used more rarely than others. Analyses of positions of such rare codons in protein sequences revealed that rare codons can impact co-translational protein folding and that positions of some rare codons are evolutionarily conserved. Analyses of their positions in protein 3-dimensional structures, which are richer in biochemical information than sequences alone, might further explain the role of rare codons in protein folding. RESULTS: We model protein structures as networks and use network centrality to measure the structural position of an amino acid. We first validate that amino acids buried within the structural core are network-central, and those on the surface are not. Then, we study potential differences between network centralities and thus structural positions of amino acids encoded by conserved rare, non-conserved rare and commonly used codons. We find that in 84% of proteins, the three codon categories occupy significantly different structural positions. We examine protein groups showing different codon centrality trends, i.e. different relationships between structural positions of the three codon categories. We see several cases of all proteins from our data with some structural or functional property being in the same group. Also, we see a case of all proteins in some group having the same property. Our work shows that codon usage is linked to the final protein structure and thus possibly to co-translational protein folding. AVAILABILITY AND IMPLEMENTATION: https://nd.edu/∼cone/CodonUsage/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Ian M Walsh; Micayla A Bowman; Iker F Soto Santarriaga; Anabel Rodriguez; Patricia L Clark Journal: Proc Natl Acad Sci U S A Date: 2020-02-03 Impact factor: 11.205
Authors: Lesley H Greene; Tony E Lewis; Sarah Addou; Alison Cuff; Tim Dallman; Mark Dibley; Oliver Redfern; Frances Pearl; Rekha Nambudiry; Adam Reid; Ian Sillitoe; Corin Yeats; Janet M Thornton; Christine A Orengo Journal: Nucleic Acids Res Date: 2006-11-29 Impact factor: 16.971