Literature DB >> 23680395

Prediction of contacts from correlated sequence substitutions.

William R Taylor1, Russell S Hamilton, Michael I Sadowski.   

Abstract

Recent work has led to a substantial improvement in the accuracy of predictions of contacts between amino acids using evolutionary information derived from multiple sequence alignments. Where large numbers of diverse sequence relatives are available and can be aligned to the sequence of a protein of unknown structure it is now possible to generate high-resolution models without recourse to the structure of a template. In this review we describe these exciting new techniques and critically assess the state-of-the-art in contact prediction in the light of these. While concentrating on methods, we also discuss applications to protein and RNA structure prediction as well as potential future developments.
Copyright © 2013 Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 23680395     DOI: 10.1016/j.sbi.2013.04.001

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   6.809


  26 in total

Review 1.  Genetically modified proteins: functional improvement and chimeragenesis.

Authors:  Larissa Balabanova; Vasily Golotin; Anna Podvolotskaya; Valery Rasskazov
Journal:  Bioengineered       Date:  2015-07-25       Impact factor: 3.269

Review 2.  A tale of two machines: a review of the BLAST meeting, Tucson, AZ, 20-24 January 2013.

Authors:  Christine Josenhans; Kirsten Jung; Christopher V Rao; Alan J Wolfe
Journal:  Mol Microbiol       Date:  2013-10-31       Impact factor: 3.501

3.  BCov: a method for predicting β-sheet topology using sparse inverse covariance estimation and integer programming.

Authors:  Castrense Savojardo; Piero Fariselli; Pier Luigi Martelli; Rita Casadio
Journal:  Bioinformatics       Date:  2013-09-23       Impact factor: 6.937

4.  Structure of the Bacterial Cytoskeleton Protein Bactofilin by NMR Chemical Shifts and Sequence Variation.

Authors:  Maher M Kassem; Yong Wang; Wouter Boomsma; Kresten Lindorff-Larsen
Journal:  Biophys J       Date:  2016-06-07       Impact factor: 4.033

5.  High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features.

Authors:  David T Jones; Shaun M Kandathil
Journal:  Bioinformatics       Date:  2018-10-01       Impact factor: 6.937

6.  Covariation Is a Poor Measure of Molecular Coevolution.

Authors:  David Talavera; Simon C Lovell; Simon Whelan
Journal:  Mol Biol Evol       Date:  2015-05-04       Impact factor: 16.240

7.  From principal component to direct coupling analysis of coevolution in proteins: low-eigenvalue modes are needed for structure prediction.

Authors:  Simona Cocco; Remi Monasson; Martin Weigt
Journal:  PLoS Comput Biol       Date:  2013-08-22       Impact factor: 4.475

8.  Prediction of protein structural features from sequence data based on Shannon entropy and Kolmogorov complexity.

Authors:  Robert Paul Bywater
Journal:  PLoS One       Date:  2015-04-09       Impact factor: 3.240

9.  The Phylogenetic Signature Underlying ATP Synthase c-Ring Compliance.

Authors:  Alessandro Pandini; Jens Kleinjung; Willie R Taylor; Wolfgang Junge; Shahid Khan
Journal:  Biophys J       Date:  2015-09-01       Impact factor: 4.033

10.  Sequence specificity between interacting and non-interacting homologs identifies interface residues--a homodimer and monomer use case.

Authors:  Qingzhen Hou; Bas E Dutilh; Martijn A Huynen; Jaap Heringa; K Anton Feenstra
Journal:  BMC Bioinformatics       Date:  2015-10-08       Impact factor: 3.169

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