Fine-Grained Synonymous Codon Usage Patterns and their Potential Role in Functional Protein Production

Multiple computational models exist that leverage the idea that some codons are “preferred” to others when producing functional proteins. In this work, we aim to address the following two questions: (i) do proteins have similar codon usage subprofiles?, (ii) if so, can they be associated to specific Gene Ontology (GO) terms? To answer these questions, we analyze two different data sets E. coli and S. cerevisiae (yeast). For both, we use codon usage profiles that have been linked to protein co-translational folding and perform unsupervised clustering. Significantly, our clusters determine biologically meaningful patterns consistent with previously published observations. Our results suggest that codon patterns have potential to be incorporated into more complex deep learning-inspired frameworks in future work to better understand and predict functional protein production in a cell.