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A general method for chemogenetic control of peptide function

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Abstract

Natural or engineered peptides serve important biological functions. A general approach to achieve chemical-dependent activation of short peptides will be valuable for spatial and temporal control of cellular processes. Here we present a pair of chemically activated protein domains (CAPs) for controlling the accessibility of both the N- and C-terminal portion of a peptide. CAPs were developed through directed evolution of an FK506-binding protein. By fusing a peptide to one or both CAPs, the function of the peptide is blocked until a small molecule displaces them from the FK506-binding protein ligand-binding site. We demonstrate that CAPs are generally applicable to a range of short peptides, including a protease cleavage site, a dimerization-inducing heptapeptide, a nuclear localization signal peptide, and an opioid peptide, with a chemical dependence up to 156-fold. We show that the CAPs system can be utilized in cell cultures and multiple organs in living animals.

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Fig. 1: Engineering of the CapN system.
Fig. 2: Engineering of the CapC system.
Fig. 3: Applying CAPs for shield-1-induced protein translocation.
Fig. 4: Applying CAPs to cage NLS peptide and opioid peptide.
Fig. 5: Applying CAPs to shield-1-induced transgene transcription.
Fig. 6: AquaShield-1 induced transgene expression in mouse tissues.

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Data availability

All the data supporting the findings of this study are available within the paper and its supplementary information files. PDB-1FAP, PDB-1NSG, and PDB-6DDF cited in this study are available at Protein Data Bank. All the DNA constructs used in this study are available upon request to the corresponding author. Source data are provided with this paper.

Code availability

The GROMACS software package including source code is freely available at https://www.gromacs.org and https://gitlab.com/gromacs/gromacs and includes implementations of all simulation and analysis algorithms used for this project. The VMD (Visual Molecular Dynamics) package used to visualize the simulated proteins is available from https://www.ks.uiuc.edu/Research/vmd.

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Acknowledgements

H. Jiang helped with TEV protease expression and purification and neuronal culture preparation. L. Wen helped with cloning and imaging. FACS was performed at the Flow Cytometry Core at the University of Michigan. This study is supported by the University of Michigan and National Institutes of Health (NIH) grants DP2MH132939, R01AT011652, and R01HL156989. M.H. gratefully acknowledges financial support from Research Corporation for Science Advancement (#27360). K.K. is supported by NIH F31MH12915001.

Author information

Authors and Affiliations

Authors

Contributions

W.W., J.S., L.G., and P.L. conceived the project idea. W.W., J.S., and L.G. designed the yeast cell-based and cell culture experiments. P.L., X.L., C.E., W.W., J.S., and L.G. designed the animal experiments. J.S. performed the CapN evolution and L.G. performed the CapC evolution. L.G. performed cell culture application of CAPs caging TEVcs, and characterization of shield-1 concentration and incubation time in the transgene transcription system. J.S., L.G., and K.L. performed application of CapC caging enkephalin. J.S., K.K., and G.S. performed application of CAPs caging SsrA for translocation. J.S. performed all other cell culture application and characterization. X.L. and C.E. performed the animal experiments. M.H. performed the simulation experiment. All authors analyzed data, wrote and edited the manuscript.

Corresponding authors

Correspondence to Peng Li or Wenjing Wang.

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Competing interests

The authors declare the following competing interests. A patent application has been filed by W.W., P.L., J.S., and L.G. with title ‘Chemogenetic Regulation of Peptide Function,’ U.S. Provisional Patent Application No. 63/329,736, filed April 11, 2022; applicants: the Regents of the University of Michigan; patent pending. All other authors declare no competing interests.

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Nature Methods thanks John Ngo and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Rita Strack, in collaboration with the Nature Methods team. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Ligand binding site of FKBP and directed evolution results of CapN.

Related to main Fig. 1. a, Crystal structure of FKBP12 (PDB:1FAP). The hydrophobic residues around the ligand binding site are shown in yellow and stick representation. b, Sequences of forty clones from the post 4th round CapN library as shown in main Fig. 1e. Twenty-three distinct sequences were identified. Clone #1 is the final CapN used for the rest of this study. c, FACS analysis of the most enriched eight clones, corresponding to clones #1-#8 shown in b. Values are median HA intensity of FLAG-positive cells (Q2 + Q4). All eight clones showed similar results. This experiment was performed once.

Extended Data Fig. 2 All-atom molecular dynamics simulations.

Results from a 2 microsecond molecular dynamics simulations of FKBP and a capped ArgTyrSerProAsnLeu peptide in 150 mM buffer. a, the central configurations for the top 5 clusters (Rank 1–5) obtained from RMSD clustering indicate direct interactions between Leu6 of the peptide (shown in a’licorice’ representation; cap residues are shown in green, other atoms in CPK colors with gray carbons) and the F36V binding site of FKBP (shown as van-der-Waals spheres). The secondary structure of the FKBP protein is shown in a cartoon representation with red 𝛼-helices and yellow 𝛽-sheets. b, RMSD time traces with respect to the structures shown in a indicate the longevity of the respective conformations within the simulations. RMSD’s of 0 indicate the simulation time points corresponding to the structures in a. A horizontal dashed line indicates the 1.5 Å cutoff used for clustering. c, time traces of the center of mass distances between each individual sidechain of the peptide and the sidechain of the F36V binding site indicate a persistent proximity of Leu6 to the binding site for a large fraction of the simulation trajectory (distances of 5–6 Å). Fractions of the simulation trajectory with close proximity of Leu6 to the F36V binding site include all configurations associated with the top 5 clusters shown in a.

Source data

Extended Data Fig. 3 Directed evolution results of CapC.

Related to main Fig. 2. a, Sequences of twenty clones from the post 2nd round CapC library as shown in main Fig. 2c. Eighteen distinct sequences were identified and characterized. One sequence with early stop codon is not shown. Clone #18 is the final CapC used for the rest of this study. b, FACS analysis of the eighteen clones shown in a. Values are median HA intensity of FLAG-positive cells (Q2 + Q4). This experiment was performed once.

Extended Data Fig. 4 Comparison of single CapN, single CapC, and tandem CAPs in caging TEVcs.

a, Scheme of the three constructs tested. CapN-TEVcs-CapC is the combined use of both post-evolution CAPs. b, FACS plots of the three constructs shown in a. Values are median biotin intensity of FLAG-positive cells (Q2 + Q4). This experiment used a stronger TEV protease condition than main Figs. 1e and 1f. See method section for details. Protease cleavage (‘+ shield-1’ or ‘− shield-1’) is defined as the difference of the median HA signal between the + protease and – protease conditions. The dynamic ranges are calculated by the ratio of protease cleavage of the ‘+ shield-1’ and ‘− shield-1’ conditions. This experiment was performed once.

Extended Data Fig. 5 µOR peptide ligands and binding pocket, and effect of different drugs in the control study.

Related to main Fig. 4c, d. a, Left: Structure of [Met5]-enkephalin and its analog DAMGO. Right: Crystal structure of µOR binding pocket. PDB: 6DDF. b, Scheme and sequence of the constructs. SS, signal sequence (KTIIALSYIFCLVFA) is cleaved before the protein is trafficked to plasma membrane. Enkephalin (YGGFM). Left: Construct of CapC caged enkephalin fused to µOR. Right: Construct of µOR only used for control study. c, Cells transfected with µOR construct were stimulated with forskolin (1 µM) at 15 min, and then different drugs (10 µM) at 45 min. Top: Four conditions plotted on the same graph. Bottom: Four conditions plotted on separate graphs. From left to right: no drug, naloxone, shield-1, DAMGO. n = 3 wells from one replicate for all conditions. Errors are standard error of the mean. This experiment was performed once.

Source data

Extended Data Fig. 6 Effect of shield-1 on transcription-activation domain expression.

Related to main Fig. 5. a, Quantification of reporter gene activation level (mCherry, left) and transcription-activation domain expression marker level (EGFP, right). n = 12 fields of view from one replicate for all conditions. b, No difference in reporter expression was found between the + shield-1 and – shield-1 conditions in the control study with SspB-EGFP-VP16 only. n = 12 fields of view from one replicate for all conditions. All scale bars, 50 µm. P values are determined by unpaired two-tailed t-tests. **P < 0.01; ***P < 0.001; ****P < 0.0001; NS, not significant. This experiment was performed three times with similar results.

Source data

Extended Data Fig. 7 Dose response curve of CapC and CAPs caged SsrA.

The mean mCherry intensities of EGFP positive cell population are plotted against shield-1 concentration. Half maximum response was observed at 21 nM for CapC single-caged SsrA (95% confidence interval = 19 nM ~ 24 nM) and 55 nM for CAPs double-caged SsrA (95% confidence interval = 51 nM ~ 59 nM). n = 3 technical replicates for all conditions. Errors are standard error of the mean. Source FACS data is shown in Supplementary Fig. 8. This experiment was performed once.

Source data

Supplementary information

Supplementary Information

Supplementary Figs 1–14, Supplementary Method 1, Supplementary Table, References.

Reporting Summary

Peer Review File

Supplementary Video

Video of shield-1 induced protein translocation to plasma membrane.

Supplementary Data

Statistical data of Supplementary Figs 1, 7, 9, 12.

Source data

Source Data Fig. 3

Statistical data in graphs.

Source Data Fig. 4

Statistical data in graphs.

Source Data Fig. 5

Statistical data in graphs.

Source Data Fig. 6

Statistical data in graphs.

Source Data Extended Data Fig. 2b

Simulation data in graphs.

Source Data Extended Data Fig. 2c

Simulation data in graphs.

Source Data Extended Data Fig. 5

Statistical data in graphs.

Source Data Extended Data Fig. 6

Statistical data in graphs.

Source Data Extended Data Fig. 7

Statistical data in graphs.

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Shen, J., Geng, L., Li, X. et al. A general method for chemogenetic control of peptide function. Nat Methods 20, 112–122 (2023). https://doi.org/10.1038/s41592-022-01697-8

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