Literature DB >> 24573480

Prediction of intrinsic disorder in proteins using MFDp2.

Marcin J Mizianty1, Vladimir Uversky, Lukasz Kurgan.   

Abstract

Intrinsically disordered proteins (IDPs) are either entirely disordered or contain disordered regions in their native state. IDPs were found to be abundant across all kingdoms of life, particularly in eukaryotes, and are implicated in numerous cellular processes. Experimental annotation of disorder lags behind the rapidly growing sizes of the protein databases and thus computational methods are used to close this gap and to investigate the disorder. MFDp2 is a novel webserver for accurate sequence-based prediction of protein disorder which also outputs well-described sequence-derived information that allows profiling the predicted disorder. We conveniently visualize sequence conservation, predicted secondary structure, relative solvent accessibility, and alignments to chains with annotated disorder. The webserver allows predictions for multiple proteins at the same time, includes help pages and tutorial, and the results can be downloaded as text-based (parsable) file. MFDp2 is freely available at http://biomine.ece.ualberta.ca/MFDp2/.

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Year:  2014        PMID: 24573480     DOI: 10.1007/978-1-4939-0366-5_11

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  18 in total

1.  How disordered is my protein and what is its disorder for? A guide through the "dark side" of the protein universe.

Authors:  Philippe Lieutaud; François Ferron; Alexey V Uversky; Lukasz Kurgan; Vladimir N Uversky; Sonia Longhi
Journal:  Intrinsically Disord Proteins       Date:  2016-12-21

2.  Accurately Predicting Disordered Regions of Proteins Using Rosetta ResidueDisorder Application.

Authors:  Stephanie S Kim; Justin T Seffernick; Steffen Lindert
Journal:  J Phys Chem B       Date:  2018-03-29       Impact factor: 2.991

3.  DISOselect: Disorder predictor selection at the protein level.

Authors:  Akila Katuwawala; Christopher J Oldfield; Lukasz Kurgan
Journal:  Protein Sci       Date:  2019-11-07       Impact factor: 6.725

4.  Measuring Intrinsic Disorder and Tracking Conformational Transitions Using Rosetta ResidueDisorder.

Authors:  Justin T Seffernick; He Ren; Stephanie S Kim; Steffen Lindert
Journal:  J Phys Chem B       Date:  2019-08-14       Impact factor: 2.991

5.  Predicting Protein Conformational Disorder and Disordered Binding Sites.

Authors:  Ketty C Tamburrini; Giulia Pesce; Juliet Nilsson; Frank Gondelaud; Andrey V Kajava; Jean-Guy Berrin; Sonia Longhi
Journal:  Methods Mol Biol       Date:  2022

Review 6.  The roles of intrinsic disorder-based liquid-liquid phase transitions in the "Dr. Jekyll-Mr. Hyde" behavior of proteins involved in amyotrophic lateral sclerosis and frontotemporal lobar degeneration.

Authors:  Vladimir N Uversky
Journal:  Autophagy       Date:  2017-12-17       Impact factor: 16.016

7.  Computational Prediction of Intrinsic Disorder in Protein Sequences with the disCoP Meta-predictor.

Authors:  Christopher J Oldfield; Xiao Fan; Chen Wang; A Keith Dunker; Lukasz Kurgan
Journal:  Methods Mol Biol       Date:  2020

8.  Association between intrinsic disorder and serine/threonine phosphorylation in Mycobacterium tuberculosis.

Authors:  Gajinder Pal Singh
Journal:  PeerJ       Date:  2015-01-08       Impact factor: 2.984

Review 9.  Fairy "tails": flexibility and function of intrinsically disordered extensions in the photosynthetic world.

Authors:  Gabriel Thieulin-Pardo; Luisana Avilan; Mila Kojadinovic; Brigitte Gontero
Journal:  Front Mol Biosci       Date:  2015-05-19

10.  A novel approach for predicting disordered regions in a protein sequence.

Authors:  Meijing Li; Seong Beom Cho; Keun Ho Ryu
Journal:  Osong Public Health Res Perspect       Date:  2014-07-01
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