Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2022 Oct 26;14(21):5259.
doi: 10.3390/cancers14215259.

DGKα, Bridging Membrane Shape Changes with Specific Molecular Species of DAG/PA: Implications in Cancer and Immunosurveillance

Affiliations
Review

DGKα, Bridging Membrane Shape Changes with Specific Molecular Species of DAG/PA: Implications in Cancer and Immunosurveillance

José Carlos Bozelli Jr et al. Cancers (Basel). .

Abstract

Cancer immunotherapy has revolutionized the oncology field. Despite the success, new molecular targets are needed to increase the percentage of patients that benefits from this therapy. Diacylglycerol kinase α (DGKα) has gathered great attention as a potential molecular target in immunotherapy because of its role in cancer proliferation and immunosuppression. DGKα catalyzes the ATP-dependent phosphorylation of diacylglycerol (DAG) to produce phosphatidic acid (PA). Since both lipids are potent signaling messengers, DGKα acts as a switch between different signaling pathways. Its role in cancer and immunosuppression has long been ascribed to the regulation of DAG/PA levels. However, this paradigm has been challenged with the identification of DGKα substrate acyl chain specificity, which suggests its role in signaling could be specific to DAG/PA molecular species. In several biological processes where DGKα plays a role, large membrane morphological changes take place. DGKα substrate specificity depends on the shape of the membrane that the enzyme binds to. Hence, DGKα can act as a bridge between large membrane morphological changes and the regulation of specific molecular species of DAG/PA. Bearing in mind the potential therapeutic benefits of targeting DGKα, here, the role of DGKα in cancer and T cell biology with a focus on the modulation of its enzymatic properties by membrane shape is reviewed. The goal is to contribute to a global understanding of the molecular mechanisms governing DGKα biology. This will pave the way for future experimentation and, consequently, the design of better, more potent therapeutic strategies aiming at improving the health outcomes of cancer patients.

Keywords: cancer; cellular signaling; diacylglycerol; diacylglycerol kinase α; immune surveillance; immunotherapy; phosphatidic acid; regulation of enzymes by membrane shape; substrate acyl chain specificity.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
DGKα enzymatic reaction and structure. (A) DGKα catalyzes the ATP-dependent phosphorylation of diacylglycerol (DAG) to produce phosphatidic acid (PA). DAG and PA molecular species bear 16:0 (blue)/18:1 (cyan) acyl chains. This DAG molecular species illustrates an example of DGKα preferred substrate. (B) Domain architecture of DGKα includes two EF hand motifs (EF hand 1 in lime and EF hand 2 in forest green), two C1 domains (C1A in hot pink and C1B in magenta), a catalytic domain (dark turquoise), and an accessory domain (royal blue). Y335 (black arrow), which is involved in DGKα phosphorylation, is identified as well as a proline rich segment (Pro, purple), suggested to be involved in membrane interaction. (C) AlphaFold predicted high-resolution structure of human DGKα (UniprotKB accession number P23743) was obtained from AlphaFold database [25]. Structures were generated using Chimera X [26] and domains colored as follows: EF hand 1 (residues 114–142, lime), EF hand 2 (residues 159–187, forest green), C1A (residues 206–253, hot pink), C1B (residues 268–319, magenta), catalytic (residues 376–500, dark turquoise), accessory (residues 520–701, royal blue), and Pro (residues 722–735, purple). The remaining protein was colored in gold.
Figure 2
Figure 2
Mapping DGKα three-dimensional structure. (A) Sequence conservation of human DGK mapped onto AlphaFold predicted high-resolution structure of human DGKα. Multiple sequence alignment of the ten paralogs of human DGK was done with Clustal Omega [33] and residues were colored based on sequence conservation (maroon = conserved and cyan = variable residues). (B) Electrostatic surface potential (ESP) of AlphaFold predicted high-resolution structure of human DGKα. ESP was calculated with adaptive Poisson-Boltzman solver (APBS) [34] and colored according to color key (red = acidic, white = neutral, and blue = basic surfaces). Enlarged on the left panel ATP docked to its putative binding site, which binds with an average affinity of −7.3 ± 0.6 kcal.mol−1. The three lowest energy docking poses are shown. Blind docking was performed with Webina [35].
Figure 3
Figure 3
DGKα predicted structure is likely the active one. AlphaFold predicted high-resolution structure of human DGKα (UniprotKB accession number P23743). Structures were generated using Chimera X and domains colored as follows: EF hand 1 (residues 114–142, lime), EF hand 2 (residues 159–187, forest green), C1A (residues 206–253, hot pink), C1B (residues 268–319, magenta), catalytic (residues 376–500, dark turquoise), accessory (residues 520–701, royal blue), and Pro (residues 722–735, purple). The remaining protein was colored in gold. Enlarged on the right panel is the overlay between the predicted (green) and the experimentally solved (gray, PDB ID: 6IIE [32]) structures of the EF hand domains. The experimentally solved structure had Ca2+ bound, which is shown in purple. The red arrow indicates the putative ATP-binding site is exposed in the predicted structure.
Figure 4
Figure 4
Membrane-bound DGKα. (A) The spatial arrangement of the AlphaFold predicted structure of human DGKα bound to the eukaryotic plasma membrane was done with PPM 3.0 [47]. Residues in C1 and accessory domains as well as the Pro segment anchors the enzyme to the membrane interface. Only the membrane leaflet interacting with the enzyme is shown. Structures were generated using Chimera X [26] and domains colored as follows: EF hand 1 (residues 114–142, lime), EF hand 2 (residues 159–187, forest green), C1A (residues 206–253, hot pink), C1B (residues 268–319, magenta), catalytic (residues 376–500, dark turquoise), accessory (residues 520–701, royal blue), and Pro (residues 722–735, purple). The remaining protein was colored in gold. (B) The surface of the enzyme interacting with the membrane is shown and colored by Electrostatic surface potential (ESP, red = acidic, white = neutral, and blue = basic surfaces). The membrane leaflet interacting with the enzyme was removed for clarity.
Figure 5
Figure 5
Putative role of DGKα in bridging membrane morphological changes to specific molecular species of DAG/PA in T cell and cancer biological processes. Cartoons illustrating (A) TCR activation and (B) cancer cell migration. It is proposed that in these processes, DGKα would localize in membranes bearing negative curvature (around the IS during TCR activation and the tips of invasive protrusions during cancer cell migration), which would endow the enzyme with its acyl chain specificity, letting it act on its preferred substrates, i.e., DAG with saturated/monounsaturated acyl chains. Schematic representations were generated using Biorender (©BioRender-biorender.com).
Figure 6
Figure 6
CU-3 inhibits DGKα by binding into the ATP-binding site. Electrostatic surface potential (ESP) of AlphaFold predicted high-resolution structure of human DGKα. ESP was calculated with adaptive Poisson–Boltzman solver (APBS) [34] and colored according to color key (red = acidic, white = neutral, and blue = basic surfaces). Enlarged on the left panel CU-3 docked to DGKα. CU-3 docks into the putative ATP binding site with an average affinity of −8.0 ± 0.3 kcal.mol−1. The three lowest energy docking poses are shown. Blind docking was performed with Webina [35].

Similar articles

Cited by

References

    1. Goldberg M.S. Improving cancer immunotherapy through nanotechnology. Nat. Cancer. 2019;19:587–602. doi: 10.1038/s41568-019-0186-9. - DOI - PubMed
    1. Waldman A.D., Fritz J.M., Lenardo M.J. A guide to cancer immunotherapy: From T cell basic science to clinical practice. Nat. Rev. Immunol. 2020;20:651–668. doi: 10.1038/s41577-020-0306-5. - DOI - PMC - PubMed
    1. Johnson D.B., Nebhan C.A., Moslehi J.J., Balko J.M. Immune-checkpoint inhibitors: Long-term implications of toxicity. Nat. Rev. Clin. Oncol. 2022;19:254–267. doi: 10.1038/s41571-022-00600-w. - DOI - PMC - PubMed
    1. Kubli S.P., Berger T., Araujo D.V., Siu L.L., Mak T.W. Beyond immune checkpoint blockade: Emerging immunological strategies. Nat. Rev. Drug Discov. 2021;20:899–919. doi: 10.1038/s41573-021-00155-y. - DOI - PubMed
    1. Korman A.J., Garrett-Thomson S.C., Lonberg N. The foundations of immune checkpoint blockade and the ipilimumab approval decennial. Nat. Rev. Drug Discov. 2021;21:509–528. doi: 10.1038/s41573-021-00345-8. - DOI - PubMed

Grants and funding

This research was funded by the Canadian Natural Sciences and Engineering Research Council grant number RGPIN-2018-05585 to R.M.E and an NSERC Alliance grant ALLRP 576144-22 to RME.

LinkOut - more resources