Abstract

Asparagine residues in proteins undergo spontaneous deamidation, a post-translational modification that may act as a molecular clock for the regulation of protein function and turnover. Asparagine deamidation is modulated by protein local sequence, secondary structure and hydrogen bonding. We present NGOME, an algorithm able to predict non-enzymatic deamidation of internal asparagine residues in proteins in the absence of structural data, using sequence-based predictions of secondary structure and intrinsic disorder. Compared to previous algorithms, NGOME does not require three-dimensional structures yet yields better predictions than available sequence-only methods. Four case studies of specific proteins show how NGOME may help the user identify deamidation-prone asparagine residues, often related to protein gain of function, protein degradation or protein misfolding in pathological processes. A fifth case study applies NGOME at a proteomic scale and unveils a correlation between asparagine deamidation and protein degradation in yeast. NGOME is freely available as a webserver at the National EMBnet node Argentina, URL: http://www.embnet.qb.fcen.uba.ar/ in the subpage “Protein and nucleic acid structure and sequence analysis”.

Highlights

  • Protein deamidation is a post-translational modification in which the side chain amide group of a glutamine or asparagine residue is transformed into an acidic carboxylate group [1]

  • We present NGOME, a sequence-based method for the prediction of asparagine deamidation from predicted structural features

  • The third table is sorted by residue number, while the fourth table is sorted by t50(NGOME). This experiment tests whether an asparagine residue introduced by a point mutation at a particular position would deamidate according to NGOME

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Summary

Introduction

Protein deamidation is a post-translational modification in which the side chain amide group of a glutamine or asparagine residue is transformed into an acidic carboxylate group [1]. We present NGOME, a sequence-based method for the prediction of asparagine deamidation from predicted structural features. We compiled a database of 281 asparagine residues (67 positives and 214 negatives) in 39 proteins to train NGOME (see S1 Table in S1 File).

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