ArticleACS omega2018
Exploring Selectivity of Multikinase Inhibitors across the Human Kinome.
Article in ACS omega, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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Who cites it
12 citing papers in PubMed.
- Kinase-Targeted Therapies for Glioblastoma.International journal of molecular sciences · 2025Review
- Data sets of human and mouse protein kinase inhibitors with curated activity data including covalent inhibitors.Future science OA · 2023Article
- Adverse effects of tyrosine kinase inhibitors in cancer therapy: pathophysiology, mechanisms and clinical management.Signal transduction and targeted therapy · 2023Review
- Target-specific compound selectivity for multi-target drug discovery and repurposing.Frontiers in pharmacology · 2022Article
- Kinase inhibitor data set for systematic analysis of representative kinases across the human kinome.Data in brief · 2020Article
- Assessing the information content of structural and protein-ligand interaction representations for the classification of kinase inhibitor binding modes via machine learning and active learning.Journal of cheminformatics · 2020Article
- Data structures for computational compound promiscuity analysis and exemplary applications to inhibitors of the human kinome.Journal of computer-aided molecular design · 2020Article
- Structural analysis of fungal pathogenicity-related casein kinase α subunit, Cka1, in the human fungal pathogen Cryptococcus neoformans.Scientific reports · 2019Article
- Data structures for compound promiscuity analysis: promiscuity cliffs, pathways and promiscuity hubs formed by inhibitors of the human kinome.Future science OA · 2019Article
- Systematic computational identification of promiscuity cliff pathways formed by inhibitors of the human kinome.Journal of computer-aided molecular design · 2019Article
- Data-Driven Exploration of Selectivity and Off-Target Activities of Designated Chemical Probes.Molecules (Basel, Switzerland) · 2018Article
- Reconciling Selectivity Trends from a Comprehensive Kinase Inhibitor Profiling Campaign with Known Activity Data.ACS omega · 2018Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Selectivity of kinase inhibitors, or the lack thereof, continues to be an intensely debated topic in drug discovery research. Especially, type I inhibitors, which represent most of the currently available kinase inhibitors, are often thought to lack selectivity because they target the largely conserved adenosine triphosphate-binding site in kinases. Herein, we present a large-scale analysis of potential selectivity among multikinase inhibitors, covering 141 human kinases and more than 10 000 qualifying compounds. By design, the analysis was focused on type I inhibitors and carried out at the level of systematically generated kinase pairs sharing inhibitors. Kinase pair category- and compound-based selectivity profiles identified in part highly selective inhibitors for many kinases. Sets of inhibitors associated with kinase pairs frequently contained nonselective as well as increasingly selective compounds. Selectivity of inhibitors did not result from gatekeeper residues settings or phylogenetic distance of kinases. Rather, it was most likely attributable to subtle differences between binding regions in kinases. Taken together, the results of our study reveal that many multikinase inhibitors are more selective than one might assume.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.