Literature DB >> 26201486

Untapped Potential of Disordered Proteins in Current Druggable Human Proteome.

Gang Hu, Zhonghua Wu, Kui Wang, Vladimir N Uversky1, Lukasz Kurgan.   

Abstract

Current efforts in design and characterization of drugs often rely on the structure of their protein targets. However, a large fraction of proteins lack unique 3-D structures and exist as highly dynamic structural ensembles. These intrinsically disordered proteins are involved in pathogenesis of various human diseases and are highly abundant in eukaryotes. Based on a comprehensive analysis of the current druggable human proteome covering 12 drug classes and 18 major classes of drug targets we show a significant bias toward high structural coverage and low abundance of intrinsic disorder. We review reasons for this bias including widespread use of the structural information in various stages of drug development and characterization process and difficulty with attaining structures for the intrinsically disordered proteins. We also discuss future of intrinsically disordered proteins as drug targets. Given the overall high disorder content of the human proteome and current bias of the druggable human proteome toward structural proteins, it is inevitable that disordered proteins will have to raise up on the list of prospective drug targets. The protein disorder-assisted drug design can draw from current rational drug design techniques and would also need novel approaches that no longer rely on a unique protein structure.

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Year:  2016        PMID: 26201486     DOI: 10.2174/1389450116666150722141119

Source DB:  PubMed          Journal:  Curr Drug Targets        ISSN: 1389-4501            Impact factor:   3.465


  19 in total

1.  Codon selection reduces GC content bias in nucleic acids encoding for intrinsically disordered proteins.

Authors:  Christopher J Oldfield; Zhenling Peng; Vladimir N Uversky; Lukasz Kurgan
Journal:  Cell Mol Life Sci       Date:  2019-06-07       Impact factor: 9.261

2.  Genes encoding intrinsic disorder in Eukaryota have high GC content.

Authors:  Zhenling Peng; Vladimir N Uversky; Lukasz Kurgan
Journal:  Intrinsically Disord Proteins       Date:  2016-12-15

Review 3.  Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions.

Authors:  Fanchi Meng; Vladimir N Uversky; Lukasz Kurgan
Journal:  Cell Mol Life Sci       Date:  2017-06-06       Impact factor: 9.261

Review 4.  Intrinsically Disordered Proteins: Critical Components of the Wetware.

Authors:  Prakash Kulkarni; Supriyo Bhattacharya; Srisairam Achuthan; Amita Behal; Mohit Kumar Jolly; Sourabh Kotnala; Atish Mohanty; Govindan Rangarajan; Ravi Salgia; Vladimir Uversky
Journal:  Chem Rev       Date:  2022-02-16       Impact factor: 72.087

5.  Prediction of protein disorder based on IUPred.

Authors:  Zsuzsanna Dosztányi
Journal:  Protein Sci       Date:  2017-11-16       Impact factor: 6.725

6.  DisProt: intrinsic protein disorder annotation in 2020.

Authors:  András Hatos; Borbála Hajdu-Soltész; Alexander M Monzon; Nicolas Palopoli; Lucía Álvarez; Burcu Aykac-Fas; Claudio Bassot; Guillermo I Benítez; Martina Bevilacqua; Anastasia Chasapi; Lucia Chemes; Norman E Davey; Radoslav Davidović; A Keith Dunker; Arne Elofsson; Julien Gobeill; Nicolás S González Foutel; Govindarajan Sudha; Mainak Guharoy; Tamas Horvath; Valentin Iglesias; Andrey V Kajava; Orsolya P Kovacs; John Lamb; Matteo Lambrughi; Tamas Lazar; Jeremy Y Leclercq; Emanuela Leonardi; Sandra Macedo-Ribeiro; Mauricio Macossay-Castillo; Emiliano Maiani; José A Manso; Cristina Marino-Buslje; Elizabeth Martínez-Pérez; Bálint Mészáros; Ivan Mičetić; Giovanni Minervini; Nikoletta Murvai; Marco Necci; Christos A Ouzounis; Mátyás Pajkos; Lisanna Paladin; Rita Pancsa; Elena Papaleo; Gustavo Parisi; Emilie Pasche; Pedro J Barbosa Pereira; Vasilis J Promponas; Jordi Pujols; Federica Quaglia; Patrick Ruch; Marco Salvatore; Eva Schad; Beata Szabo; Tamás Szaniszló; Stella Tamana; Agnes Tantos; Nevena Veljkovic; Salvador Ventura; Wim Vranken; Zsuzsanna Dosztányi; Peter Tompa; Silvio C E Tosatto; Damiano Piovesan
Journal:  Nucleic Acids Res       Date:  2020-01-08       Impact factor: 16.971

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.  Dihydroquinazolines enhance 20S proteasome activity and induce degradation of α-synuclein, an intrinsically disordered protein associated with neurodegeneration.

Authors:  Taylor J Fiolek; Christina L Magyar; Tyler J Wall; Steven B Davies; Molly V Campbell; Christopher J Savich; Jetze J Tepe; R Adam Mosey
Journal:  Bioorg Med Chem Lett       Date:  2021-01-27       Impact factor: 2.823

9.  flDPnn: Accurate intrinsic disorder prediction with putative propensities of disorder functions.

Authors:  Gang Hu; Akila Katuwawala; Kui Wang; Zhonghua Wu; Sina Ghadermarzi; Jianzhao Gao; Lukasz Kurgan
Journal:  Nat Commun       Date:  2021-07-21       Impact factor: 14.919

10.  Analysis of the dark proteome of Chandipura virus reveals maximum propensity for intrinsic disorder in phosphoprotein.

Authors:  Nishi R Sharma; Kundlik Gadhave; Prateek Kumar; Mohammad Saif; Md M Khan; Debi P Sarkar; Vladimir N Uversky; Rajanish Giri
Journal:  Sci Rep       Date:  2021-06-24       Impact factor: 4.379

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