Computational Modeling of Kinase Inhibitor Selectivity

Overview

Journal ACS Med Chem Lett

Publisher American Chemical Society

Specialty Chemistry

Date 2015 Dec 18

PMID 26677403

Citations 6

Authors

Govindan Subramanian

Manish Sud

Affiliations

Soon will be listed here.

Abstract

An exhaustive computational exercise on a comprehensive set of 15 therapeutic kinase inhibitors was undertaken to identify as to which compounds hit which kinase off-targets in the human kinome. Although the kinase selectivity propensity of each inhibitor against ∼480 kinase targets is predicted, we compared our predictions to ∼280 kinase targets for which consistent experimental data are available and demonstrate an overall average prediction accuracy and specificity of ∼90%. A comparison of the predictions was extended to an additional ∼60 kinases for sorafenib and sunitinib as new experimental data were reported recently with similar prediction accuracy. The successful predictive capabilities allowed us to propose predictions on the remaining kinome targets in an effort to repurpose known kinase inhibitors to these new kinase targets that could hold therapeutic potential.

Citing Articles

Computational analysis of kinase inhibitor selectivity using structural knowledge.

Lo Y, Liu T, Morrissey K, Kakiuchi-Kiyota S, Johnson A, Broccatelli F Bioinformatics. 2018; 35(2):235-242.

PMID: 29985971 PMC: 6330000. DOI: 10.1093/bioinformatics/bty582.

Quantitative Structure-Activity Relationship Modeling of Kinase Selectivity Profiles.

Kothiwale S, Borza C, Pozzi A, Meiler J Molecules. 2017; 22(9).

PMID: 28925954 PMC: 6151389. DOI: 10.3390/molecules22091576.

De novo design of protein kinase inhibitors by in silico identification of hinge region-binding fragments.

Urich R, Wishart G, Kiczun M, Richters A, Tidten-Luksch N, Rauh D ACS Chem Biol. 2013; 8(5):1044-52.

PMID: 23534475 PMC: 3833278. DOI: 10.1021/cb300729y.

Biotinylated phosphoproteins from kinase-catalyzed biotinylation are stable to phosphatases: implications for phosphoproteomics.

Senevirathne C, Pflum M Chembiochem. 2013; 14(3):381-7.

PMID: 23335220 PMC: 4524292. DOI: 10.1002/cbic.201200626.

Extraction and validation of substructure profiles for enriching compound libraries.

Yeo W, Go M, Nilar S J Comput Aided Mol Des. 2012; 26(10):1127-41.

PMID: 22983491 DOI: 10.1007/s10822-012-9604-8.

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