A quantitative analysis of kinase inhibitor selectivity

By Mazen W. Karaman, S. Herrgård, D. K. Treiber, P. Gallant, Corey E Atteridge, Brian T. Campbell, Katrina Chan, P. Ciceri, Mindy I. Davis, Philip T Edeen and 11 more. Nature Biotechnology, 2008

2,415 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/e81324c2ba10bb969ae67799ddd36e8a2a0a5646

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

In Molecular Biology

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

KinMap: a web-based tool for interactive navigation through human kinome data (2017, methodology): “…structures were obtained from the Protein Data Bank [11], the number of assay and compound values from ChEMBL [12], inhibition profiles from published panels [4, 13], and information related to kinase-disease associations from the Center for Therapeutic Target Validation (CTTV) platform [14].”
Cell cycle kinases as therapeutic targets for cancer (2009, background): “On the basis of advanced technologies that allow structure-based drug design and chemical genetics, and powerful screening platforms to investigate drug activity and target selectivit”
Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology (2013, methodology): “A comparison was conducted using the screening approach proposed in this study (blue bars; PDB IDs from Table S5) and bioassay results [30] (red bars).”
Patient-derived Models of Acquired Resistance Can Identify Effective Drug Combinations for Cancer (2014, background): “Two other drugs (dasatinib and KIN001-113) that potently inhibit Src family kinases (SFKs) (23, 24) were often hits in models in which AZD0530 was a hit (Fig.”
Src kinases as therapeutic targets for cancer (2009, background): “It is important to note that SFK inhibitors such as dasatinib and bosutinib might have significant off-target effects on kinases other than SFKs, leading to differences in efficacy and toxicity”
Decoding signalling networks by mass spectrometry-based proteomics (2010, methodology): “Quantitative MS combined with global phosphoproteomics is an attractive method for identifying targets of such inhibitors and for assessing their specificit”
An overview of the PubChem BioAssay resource (2009, background): “It also includes ligand–protein binding activity data generated by the targeted high-throughput structural biology experiments at the European Structural Genomics Consortium (11), literature-extracted bioactivity data from the BindingDB (12) project, the IUPHAR (13) project and the PDBBind (14) proj”
Eph receptors and ephrins in cancer: bidirectional signaling and beyond (2010, background): “gov/drugdictionary/?CdrID=315885">dasatinib , a multi-targeted kinase inhibitor already used in the treatment of chronic myelogenous leukaemia and under clinical evaluation to treat solid tumours, potently inhibits EPHA2 and other Eph receptors in addition to its primary targets Abl and Src family k”
Small molecule inhibition of the autophagy kinase ULK1 and identification of ULK1 substrates (2015, methodology): “SBI-0206965 Is a Highly Selective Kinase Inhibitor We next examined the specificity of 6965 using the DiscoveRx KINOMEscan panel of 456 purified human kinases in a competition-binding assay (Fabian et al., 2005; Karaman et al., 2008).”
Structure-based Systems Biology for Analyzing Off-target Binding (2011, background): “Although multiple target assays are available for well-studied gene families such as protein kinases [138], it may not be feasible to develop assays that are able to detect weak bindings across a large panel of proteins from different gene families, especially for those families not well…”