The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Defining a new nomenclature for the structures of active and inactive kinases
Open accessPublished version of a preprint
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures








Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“However, a protein can exist in one conformation in its “inactive” state and another in its “active” state.53–56”
From AlphaFold 2: Why It Works and Its Implications for Understanding the Relationships of Protein Sequence, Structure, and Function (2021) · cites this paper as [54]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302
PHENIX : a comprehensive Python-based system for macromolecular structure solution
Adams, P. D., Afonine, P. V., Bunkóczi, G., Chen, V. B., Davis, I. W., Echols, N., Headd, J. J., Hung, L.-W., Kapral, G. J., Grosse-Kunstleve, R. W., et al. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909052925 · Cited by 23,716
(1996) · Cited by 20,179
The protein kinase complement of the human genome
Manning, G., Whyte, D. B., Martinez, R., Hunter, T., & Sudarsanam, S. (2002) · Science · doi:10.1126/science.1075762 · Cited by 8,145
PHENIX: a comprehensive Python-based system for macromolecular structure solution
Adams, P. D., Afonine, P. V., Bunkòczi, G., Chen, V. B., Davis, I., Echols, N., Headd, J. J., Hung, L., Kapral, G. J., Grosse‐Kunstleve, R. W., et al. (2012) · International Tables for Crystallography · doi:10.1107/97809553602060000865 · Cited by 7,334
Mardia, K. V., & Jupp, P. E. (1999) · Wiley series in probability and statistics · doi:10.1002/9780470316979 · Cited by 3,277
Targeting cancer with small molecule kinase inhibitors
Zhang, J., Yang, P. L., & Gray, N. S. (2008) · Nature reviews. Cancer · doi:10.1038/nrc2559 · Cited by 2,648
Satisfying Hydrogen Bonding Potential in Proteins
McDonald, I. K., & Thornton, J. M. (1994) · Journal of Molecular Biology · doi:10.1006/jmbi.1994.1334 · Cited by 2,136
The Conformational Plasticity of Protein Kinases
Huse, M., & Kuriyan, J. (2002) · Cell · doi:10.1016/s0092-8674(02)00741-9 · Cited by 1,760
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining
Simoudis, E., Han, J., & Fayyad, U. M. (1996) · Cited by 1,121
Cited by
Sorted by citations
Items 301–367 of 367
Gu, X., Aranganathan, A., & Tiwary, P. (2024) · eLife · doi:10.7554/elife.99702.1.sa1
Gu, X., Aranganathan, A., & Tiwary, P. (2024) · eLife · doi:10.7554/elife.99702.1.sa0
Delineating Drug Class and Target-Specific Adverse Events of Kinase InhibitorsPreprint
Schweickart, A., Somani, J., Theisen, R., Sahni, N., Cichońska, A., & Rahman, R. (2024) · medRxiv · doi:10.1101/2024.08.07.24311573
Gu, X., Aranganathan, A., & Tiwary, P. (2024) · eLife · doi:10.7554/elife.99702.2.sa0
Gu, X., Aranganathan, A., & Tiwary, P. (2024) · eLife · doi:10.7554/elife.99702.2.sa2
Gu, X., Aranganathan, A., & Tiwary, P. (2024) · eLife · doi:10.7554/elife.99702.2.sa1
Gu, X., Aranganathan, A., & Tiwary, P. (2024) · eLife · doi:10.7554/elife.99702.2.sa3
Electrical Forces Improve Memory in Old Age
McCaig, C. (2025) · Reviews of physiology, biochemistry and pharmacology · doi:10.1007/978-3-031-68827-0_21
Behn, J., Deepak, R. N. V. K., Hu, J., & Fan, H. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5166681
Activation segment of protein kinases: classification based on multidimensional analysis
Ahiri, A., & Aboulmouhajir, A. (2025) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2025.2475399
Zheng, L., Xu, C., Zhang, S., Zhang, N., Zhu, Y., Lu, M., Chen, Y., Zhu, Y., & Liu, H. (2025) · ChemistrySelect · doi:10.1002/slct.202403430
Stable H-bond networks are crucial for selective CLK1 inhibition: a computational perspective
Huang, Y., Hu, B., Liu, H., Wang, J., & Duan, N. (2025) · Frontiers in Chemistry · doi:10.3389/fchem.2025.1582515
Chaudhuri, N. R., & Dastidar, S. G. (2025) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.5c00529
Investigation of membrane-associated functions of MLKL in programmed cell death
Friedrich, J. S. (2025) · Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) · doi:10.21248/gups.91753
JAK2 Inhibitors as the Elixir for Humans: A Truth or Myth (A Review)
Achutha, A. S., Pushpa, V. L., Divya, V., Sarithamol, S., Surendran, S., Manoj, K. B., Sunitha, V. R., & Jeneena, K. B. (2025) · Cell and Tissue Biology · doi:10.1134/s1990519x25600097
Geometry-constrained prediction of catalytically competent kinase domains across the human kinome
Wang, Y., Hu, Q., & Huang, J. (2026) · Cell Reports Physical Science · doi:10.1016/j.xcrp.2026.103412
Uncovering the Molecular Basis of Kinase Activity and Substrate Recognition With Phospho-PCAPreprint
Yu, C., Pao, E., & Valen, D. V. (2025) · SSRN Electronic Journal · doi:10.1101/2025.11.07.687244
Characterization of Mast2 kinase defines structural features, regulation, and substrates
Lemke, M. C., Chen, M., Jang, S. S., Rader, M., Avala, N. R., Bauchle, C. J., Pluguez, R., Miller, C. J., Butler, J. D., Hargett, S. R., et al. (2025) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2025.110922
QM / MM Free Energy Calculations of IRE1 Reveal a Unique Protonation State of the Catalytic Lys599
Carlesso, A., Conflitti, P., Mahdizadeh, S. J., Deganutti, G., Eriksson, L. A., & Limongelli, V. (2025) · Journal of Computational Chemistry · doi:10.1002/jcc.70288
Structural pattern recognition in retrosynthetic analysis
Trombini, C. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-36542-3.00005-0
Deciphering covalent kinase inhibitor binding landscape through structural kinome profiling
Zhao, Z., & Bourne, P. E. (2026) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2026.118872 · Cited by 2
Zaky, Y. A., Rashad, M. W., Zaater, M. A., & Kerdawy, A. M. E. (2024) · Figshare · doi:10.6084/m9.figshare.26660353
Pal, S., & Mohanty, D. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.01.691623
Jarvis, A. F., Bhat, M. Y., Maujean, T., Abreu, A. L., Toy, K., Burslem, G. M., & Brady, D. C. (2026) · ACS Bio & Med Chem Au · doi:10.1021/acsbiomedchemau.5c00231
Wan, J., Xiong, X., Geng, Z., Yuan, B., Ma, Y., Zhao, Y., Wong, Z. Y. D., Kang, X., Fan, R., Min, D., et al. (2026) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.5c03145
Gkoutzivelaki, A., Triantopoulou, S.-I., Chiniadis, L., Komiotis, A., Triantis, C., Komiotis, D., Papakyriakou, A., Pratsinis, H., & Manta, S. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27041738
Novel universal domain-centric method for protein classification
Fadaei, S., Krebs, F. S., & Zoete, V. (2026) · Scientific Reports · doi:10.1038/s41598-026-41142-w
Gatlin, W., Ludwick, M., Turano, L., Foley, B., Riedlová, K., Škrhák, V., Novotný, M., Hoksza, D., & Verkhivker, G. M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.21.713412
Etude de la modulation de voies de mort cellulaire programmée par des molécules marines
Nguyen, T.-N.-D. (2019) · theses.fr (ABES) · doi:10.70675/19e7bbbbz7578z4637zad5czb478c3e1222a
Pescheteau, C. (2021) · theses.fr (ABES) · doi:10.70675/f258c770z5a4bz407bz9533z56a9b2b6a0f8
Control, use and misuse of cellular signalling networks
Juyoux, P. (2021) · theses.fr (ABES) · doi:10.70675/59616c42zeda8z4a8dza27fze9e6c6d83982
Characterization of protein-protein interactions mediated by the IKK complex
Moro, S. (2022) · theses.fr (ABES) · doi:10.70675/340a028ezd105z4e02z83b4z27f3cd5ea5eb
Etude des résistances aux inhibiteurs d’ALK dans les LAGC ALK+
Vasseur, D. (2023) · theses.fr (ABES) · doi:10.70675/f61106c4z7744z4662z8df7z4c6f885a65cf
Machine learning to understand and engineer the structural kinome
Reveguk, I. (2023) · theses.fr (ABES) · doi:10.70675/bac5b968z5ac5z406czaa3az3ea700df1ec8
Yang, X., Zhang, Y., Lv, Q., Liu, Y., Jiang, C., & Zhang, X. (2026) · European journal of medical research · doi:10.1186/s40001-026-04500-y
Fadaei, S., Krebs, F. S., & Zoete, V. (2026) · Bioinformatics · doi:10.1093/bioinformatics/btag487
Nael, M. A., Alakonda, L. M., & Elokely, K. M. (2026) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6c00886
Chemical Space Exploration of a Database of Covalent Binders in the PDB
Velasco-Saavedra, M. A., Mar-Antonio, E., Colorado-Pablo, L. F., Santos‐Contreras, M. Á., Flores-León, C. D., Carreón-Escalante, M., Sánchez-Maza, S., Ambrosio-Huerta, A., Goode‐Romero, G., Medina‐Franco, J. L., et al. (2026) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6c00846 · Cited by 1
Zhang, Y., Pei, C.-J., Luo, Z., Zhu, Z., Wu, J., & Wang, Z. (2026) · Communications Biology · doi:10.1038/s42003-026-10502-7
Jang, W., & Shin, W. (2026) · Bioinformatics · doi:10.1093/bioinformatics/btag481
Transfer seeding reveals divergent activation ensembles across tyrosine kinasesPreprint
Zhu, Y., Degiacomi, M. T., Mey, A. S. J. S., & Singh, S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.26.734786
Janus kinase 2 activation loop as a regulator of catalysis and trans-activation
Miao, Y., Mykuliak, V. V., Hubbard, S. R., Silvennoinen, O., Hytönen, V. P., & Haikarainen, T. (2026) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2026.153276
Bazarova, A., & Verkhivker, G. M. (2026) · Journal of Chemical Information and Modeling · doi:10.64898/2026.07.02.736203
Riding toward Selectivity: Optimization of Covalent 7-Azaindole-Based BMX Kinase Inhibitors
Liang, X. J., Albertini, C., Kronenberger, T., Shevchenko, E., Rasch, A., Berger, B., Schwalm, M. P., Berger, L. M., Krämer, A., Serafim, R. A. M., et al. (2026) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.6c01366
Explainable AI reveals the allosteric blind spot in protein-ligand binding predictions
Parikh, V., Foley, B., Gatlin, W., Ludwick, M., Turano, L., & Verkhivker, G. M. (2026) · Cell Reports Physical Science · doi:10.1016/j.xcrp.2026.103448 · Cited by 1
Enzymes, their Catalytic Properties, and Enzymes as Drug Targets
Minden, A. (2026) · Springer eBooks · doi:10.1007/978-3-032-20529-2_5
Dar, B. A., Dar, A. H., & Dar, S. A. (2026) · Journal of Allergy & Infectious Diseases · doi:10.46439/allergy.7.057
Novak, J. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27167122
Zhang, B., Xi, Q.-F., Ying, Y.-M., Zhao, D.-R., Yang, L.-Q., & Sang, P. (2026) · RSC Advances · doi:10.1039/d6ra04733e
Welsh, C. L., & Madan, L. K. (2026) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.70169
Anyanwu, V. O., Spiriti, J. M., & Wong, C. F. (2026) · ACS Omega · doi:10.1021/acsomega.6c08155
Drug Repositioning in Kinase Inhibitor Discovery for Cancer Therapy
Sun, Q., Pang, X., & Liu, Y. (2026) · Pharmaceutics · doi:10.3390/pharmaceutics18101240
Ruiz‐Campos, P., Dongo, R. J. Z., Quiñones-Inga, J., & Hurtado-Roca, Y. (2026) · Journal of Molecular Graphics and Modelling · doi:10.1016/j.jmgm.2026.109608
Integrative computational simulations uncover the conformational activation pathway of AKT1 kinase
Liu, C., Zhang, Y., Xiang, Y., Chen, S., Zhang, C., Chai, Z., & Bai, D. (2026) · Physical Chemistry Chemical Physics · doi:10.1039/d6cp02600a
Kinase Inhibitors can Change Protonation or Tautomeric State upon Binding
Ranepura, G., Chowdhury, S. I., Rosenzweig, E., Rustenburg, A. S., de Castro, R. L.-R., Mao, J., Chodera, J. D., Singh, S., & Gunner, M. R. (2026) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6c02792
Defining the conformational landscape of glycogen synthase kinase 3 beta (GSK3β)
Gurtu, A., & Laezza, F. (2026) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s2059798326010533
BindingDB Entry 50016590: Identification of Inhibitors of the
BindingDB (2023) · UC San Diego · doi:10.7270/q2hx1hnp
BindingDB Entry 50020040: Development of MPS1 Inhibitors: Recent Advances and Perspectives.
BindingDB (2024) · UC San Diego · doi:10.7270/q2fr021h
BindingDB Entry 50017724: Design and development of photoswitchable DFG-Out RET kinase inhibitors.
BindingDB (2023) · UC San Diego · doi:10.7270/q2rj4pjx
Metadata
- Authors
- Modi, V., & Dunbrack, R. L.
- Affiliations
- Fox Chase Cancer Center (US)
- Corresponding author
- Dunbrack, Roland L.
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2019-03-13
- Volume
- 116
- Issue
- 14
- Pages
- 6818-6827
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC6452665
- OpenAlex
- W2922340164
- Cited by
- 367
- References
- 38
- Citations by year
- 2026: 54 · 2025: 44 · 2024: 65 · 2023: 68 · 2022: 48 · 2021: 48 · 2020: 33 · 2019: 6
- FWCI
- 11.16
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- HHS | NIH | National Institute of General Medical Sciences (R35 GM122517)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Kinase Regulation and GTPase Signaling
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Keywords
- protein kinases, DFG motif, kinase activation loop, kinase inhibitors, backbone dihedral angles, density-based clustering, structure-based drug design, type II kinase inhibitors
- MeSH terms
- Algorithms, Models, Molecular, Terminology as Topic, Protein Kinases, Substrate Specificity, Protein Structure, Secondary, Catalytic Domain, Protein Kinase Inhibitors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review