A Systematic Review on Popularity, Application and Characteristics of Protein Secondary Structure Prediction Tools

Current Drug Discovery Technologies
Elaheh Kashani-AminAzadeh Ebrahim-Habibi

Abstract

Prediction of proteins' secondary structure is one of the major steps in the generation of homology models. These models provide structural information which is used to design suitable ligands for potential medicinal targets. However, selecting a proper tool between multiple Secondary Structure Prediction (SSP) options is challenging. The current study is an insight into currently favored methods and tools, within various contexts. A systematic review was performed for a comprehensive access to recent (2013-2016) studies which used or recommended protein SSP tools. Three databases, Web of Science, PubMed and Scopus were systematically searched and 99 out of the 209 studies were finally found eligible to extract data. Four categories of applications for 59 retrieved SSP tools were: (I) prediction of structural features of a given sequence, (II) evaluation of a method, (III) providing input for a new SSP method and (IV) integrating an SSP tool as a component for a program. PSIPRED was found to be the most popular tool in all four categories. JPred and tools utilizing PHD (Profile network from HeiDelberg) method occupied second and third places of popularity in categories I and II. JPred was only found in the two first categories,...Continue Reading

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Citations

May 10, 2019·Cell Biochemistry and Biophysics·Elaheh Kashani-AminAzadeh Ebrahim-Habibi
Oct 30, 2020·Nucleic Acids Research·Bi ZhaoLukasz Kurgan

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