Literature DB >> 23141694

Finding protein targets for small biologically relevant ligands across fold space using inverse ligand binding predictions.

Gang Hu1, Jianzhao Gao, Kui Wang, Marcin J Mizianty, Jishou Ruan, Lukasz Kurgan.   

Abstract

Inverse ligand binding prediction utilizes a few protein-ligand (drug) complexes to predict other secondary therapeutic and off-targets of a given drug molecule on a proteomic scale. We adapt two binding site predictors, FINDSITE and SMAP, to perform the inverse predictions and evaluate them on over 30 representative ligands. Use of just one complex allows the identification of other protein targets; the availability of additional complexes improves the results. Both methods offer comparable quality when using three complexes with diverse proteins. SMAP is better when fewer complexes are available, while FINDSITE provides stronger predictions for smaller ligands. We propose a consensus that combines (and outperforms) the two complementary approaches implemented by FINDSITE and SMAP. Most importantly, we demonstrate that these methods successfully find distant targets that belong to structurally different folds compared to the proteins in the input complexes.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23141694     DOI: 10.1016/j.str.2012.09.011

Source DB:  PubMed          Journal:  Structure        ISSN: 0969-2126            Impact factor:   5.006


  9 in total

1.  PDID: database of molecular-level putative protein-drug interactions in the structural human proteome.

Authors:  Chen Wang; Gang Hu; Kui Wang; Michal Brylinski; Lei Xie; Lukasz Kurgan
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2.  Large-scale binding ligand prediction by improved patch-based method Patch-Surfer2.0.

Authors:  Xiaolei Zhu; Yi Xiong; Daisuke Kihara
Journal:  Bioinformatics       Date:  2014-10-29       Impact factor: 6.937

3.  Databases and Tools to Investigate Protein-Metabolite Interactions.

Authors:  Leonardo Perez de Souza; Alisdair R Fernie
Journal:  Methods Mol Biol       Date:  2023

4.  Human structural proteome-wide characterization of Cyclosporine A targets.

Authors:  Gang Hu; Kui Wang; Jody Groenendyk; Khaled Barakat; Marcin J Mizianty; Jishou Ruan; Marek Michalak; Lukasz Kurgan
Journal:  Bioinformatics       Date:  2014-08-28       Impact factor: 6.937

5.  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

6.  Uncovering the Molecular Mechanism of Actions between Pharmaceuticals and Proteins on the AD Network.

Authors:  Shujuan Cao; Liang Yu; Jingyuan Mao; Quan Wang; Jishou Ruan
Journal:  PLoS One       Date:  2015-12-09       Impact factor: 3.240

7.  A Novel Method for Drug Screen to Regulate G Protein-Coupled Receptors in the Metabolic Network of Alzheimer's Disease.

Authors:  Yang Li; Wei Zheng; Wuyun Qiqige; Shujuan Cao; Jishou Ruan; Yanping Zhang
Journal:  Biomed Res Int       Date:  2018-02-20       Impact factor: 3.411

8.  Cyclosporine A binding to COX-2 reveals a novel signaling pathway that activates the IRE1α unfolded protein response sensor.

Authors:  Jody Groenendyk; Tautvydas Paskevicius; Hery Urra; Clement Viricel; Kui Wang; Khaled Barakat; Claudio Hetz; Lukasz Kurgan; Luis B Agellon; Marek Michalak
Journal:  Sci Rep       Date:  2018-11-12       Impact factor: 4.379

Review 9.  Machine learning approaches and databases for prediction of drug-target interaction: a survey paper.

Authors:  Maryam Bagherian; Elyas Sabeti; Kai Wang; Maureen A Sartor; Zaneta Nikolovska-Coleska; Kayvan Najarian
Journal:  Brief Bioinform       Date:  2021-01-18       Impact factor: 11.622

  9 in total

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