Literature DB >> 18203772

Predicting disulfide bond connectivity in proteins by correlated mutations analysis.

Rotem Rubinstein1, Andras Fiser.   

Abstract

MOTIVATION: Prediction of disulfide bond connectivity facilitates structural and functional annotation of proteins. Previous studies suggest that cysteines of a disulfide bond mutate in a correlated manner.
RESULTS: We developed a method that analyzes correlated mutation patterns in multiple sequence alignments in order to predict disulfide bond connectivity. Proteins with known experimental structures and varying numbers of disulfide bonds, and that spanned various evolutionary distances, were aligned. We observed frequent variation of disulfide bond connectivity within members of the same protein families, and it was also observed that in 99% of the cases, cysteine pairs forming non-conserved disulfide bonds mutated in concert. Our data support the notion that substitution of a cysteine in a disulfide bond prompts the substitution of its cysteine partner and that oxidized cysteines appear in pairs. The method we developed predicts disulfide bond connectivity patterns with accuracies of 73, 69 and 61% for proteins with two, three and four disulfide bonds, respectively.

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Year:  2008        PMID: 18203772     DOI: 10.1093/bioinformatics/btm637

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  18 in total

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4.  Molecular Evolutionary Analysis of Nematode Zona Pellucida (ZP) Modules Reveals Disulfide-Bond Reshuffling and Standalone ZP-C Domains.

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5.  Identifying functionally informative evolutionary sequence profiles.

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Journal:  Bioinformatics       Date:  2018-04-15       Impact factor: 6.937

6.  DBCP: a web server for disulfide bonding connectivity pattern prediction without the prior knowledge of the bonding state of cysteines.

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7.  Towards accurate residue-residue hydrophobic contact prediction for alpha helical proteins via integer linear optimization.

Authors:  R Rajgaria; S R McAllister; C A Floudas
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8.  Assessing the accuracy of contact predictions in CASP13.

Authors:  Rojan Shrestha; Eduardo Fajardo; Nelson Gil; Krzysztof Fidelis; Andriy Kryshtafovych; Bohdan Monastyrskyy; Andras Fiser
Journal:  Proteins       Date:  2019-10-24

9.  Unexpected diversity in Shisa-like proteins suggests the importance of their roles as transmembrane adaptors.

Authors:  Jimin Pei; Nick V Grishin
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10.  CD-HIT: accelerated for clustering the next-generation sequencing data.

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Journal:  Bioinformatics       Date:  2012-10-11       Impact factor: 6.937

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