scholarly journals Side-chain Conformations Cooperatively Restricted in Protein Secondary Structure. I. A Novel Method for Exhaustive Structure Searching.

1996 ◽  
Vol 72 (7) ◽  
pp. 143-148
Author(s):  
Haruki NAKAMURA ◽  
Ryuji TANIMURA ◽  
Akinori KIDERA
Keyword(s):  
Secondary Structure ◽  
Protein Secondary Structure ◽  
Side Chain ◽  
Novel Method ◽  
Chain Conformations

scholarly journals An Algorithm for Computing Side Chain Conformational Variations of a Protein Tunnel/Channel

Molecules ◽  
2018 ◽  
Vol 23 (10) ◽  
pp. 2459
Author(s):  
Udeok Seo ◽  
Ku-Jin Kim ◽  
Beom Kang
Keyword(s):  
Amino Acids ◽  
Maximum Size ◽  
Protein Molecule ◽  
Divide And Conquer ◽  
Side Chain ◽  
Conformational Variations ◽  
Novel Method ◽  
Pass Through ◽  
Chain Conformations ◽  
Local Side

In this paper, a novel method to compute side chain conformational variations for a protein molecule tunnel (or channel) is proposed. From the conformational variations, we compute the flexibly deformed shapes of the initial tunnel, and present a way to compute the maximum size of the ligand that can pass through the deformed tunnel. By using the two types of graphs corresponding to amino acids and their side chain rotamers, the suggested algorithm classifies amino acids and rotamers which possibly have collisions. Based on the divide and conquer technique, local side chain conformations are computed first, and then a global conformation is generated by combining them. With the exception of certain cases, experimental results show that the algorithm finds up to 327,680 valid side chain conformations from 128~1233 conformation candidates within three seconds.

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

2019 ◽  
Vol 16 (2) ◽  
pp. 159-172 ◽  
Author(s):  
Elaheh Kashani-Amin ◽  
Ozra Tabatabaei-Malazy ◽  
Amirhossein Sakhteman ◽  
Bagher Larijani ◽  
Azadeh Ebrahim-Habibi
Keyword(s):  
Systematic Review ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Web Of Science ◽  
Secondary Structure Prediction ◽  
Structural Information ◽  
Protein Secondary Structure ◽  
Structural Features ◽  
Prediction Tools ◽  
Insight Into

Background: 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. Objective: A systematic review was performed for a comprehensive access to recent (2013-2016) studies which used or recommended protein SSP tools. Methods: 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. Results: 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, while PHD was present in three fields. Conclusion: This study provides a comprehensive insight into the recent usage of SSP tools which could be helpful for selecting a proper tool.

Sign in / Sign up

Export Citation Format

Share Document