Computational Prediction of Protein Secondary Structure from Sequence. (1st November 2016)

• Record Type: Journal Article
• Authors: Meng, Fanchi; Kurgan, Lukasz
• Editors: Coligan, John E.; Dunn, Ben M.; Speicher, David W.; Wingfield, Paul T.
• Is Part Of: Current protocols in protein science. Volume 86(2016)
• Page Start: 2.3.1
• Page End: 2.3.10
• Publication Date: 2016-11-01
• Subjects: coil -- DSSP -- helix -- secondary structure of proteins -- strand -- prediction; Proteins -- Laboratory manuals; Proteins; Clinical Laboratory Techniques; Genetic Techniques; Immunologic Techniques; Proteins; Laboratory manuals; 572.6028
• DOI: 10.1002/cpps.19
• Languages: English
• ISSNs: 1934-3655

Abstract

Abstract: Secondary structure of proteins refers to local and repetitive conformations, such as α‐helices and β‐strands, which occur in protein structures. Computational prediction of secondary structure from protein sequences has a long history with three generations of predictive methods. This unit summarizes several recent third‐generation predictors. We discuss their inputs and outputs, availability, and predictive performance and explain how to perform and interpret their predictions. We cover methods for the prediction of the 3‐class secondary structure states (helix, strand, and coil) as well as the 8‐class secondary structure states. Recent empirical assessments and our small‐scale analysis reveal that these predictions are characterized by high levels of accuracy, between 70% and 80%. We emphasize that modern predictors are available to end users in the form of convenient‐to‐use Web servers and stand‐alone software. © 2016 by John Wiley & Sons, Inc.