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Computational design of constitutively active cGAS


Cyclic GMP–AMP synthase (cGAS) is a pattern recognition receptor critical for the innate immune response to intracellular pathogens, DNA damage, tumorigenesis and senescence. Binding to double-stranded DNA (dsDNA) induces conformational changes in cGAS that activate the enzyme to produce 2′-3′ cyclic GMP–AMP (cGAMP), a second messenger that initiates a potent interferon (IFN) response through its receptor, STING. Here, we combined two-state computational design with informatics-guided design to create constitutively active, dsDNA ligand-independent cGAS (CA-cGAS). We identified CA-cGAS mutants with IFN-stimulating activity approaching that of dsDNA-stimulated wild-type cGAS. DNA-independent adoption of the active conformation was directly confirmed by X-ray crystallography. In vivo expression of CA-cGAS in tumor cells resulted in STING-dependent tumor regression, demonstrating that the designed proteins have therapeutically relevant biological activity. Our work provides a general framework for stabilizing active conformations of enzymes and provides CA-cGAS variants that could be useful as genetically encoded adjuvants and tools for understanding inflammatory diseases.

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Fig. 1: Computational design of a DNA-independent constitutively active cGAS.
Fig. 2: Structural and bioinformatics comparison between cGAS and the static structural homolog MiD51.
Fig. 3: Activity of bioinformatics-guided CA-cGAS variants.
Fig. 4: X-ray crystallography of CA-cGAS variants.
Fig. 5: In vivo activity of CA-cGAS-50.

Data availability

X-ray coordinates and structure factors are deposited in the RCSB Protein Data Bank under IDs 7LZ3 (CA-cGAS-41) and 7KXS (CA-cGAS-50). All raw data are provided as source data files.

Code availability

The Rosetta software and source code is freely available for non-profit use and can be licensed for commercial use. See


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We thank M. Lajoie, M. Pepper and D. Baker for discussions; D. Mannikko and S. Stoll for related investigations; J. Woodward for information and related investigations; R. Krishnamurty for project management; and members of the King laboratory for comments on the manuscript. Figure 5b was created using This work was funded by a grant from the Bill & Melinda Gates Foundation (OPP1156262) to N.P.K. and D.B.S. D.B.S. is a Howard Hughes Medical Institute Faculty Scholar. X-ray data were collected at the Advanced Light Source at LBNL, supported by the Howard Hughes Medical Institute and grants from NIH (P30 GM124169-01, ALS-ENABLE P30 GM124169 and S10OD018483), NCI SBDR (CA92584) and DOE-BER IDAT (DE-AC02-05CH11231). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations



Q.M.D., E.E.G., D.B.S. and N.P.K. conceived the study. Q.M.D. designed CA-cGAS. Q.M.D. and S.O. performed bioinformatics analyses. E.E.G., H.E.V. and S.C. performed ISRE, cellular cGAMP concentration and in vivo assays. M.R.J. performed in vivo assays. Q.M.D. performed biochemical analyses. Q.M.D. and A.K. performed crystal screens and optimization. B.S. collected the crystallographic data. A.K.B. and M.J.B. analyzed and processed the crystallography data. All authors analyzed data. Q.M.D., D.B.S. and N.P.K. wrote and revised the manuscript.

Corresponding author

Correspondence to Neil P. King.

Ethics declarations

Competing interests

Q.M.D., E.E.G., D.B.S. and N.P.K. are inventors on a patent application (PCT/US22/24255) related to constitutively active cGAS proteins. The King laboratory has received unrelated sponsored research agreements from Pfizer and GSK. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Structural & Molecular Biology thanks Philip Kranzusch, John Wilson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Florian Ullrich, in collaboration with the Nature Structural & Molecular Biology team.

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Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Schematic of the ISRE assay.

a, CA-cGAS plasmids are generated, combined with hSTING and ISRE-Luciferase plasmids, and b, transfected into 293 T cells. c, Cells were incubated for 4–16 hours, lysed, and luciferase activity measured. d, Luciferase activity of the CA-cGAS-04 variant compared to WT, K395A/K399A, and K395M/K399M cGAS.

Extended Data Fig. 2 Bifurcation in unique sequences used to find E-value cutoff.

The number of sequences in multiple sequence alignments constructed using cGAS (orange) or MiD-51 (blue) input sequences, as well as the number of unique sequences found only in the cGAS or MiD51 alignment but not both (grey), and the total number of sequences (black) plotted as a function of the E-value cutoff used to generate the alignment. The ratio of unique sequences to total sequences (green) is plotted on the secondary y axis.

Source data

Extended Data Fig. 3 CA-cGAS activity and reaction products in vitro.

a, CA-cGAS activity by ISRE assay increases over time post transfection. b, Chromatogram of CA-cGAS purification by nickel affinity chromatography. The high absorbance at 260 nm relative to 280 nm indicates co-purificiation of significant amounts of nucleic acid. c, Chromatogram of CA-cGAS purification by heparin affinity chromatography monitored by absorbance at 280 nm and 260 nm. Note the much lower relative absorbance at 260 nm compared to (b). d, UV-vis spectrum of nickel-, heparin-, SEC-purified CA-cGAS and the ratio of absorbance to 260 nm to 280 nm, indicating pure protein. e, 2′,3′-cGAMP was measured by competition ELISA after in vitro reactions of wild-type cGAS with dsDNA, or CA-cGAS-41 and CA-cGAS-50 without dsDNA and either 100 mM ATP and 100 mM GTP, or 200 mM ATP only. f, In vitro reactions failed to produce detectable 3′,3′-cGAMP.

Source data

Extended Data Fig. 4 DNA binding and oligomerization of WT and CA-cGAS variants.

a, Agarose gel electrophoresis of dsDNA mixed with increasing concentrations of CA-cGAS or WT cGAS. Top row stained with SYBR Safe. Bottom row is the same gel stained with coomassie. Molar ratios are, left to right, 1:0, 0:1, 1:0.1, 1:0.316, 1:1, 1:3.16, and 1:10 dsDNA to CA-cGAS. The increasing molar ratio is indicated by the triangle above the gel images. Electrophoretic mobility shift assays were performed at least three times for each sample with similar results. Representative images are shown. The assay was performed three times with similar results b, SEC chromatogram of WT or CA-cGAS with or without incubation with dsDNA oligomers. WT cGAS, CA-cGAS-41, and CA-cGAS-50 all elute as monomers in the absence of dsDNA, shifting to earlier elution volumes in the presence of excess DNA. c, Activity in cells is not affected by truncating the unstructured N-terminal domain (compare to Fig. 3b).

Source data

Extended Data Fig. 5 Similarities and differences between CA-cGAS crystal structures and the active conformation of mcGAS.

The crystallographic asymmetric units of a, CA-cGAS-41 and b, CA-cGAS-50 with 2Fo-Fc maps after model building and refinement. The activation loop in chain A of the asymmetric unit does not adopt the inactive (PDB ID 4K8V) or active (PDB ID 4K97) conformation in c, CA-cGAS-41 or d, CA-cGAS-50. e, Details of the CA-cGAS-41 mutations (labeled and colored blue). f, CA-cGAS-41 crystallographic contacts between chains A and B within the asymmetric unit. g, Details of the CA-cGAS-50 mutations (labeled and colored blue). h, CA-cGAS-50 crystallographic contacts between copies of the A chain in one asymmetric unit and the B chain in another asymmetric unit. All maps are 2Fo-Fc maps contoured at 1.0 sigma.

Extended Data Fig. 6 ISRE activity assays of additional mcGAS and hCGAS variants.

a, The activity of bioinformatics consensus mutations applied to the break in the spine helix in a CA-cGAS-41 background. b, Based on the available activity data, computational, and bioinformatics analysis, we can infer a series of mutations that may enhance the activity of CA-cGAS. Specifically, T197V variants are more active than variants without that mutation, variants with T197L are inactive, here T197I decreased the activity of CA-cGAS-41, suggesting that valine is the largest hydrophobic residue allowed at this position. R158S adds a capping residue on the carbonyl end of the N-terminal segment of the spine helix but does not increase activity. Y200I instead of Y200F makes CA-cGAS-41 more like CA-cGAS-50, testing the interchangeability of the activating mutations. Mutations at position 207 are designed to destabilize the inactive conformation of the active site loop. S207G and S207V are as active as CA-cGAS-41, but S207I is inactive. c, Recent work suggests phosphorylation at Y201 retains cGAS in the cytosol42. However, in the active conformation this residue is well packed; phosphorylation would likely inhibit activation, but it is unclear how phosphorylation might affect CA-cGAS activity. To mimic phosphorylation at residue 201, we introduced the mutation Y201E. We also made Y201F or Y201W mutations to prevent phosphorylation at that site. Y201E completely knocks out activity in WT cGAS and significantly lowers it in some, but not all, CA-cGAS variants. Mutating Y201 to phenylalanine or tryptophan had little effect on cGAS activity. d, The activity of CA-cGAS-22, -41, -42, and -50 mutations in an hcGAS background.

Source data

Extended Data Fig. 7 Schematic depiction of multi-state design framework and characterization pipeline.

The key steps of the design and characterization pipeline are depicted schematically. The steps at which each CA-cGAS variant was discovered are indicated.

Supplementary information

Reporting Summary

Supplementary Table 1-2

Supplementary Table 1: All cGAS designs screened by the ISRE assay and their activity. Supplementary Table 2: Sequences of CA-cGAS variants.

Source data

Source Data Fig. 1

Alpha-carbon distances between active and inactive states, computational design metrics, and ISRE raw data.

Source Data Fig. 2

MiD51 and cGAS hit scores, residue probability table.

Source Data Fig. 3

ISRE data, fluorescence intensity measurements, and slopes.

Source Data Fig. 5

cGAMP measurements and statistical source data for tumor measurements.

Source Data Extended Data Fig. 2

Sequence classification as a function of MSA permissiveness.

Source Data Extended Data Fig. 3

Chromatograms and spectra, cGAMP measurements.

Source Data Extended Data Fig. 4

Chromatograms and ISRE data.

Source Data Extended Data Fig. 4

Unprocessed gel images.

Source Data Extended Data Fig. 6

ISRE data.

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Dowling, Q.M., Volkman, H.E., Gray, E.E. et al. Computational design of constitutively active cGAS. Nat Struct Mol Biol 30, 72–80 (2023).

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