ArticleProceedings of the National Academy of Sciences of the United States of America2019
Defining a new nomenclature for the structures of active and inactive kinases.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 188 papers.
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188 citing papers in PubMed, 361 citations in OpenAlex.
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- Explainable AI reveals the allosteric blind spot in protein-ligand binding predictions.Cell reports. Physical science · 2026Article
- From Descriptor Learning to Binding Stability: An Explainable Machine Learning Pipeline for EGFR Double-Mutant Inhibitor Discovery.International journal of molecular sciences · 2026Article
- Structure-conditioned self-supervised learning of residue interaction constraints in protein kinases for variant interpretation.Bioinformatics (Oxford, England) · 2026Article
- Decoding the allosteric grammar of protein kinases: A dual-stream framework integrating protein language models and energy landscape frustration analysis.Protein science : a publication of the Protein Society · 2026Article
- Kinase inhibitors can change protonation or tautomeric state upon binding.bioRxiv : the preprint server for biology · 2026Article
- Riding toward Selectivity: Optimization of Covalent 7-Azaindole-Based BMX Kinase Inhibitors.Journal of medicinal chemistry · 2026Article
- An Experimentally Validated Structure-Based Virtual Screening Approach to Identify Nucleotide-Binding Protein Inhibitors as a New Source of Kinase Inhibitors.Pharmaceuticals (Basel, Switzerland) · 2026Article
- CAFE: A Co-folding Approach for Fragment Exploration of Allosteric and Cryptic Binding Sites.bioRxiv : the preprint server for biology · 2026Article
- Integrated Framework for Probing Multimodal Protein Foundation Models with Structure-Functional Interpretability Analysis in Detection of Allosteric Binding Sites.bioRxiv : the preprint server for biology · 2026Article
- KASSPer: kinase active site structure prediction using protein and ligand language models and its application to virtual screening.Bioinformatics (Oxford, England) · 2026Article
- Tyrosine kinases sample unique activation ensembles.bioRxiv : the preprint server for biology · 2026Article
- Structural and dynamic insights into the allosteric activation of p38α MAP kinase via specific docking interactions.Communications biology · 2026Article
- Contact-Network Phenotyping of the CDK Family Reveals Selective Distal C-Lobe Contact Redistribution by Modern CDK5 Inhibitors and a Quantitative Selectivity Landscape against CDK2 and CDK1.Journal of chemical information and modeling · 2026Article
- VsNsbench: evaluating AlphaFold3-embed induced-fit mechanism for enhanced virtual screening.Acta pharmacologica Sinica · 2026Article
- Predicting and Decoding Allosteric Binding Sites Using Protein Language Models and Structure-Based Machine Learning: An Energy Landscape-Guided Explainable AI Framework.Journal of chemical theory and computation · 2026Article
- MAPK Pathway Inhibition Reshapes Kinase Chemical Probe Reactivity Reflecting Cellular Activation States.ACS bio & med chem Au · 2026Article
- KinConfBench: A Curated Benchmark for Cofolding Models on Kinase Conformational States.bioRxiv : the preprint server for biology · 2026Article
128 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Targeting protein kinases is an important strategy for intervention in cancer. Inhibitors are directed at the active conformation or a variety of inactive conformations. While attempts have been made to classify these conformations, a structurally rigorous catalog of states has not been achieved. The kinase activation loop is crucial for catalysis and begins with the conserved DFGmotif. This motif is observed in two major classes of conformations, DFGin-a set of active and inactive conformations where the Phe residue is in contact with the C-helix of the N-terminal lobe-and DFGout-an inactive form where Phe occupies the ATP site exposing the C-helix pocket. We have developed a clustering of kinase conformations based on the location of the Phe side chain (DFGin, DFGout, and DFGinter or intermediate) and the backbone dihedral angles of the sequence X-D-F, where X is the residue before the DFGmotif, and the DFG-Phe side-chain rotamer, utilizing a density-based clustering algorithm. We have identified eight distinct conformations and labeled them based on the Ramachandran regions (A, alpha; B, beta; L, left) of the XDF motif and the Phe rotamer (minus, plus, trans). Our clustering divides the DFGin group into six clusters including BLAminus, which contains active structures, and two common inactive forms, BLBplus and ABAminus. DFGout structures are predominantly in the BBAminus conformation, which is essentially required for binding type II inhibitors. The inactive conformations have specific features that make them unable to bind ATP, magnesium, and/or substrates. Our structurally intuitive nomenclature will aid in understanding the conformational dynamics of kinases and structure-based development of kinase drugs.
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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.