Analysis of the Uniprot Repertoire of Amino Acid Post-translational Modifications

IGNACIO ENRIQUE SANCHEZ; NICOLÁS AGUSTÍN MÉNDEZ

Bariloche

Congreso; Analysis of the Uniprot Repertoire of Amino Acid Post-translational Modifications; 2014

Asociacion Argentina de Bioinformatica y Biologia Computacional

BackgroundThe standard genetic code only accounts for the 20 most common amino acid residues. However, many amino acids in proteins are modified post-translationally. Thus, current sequence representations for manual or in silico analysis provide incomplete information. We set out to describe the currently known post-translational modifications in terms of prevalence, phylogenetic distribution and their relationship with the chemical reactivity of the modified standard amino acid.Materials and MethodsWe acquired the Uniprot list of post-translational modifications (2014_03 release) and transferred it to a MySQL database using python code. We queried the database to evaluate the distribution of post-translational modifications in the three domains of life and count the prevalence of each post-translational modification. As a proxy for chemical reactivity, we used the estimation of T. Krick et al. [1].Regression analysis was performed using R standard functions. The p-values for the calculated coefficients of determination were obtained by permutation tests as performed by P. Legendre?s multRegress R function [2]. Scatterplots were constructed using R.The Venn diagram used to illustrate the distribution of post-translational modifications was constructed using the BioVenn software [3].ResultsWe found 466 unique post-translational modifications in the Uniprot ontology. Note that most glycations, lipidations, disulfide bridges and cross-links are not included in the Uniprot post-translational modification ontology and were therefore not considered at this stage of analysis.We quantified the number of post-translational modifications for each of the 20 standard amino acids and the number of modifications involving one, two or more residues (Table 1). We also examined the distribution of post-translational modifications in the three domains of life (Figure 1).Last, we quantified the correlation between the number of post-translational modifications per standard amino acid and the chemical reactivity of each amino acid.ConclusionsWe propose that the standard amino acid alphabet should be expanded to include the diverse universe of post-translational modifications. Since including all post-translational modifications seems impractical, quantitative prevalence data will be needed to decide which post-translational modifications are most important. The results are likely to be different in the three domains of life and may be explained in part by the chemical reactivity of the standard amino acids.