Predicting Sequence Features, Function, and Structure of Proteins Using MESSA. Issue 1 (15th July 2019)

• Record Type: Journal Article
• Authors: Bhat, Archana S.; Grishin, Nick V.
• Editors: Baxevanis, Andreas D.; Petsko, Gregory A.; Stein, Lincoln D.; Stormo, Gary D.
• Is Part Of: Current protocols in bioinformatics. Volume 67:Issue 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-07-15
• Subjects: MESSA -- predictions -- protein sequence -- structure and function; Bioinformatics -- Laboratory manuals; Nucleotide sequence -- Laboratory manuals; Amino acid sequence -- Laboratory manuals; Base Sequence; Amino Acid Sequence; Computational Biology -- methods; Databases, Genetic; Proteins -- analysis; Sequence Analysis -- methods; Sequence Homology; Amino acid sequence; Bioinformatics; Nucleotide sequence; Laboratory Manuals; Laboratory manuals; 570.285
• DOI: 10.1002/cpbi.84
• Languages: English
• ISSNs: 1934-3396

Abstract

Abstract: MEta‐Server for protein Sequence Analysis (MESSA) is a tool that facilitates widespread protein sequence analysis by gathering structural (local sequence properties and three‐dimensional structure) and functional (annotations from SWISS‐PROT, Gene Ontology terms, and enzyme classification) predictions for a query protein of interest. MESSA uses multiple well‐established tools to offer consensus‐based predictions on important aspects of protein sequence analysis. Being freely available for noncommercial users and with a user‐friendly interface, MESSA serves as an umbrella platform that overcomes the absence of a comprehensive tool for predictive protein analysis. This article reveals how to access MESSA via the Web and shows how to input a protein sequence to analyze using the MESSA web server. It also includes a detailed explanation of the output from MESSA to aid in better interpretation of results. © 2019 by John Wiley & Sons, Inc.