Literature DB >> 12211011

Information-theoretic dissection of pairwise contact potentials.

Melissa S Cline1, Kevin Karplus, Richard H Lathrop, Temple F Smith, Robert G Rogers, David Haussler.   

Abstract

Pairwise contact potentials have a long, successful history in protein structure prediction. They provide an easily-estimated representation of many attributes of protein structures, such as the hydrophobic effect. In order to improve on existing potentials, one should develop a clear understanding of precisely what information they convey. Here, using mutual information, we quantified the information in amino acid potentials, and the importance of hydropathy, charge, disulfide bonding, and burial. Sampling error in mutual information was controlled for by estimating how much information cannot be attributed to sampling bias. We found the information in amino acid contacts to be modest: 0.04 bits per contact. Of that, only 0.01 bits of information could not be attributed to hydropathy, charge, disulfide bonding, or burial. Copyright 2002 Wiley-Liss, Inc.

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Year:  2002        PMID: 12211011     DOI: 10.1002/prot.10198

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  13 in total

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Authors:  Björn Wallner; Arne Elofsson
Journal:  Protein Sci       Date:  2003-05       Impact factor: 6.725

2.  An information theoretic approach to macromolecular modeling: I. Sequence alignments.

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3.  Structure, function, and evolution of transient and obligate protein-protein interactions.

Authors:  Julian Mintseris; Zhiping Weng
Journal:  Proc Natl Acad Sci U S A       Date:  2005-07-25       Impact factor: 11.205

4.  A study of residue correlation within protein sequences and its application to sequence classification.

Authors:  Chris Hemmerich; Sun Kim
Journal:  EURASIP J Bioinform Syst Biol       Date:  2007

5.  Effective knowledge-based potentials.

Authors:  Evandro Ferrada; Francisco Melo
Journal:  Protein Sci       Date:  2009-07       Impact factor: 6.725

6.  Application of information theory to feature selection in protein docking.

Authors:  Olaf G Othersen; Arno G Stefani; Johannes B Huber; Heinrich Sticht
Journal:  J Mol Model       Date:  2011-07-12       Impact factor: 1.810

7.  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

8.  Using inferred residue contacts to distinguish between correct and incorrect protein models.

Authors:  Christopher S Miller; David Eisenberg
Journal:  Bioinformatics       Date:  2008-05-29       Impact factor: 6.937

9.  Random amino acid mutations and protein misfolding lead to Shannon limit in sequence-structure communication.

Authors:  Andreas Martin Lisewski
Journal:  PLoS One       Date:  2008-09-01       Impact factor: 3.240

10.  Automated alphabet reduction for protein datasets.

Authors:  Jaume Bacardit; Michael Stout; Jonathan D Hirst; Alfonso Valencia; Robert E Smith; Natalio Krasnogor
Journal:  BMC Bioinformatics       Date:  2009-01-06       Impact factor: 3.169

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