SVMyr: A Web Server Detecting Co- and Post-translational Myristoylation in Proteins

• Published in: Journal of molecular biology 2022-06, Vol.434 (11), p.167605-167605, Article 167605
• Main Authors: Madeo, Giovanni, Savojardo, Castrense, Martelli, Pier Luigi, Casadio, Rita
• Format: Article
• Language: English
• Subjects: lipidation; position specific scoring matrix; post-translational modification; protein myristoylation; support vector machines
• ISSN: 0022-2836; 1089-8638
• DOI: 10.1016/j.jmb.2022.167605

SVMyr is a fast method, able to scan, for example, the entire human proteome in about 15 minutes. This makes SVMyr well-suited for genome-wide analysis. [Display omitted] •Myristoylation (MYR) is a protein modification involved in crucial processes, such as signal transduction and apoptosis.•Glycine MYR occurs during protein translation (co-translation) or after (post-translation).•SVMyr is a novel and unique web server for prediction of both co- and post-translational MYR sites.•SVMyr combines compositional/physicochemical properties with SVMs trained on 232 experimental N-terminal octapeptides.•In blind testing, SVMyr outperforms other methods in predicting co-translational MYR reporting an MCC of 0.58.•SVMyr correctly predicts post-translational MYR in 11 out of 15 proteins derived from SwissProt and literature. Myristoylation (MYR) is a protein modification where a myristoyl group is covalently attached to an exposed (N-terminal) glycine residue. Glycine myristoylation occurs during protein translation (co-translation) or after (post-translation). Myristoylated proteins have a role in signal transduction, apoptosis, and pathogen-mediated processes and their prediction can help in functionally annotating the fraction of proteins undergoing MYR in different proteomes. Here we present SVMyr, a web server allowing the detection of both co- and post-translational myristoylation sites, based on Support Vector Machines (SVM). The input encodes composition and physicochemical features of the octapeptides, known to act as substrates and to physically interact with N-myristoyltransferases (NMTs), the enzymes catalyzing the myristoylation reaction. The method, adopting a cross validation procedure, scores with values of Area Under the Curve (AUC) and Matthews Correlation Coefficient (MCC) of 0.92 and 0.61, respectively. When benchmarked on an independent dataset including experimentally detected 88 medium/high confidence co-translational myristoylation sites and 528 negative examples, SVMyr outperforms available methods, with AUC and MCC equal to 0.91 and 0.58, respectively. A unique feature of SVMyr is the ability to predict post-translational myristoylation sites by coupling the trained SVMs with the detection of caspase cleavage sites, identified by searching regular motifs matching upstream caspase cleavage sites, as reported in literature. Finally, SVMyr confirms 96% of the UniProt set of the electronically annotated myristoylated proteins (31,048) and ident