Literature DB >> 24413183

A survey on prediction of specificity-determining sites in proteins.

Abhijit Chakraborty, Saikat Chakrabarti.   

Abstract

Specificity-determining sites (SDS) are the key positions of a protein family that show a specific conservation of amino acids, related to the subfamily members of that family. SDS play crucial role in developing functional variation within the protein family during the course of evolution. Thus, it is important to identify SDS to understand the evolutionary process of diversification of biological functions within a protein family. A wide range of computational tools have been designed to detect such SDS. In this review, we intend to examine the concept of SDS in more details along with the advancements and drawbacks of different computational approaches designed towards successful prediction of SDS. Further, we discussed the algorithms behind the computational approaches developed till date and provide an exhaustive comparison of performance of each method. We also introduce a new ensemble approach, SubSite as another tool to predict SDS through a user-friendly webserver available at www.hpppi.iicb.res.in/subsite.
© The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  functional specificity; protein evolution; protein subfamily; specificity-determining sites

Mesh:

Year:  2014        PMID: 24413183     DOI: 10.1093/bib/bbt092

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  23 in total

1.  The choice of sequence homologs included in multiple sequence alignments has a dramatic impact on evolutionary conservation analysis.

Authors:  Nelson Gil; Andras Fiser
Journal:  Bioinformatics       Date:  2019-01-01       Impact factor: 6.937

Review 2.  Using Evolution to Guide Protein Engineering: The Devil IS in the Details.

Authors:  Liskin Swint-Kruse
Journal:  Biophys J       Date:  2016-07-12       Impact factor: 4.033

3.  TranCEP: Predicting the substrate class of transmembrane transport proteins using compositional, evolutionary, and positional information.

Authors:  Munira Alballa; Faizah Aplop; Gregory Butler
Journal:  PLoS One       Date:  2020-01-14       Impact factor: 3.240

4.  In silico identification and experimental validation of amino acid motifs required for the Rho-of-plants GTPase-mediated activation of receptor-like cytoplasmic kinases.

Authors:  Dézi Bianka Lajkó; Ildikó Valkai; Mónika Domoki; Dalma Ménesi; Györgyi Ferenc; Ferhan Ayaydin; Attila Fehér
Journal:  Plant Cell Rep       Date:  2018-01-16       Impact factor: 4.570

5.  Functional classification of CATH superfamilies: a domain-based approach for protein function annotation.

Authors:  Sayoni Das; David Lee; Ian Sillitoe; Natalie L Dawson; Jonathan G Lees; Christine A Orengo
Journal:  Bioinformatics       Date:  2015-07-02       Impact factor: 6.937

6.  Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations.

Authors:  Andrew F Neuwald; Stephen F Altschul
Journal:  PLoS Comput Biol       Date:  2016-12-21       Impact factor: 4.475

Review 7.  Diversity in protein domain superfamilies.

Authors:  Sayoni Das; Natalie L Dawson; Christine A Orengo
Journal:  Curr Opin Genet Dev       Date:  2015-11-03       Impact factor: 5.578

8.  ALVIS: interactive non-aggregative visualization and explorative analysis of multiple sequence alignments.

Authors:  Roland F Schwarz; Asif U Tamuri; Marek Kultys; James King; James Godwin; Ana M Florescu; Jörg Schultz; Nick Goldman
Journal:  Nucleic Acids Res       Date:  2016-01-26       Impact factor: 16.971

9.  A Bioinformatics Analysis Reveals a Group of MocR Bacterial Transcriptional Regulators Linked to a Family of Genes Coding for Membrane Proteins.

Authors:  Teresa Milano; Sebastiana Angelaccio; Angela Tramonti; Martino Luigi Di Salvo; Roberto Contestabile; Stefano Pascarella
Journal:  Biochem Res Int       Date:  2016-06-30

10.  Inferring joint sequence-structural determinants of protein functional specificity.

Authors:  Andrew F Neuwald; L Aravind; Stephen F Altschul
Journal:  Elife       Date:  2018-01-16       Impact factor: 8.140

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