Defining a new nomenclature for the structures of active and inactive kinases
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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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A protein can exist in one conformation in its inactive state and another in its active state.
“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]
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- 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
- Physical Sciences › Materials Science › Materials Chemistry › 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.
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