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N-terminal modifications of cellular proteins: The enzymes involved, their substrate specificities and biological effects.

ABSTRACT: The vast majority of eukaryotic proteins are N-terminally modified by one or more processing enzymes. Enzymes acting on the very first amino acid of a polypeptide include different peptidases, transferases, and ligases. Methionine aminopeptidases excise the initiator methionine leaving the nascent polypeptide with a newly exposed amino acid that may be further modified. N-terminal acetyl-, methyl-, myristoyl-, and palmitoyltransferases may attach an acetyl, methyl, myristoyl, or palmitoyl group, respectively, to the ?-amino group of the target protein N-terminus. With the action of ubiquitin ligases, one or several ubiquitin molecules are transferred, and hence, constitute the N-terminal modification. Modifications at protein N-termini represent an important contribution to proteomic diversity and complexity, and are essential for protein regulation and cellular signaling. Consequently, dysregulation of the N-terminal modifying enzymes is implicated in human diseases. We here review the different protein N-terminal modifications occurring co- or post-translationally with emphasis on the responsible enzymes and their substrate specificities.

SUBMITTER: Varland S

PROVIDER: S-EPMC4692089 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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N-terminal modifications of cellular proteins: The enzymes involved, their substrate specificities and biological effects.

Varland Sylvia S Osberg Camilla C Arnesen Thomas T

Proteomics 20150616 14

The vast majority of eukaryotic proteins are N-terminally modified by one or more processing enzymes. Enzymes acting on the very first amino acid of a polypeptide include different peptidases, transferases, and ligases. Methionine aminopeptidases excise the initiator methionine leaving the nascent polypeptide with a newly exposed amino acid that may be further modified. N-terminal acetyl-, methyl-, myristoyl-, and palmitoyltransferases may attach an acetyl, methyl, myristoyl, or palmitoyl group, ...[more]

PMID: 25914051

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Project description:BackgroundMembrane transport proteins (transporters) move hydrophilic substrates across hydrophobic membranes and play vital roles in most cellular functions. Transporters represent a diverse group of proteins that differ in topology, energy coupling mechanism, and substrate specificity as well as sequence similarity. Among the functional annotations of transporters, information about their transporting substrates is especially important. The experimental identification and characterization of transporters is currently costly and time-consuming. The development of robust bioinformatics-based methods for the prediction of membrane transport proteins and their substrate specificities is therefore an important and urgent task.ResultsSupport vector machine (SVM)-based computational models, which comprehensively utilize integrative protein sequence features such as amino acid composition, dipeptide composition, physico-chemical composition, biochemical composition, and position-specific scoring matrices (PSSM), were developed to predict the substrate specificity of seven transporter classes: amino acid, anion, cation, electron, protein/mRNA, sugar, and other transporters. An additional model to differentiate transporters from non-transporters was also developed. Among the developed models, the biochemical composition and PSSM hybrid model outperformed other models and achieved an overall average prediction accuracy of 76.69% with a Mathews correlation coefficient (MCC) of 0.49 and a receiver operating characteristic area under the curve (AUC) of 0.833 on our main dataset. This model also achieved an overall average prediction accuracy of 78.88% and MCC of 0.41 on an independent dataset.ConclusionsOur analyses suggest that evolutionary information (i.e., the PSSM) and the AAIndex are key features for the substrate specificity prediction of transport proteins. In comparison, similarity-based methods such as BLAST, PSI-BLAST, and hidden Markov models do not provide accurate predictions for the substrate specificity of membrane transport proteins. TrSSP: The Transporter Substrate Specificity Prediction Server, a web server that implements the SVM models developed in this paper, is freely available at http://bioinfo.noble.org/TrSSP.

Dataset Information

N-terminal modifications of cellular proteins: The enzymes involved, their substrate specificities and biological effects.

Publications

N-terminal modifications of cellular proteins: The enzymes involved, their substrate specificities and biological effects.

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