Literature DB >> 18022559

Inverse in silico screening for identification of kinase inhibitor targets.

Stefan Zahler1, Simon Tietze, Frank Totzke, Michael Kubbutat, Laurent Meijer, Angelika M Vollmar, Joannis Apostolakis.   

Abstract

Protein kinases are clinically relevant, attractive drug targets for cancer. One major problem with kinase inhibitors is broad promiscuity, causing off-target actions and side effects. In silico prediction of targets of a compound would immensely facilitate and accelerate drug development. Using a virtual "inverse" screening approach, where single compounds are docked into protein structures from a database, we identify among known targets of indirubin derivatives phosphoinositide-dependent kinase 1 (PDK1) as a target of one derivative (6BIO) in particular. This prediction is functionally supported by an in vitro kinase assay, inhibition of intracellular phosphorylation of PDK1-substrates, and inhibition of endothelial cell migration, which highly depends on PDK1. Virtual inverse screening combined with biological tests, thus, is proposed as a valuable tool for the drug discovery process and re-examination of already established kinase inhibitors.

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Year:  2007        PMID: 18022559     DOI: 10.1016/j.chembiol.2007.10.010

Source DB:  PubMed          Journal:  Chem Biol        ISSN: 1074-5521


  24 in total

1.  Virtual target screening: validation using kinase inhibitors.

Authors:  Daniel N Santiago; Yuri Pevzner; Ashley A Durand; MinhPhuong Tran; Rachel R Scheerer; Kenyon Daniel; Shen-Shu Sung; H Lee Woodcock; Wayne C Guida; Wesley H Brooks
Journal:  J Chem Inf Model       Date:  2012-07-23       Impact factor: 4.956

2.  Computational Modeling of Kinase Inhibitor Selectivity.

Authors:  Govindan Subramanian; Manish Sud
Journal:  ACS Med Chem Lett       Date:  2010-07-28       Impact factor: 4.345

Review 3.  Exploiting drug-disease relationships for computational drug repositioning.

Authors:  Joel T Dudley; Tarangini Deshpande; Atul J Butte
Journal:  Brief Bioinform       Date:  2011-06-20       Impact factor: 11.622

4.  An inverse docking approach for identifying new potential anti-cancer targets.

Authors:  Sam Z Grinter; Yayun Liang; Sheng-You Huang; Salman M Hyder; Xiaoqin Zou
Journal:  J Mol Graph Model       Date:  2011-01-19       Impact factor: 2.518

5.  Computational analysis of kinase inhibitor selectivity using structural knowledge.

Authors:  Yu-Chen Lo; Tianyun Liu; Kari M Morrissey; Satoko Kakiuchi-Kiyota; Adam R Johnson; Fabio Broccatelli; Yu Zhong; Amita Joshi; Russ B Altman
Journal:  Bioinformatics       Date:  2019-01-15       Impact factor: 6.937

6.  Improving inverse docking target identification with Z-score selection.

Authors:  Stephanie S Kim; Melanie L Aprahamian; Steffen Lindert
Journal:  Chem Biol Drug Des       Date:  2019-01-02       Impact factor: 2.817

7.  RepurposeVS: A Drug Repurposing-Focused Computational Method for Accurate Drug-Target Signature Predictions.

Authors:  Naiem T Issa; Oakland J Peters; Stephen W Byers; Sivanesan Dakshanamurthy
Journal:  Comb Chem High Throughput Screen       Date:  2015       Impact factor: 1.339

8.  Rapid Identification of Inhibitors and Prediction of Ligand Selectivity for Multiple Proteins: Application to Protein Kinases.

Authors:  Zhiwei Ma; Sheng-You Huang; Fei Cheng; Xiaoqin Zou
Journal:  J Phys Chem B       Date:  2021-03-02       Impact factor: 2.991

9.  Activation of Wnt/beta-catenin signaling increases insulin sensitivity through a reciprocal regulation of Wnt10b and SREBP-1c in skeletal muscle cells.

Authors:  Mounira Abiola; Maryline Favier; Eleni Christodoulou-Vafeiadou; Anne-Lise Pichard; Isabelle Martelly; Isabelle Guillet-Deniau
Journal:  PLoS One       Date:  2009-12-30       Impact factor: 3.240

10.  Exploring the ligand-protein networks in traditional chinese medicine: current databases, methods, and applications.

Authors:  Mingzhu Zhao; Qiang Zhou; Wanghao Ma; Dong-Qing Wei
Journal:  Evid Based Complement Alternat Med       Date:  2013-06-02       Impact factor: 2.629

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