Synthetic group A streptogramin antibiotics that overcome Vat resistance

Abstract

Natural products serve as chemical blueprints for most antibiotics in clinical use. The evolutionary process by which these molecules arise is inherently accompanied by the co-evolution of resistance mechanisms that shorten the clinical lifetime of any given class of antibiotics1. Virginiamycin acetyltransferase (Vat) enzymes are resistance proteins that provide protection against streptogramins2, potent antibiotics against Gram-positive bacteria that inhibit the bacterial ribosome3. Owing to the challenge of selectively modifying the chemically complex, 23-membered macrocyclic scaffold of group A streptogramins, analogues that overcome the resistance conferred by Vat enzymes have not been previously developed2. Here we report the design, synthesis, and antibacterial evaluation of group A streptogramin antibiotics with extensive structural variability. Using cryo-electron microscopy and forcefield-based refinement, we characterize the binding of eight analogues to the bacterial ribosome at high resolution, revealing binding interactions that extend into the peptidyl tRNA-binding site and towards synergistic binders that occupy the nascent peptide exit tunnel. One of these analogues has excellent activity against several streptogramin-resistant strains of Staphylococcus aureus, exhibits decreased rates of acetylation in vitro, and is effective at lowering bacterial load in a mouse model of infection. Our results demonstrate that the combination of rational design and modular chemical synthesis can revitalize classes of antibiotics that are limited by naturally arising resistance mechanisms.

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Fig. 1: Modular synthesis enables access to more than 60 fully synthetic group A streptogramins.
Fig. 2: Antibiotic activity and in vivo efficacy of selected group A streptogramins.
Fig. 3: In vitro acetylation, VatA binding, and ribosome binding of highly active analogues.

Data availability

Models and maps generated during this study are available in the EMDB and PDB (accessions are listed in Extended Data Tables 4 and 5). Source data are provided with this paper.

Code availability

Forcefield-based refinement is available in PHENIX (versions 1.15 and later) using beta features available in Schrӧdinger 2019-3. Python code for analysing IVT data and VatA kinetics data are available on github: https://github.com/fraser-lab/streptogramin.

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Acknowledgements

We thank F. Ward and J. Cate for initial advice on ribosome purifications and translation assays, E.Nogales and a UCSF-UCB Sackler Sabbatical Exchange Fellowship (J.S.F.) for initial cryo-EM access and training. A.A.T. and J.P. were supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. 1650113. D.J.L. was supported by a Postdoctoral Individual National Research Award NIH AI148120. H.A.C. was supported by a National Institute on Minority Health and Health Disparities (NIMHD) research diversity supplement under NIH GM123159. This project was funded by the UCSF Program for Breakthrough Biomedical Research, funded in part by the Sandler Foundation (J.S.F. and I.B.S.), a Sangvhi-Agarwal Innovation Award (J.S.F.), Packard Fellowships from the David and Lucile Packard Foundation (J.S.F. and I.B.S.), NIH GM123159 (J.S.F.), and NIH GM128656 (I.B.S.). We thank G. Meigs and J. Holton at Beamline 8.3.1 at the Advanced Light Source, which is operated by the University of California Office of the President, Multicampus Research Programs and Initiatives grant MR-15-328599, the National Institutes of Health (R01 GM124149 and P30 GM124169), Plexxikon Inc., and the Integrated Diffraction Analysis Technologies program of the US Department of Energy Office of Biological and Environmental Research. The Advanced Light Source (Berkeley, CA) is a national user facility operated by Lawrence Berkeley National Laboratory on behalf of the US Department of Energy under contract number DE-AC02-05CH11231, Office of Basic Energy Sciences. We thank M. Thompson for comments on the crystallography methods. We thank A. Myasnikov and D. Bulkley for technical support at the UCSF Center for Advanced CryoEM, which is supported by NIH grants S10OD020054 and S10OD021741 and the Howard Hughes Medical Institute (HHMI). We thank E. Eng and E. Kopylov for technical support at the National Center for CryoEM Access and Training (NCCAT) and the Simons Electron Microscopy Center located at the New York Structural Biology Center, which is supported by the NIH Common Fund Transformative High Resolution Cryo-Electron Microscopy program (U24 GM129539) and by grants from the Simons Foundation (SF349247) and NY State. We thank W. Weiss at the University of North Texas Health Science Center for conducting the animal study.

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Contributions

Q.L. and I.B.S. determined analogues for synthesis and designed the synthetic routes; Q.L. executed and optimized the syntheses of analogues, with assistance from A.A.T. (analogues 2932), R.W. (analogue 21), K.J. (analogues 27 and 28), and D.C. (analogue 26); J.P. and D.J.L. prepared samples and collected cryo-EM data; J.P. and A.F.B. calculated cryo-EM reconstructions; J.P. and J.E.P. performed the VatA acetylation assay; J.P. performed the in vitro translation experiments; G.v.Z. and K.B. developed new tools for cryo-EM model refinement; J.P., K.B. and J.T.B. performed cryo-EM model refinements; G.v.Z., J.P., H.A.C., N.Z. and M.P.J. determined relative energies of macrocycle confirmations; H.A.C. collected X-ray crystallographic data and performed X-ray model refinements; D.S., C.W., B.M., E.M, and O.C. designed and executed the MIC assays; Q.L., J.P., I.B.S. and J.S.F. wrote the manuscript. All authors discussed the results and commented on the manuscript.

Corresponding author

Correspondence to Ian B. Seiple.

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Competing interests

K.B. and G.v.Z. are employees of Schrodinger Inc. D.S., C.W. and B.M. are employees of Micromyx.

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Peer review information Nature thanks Martin Burke, Gerard Wright and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Natural and semisynthetic streptogramins and their molecular mechanisms of action and resistance.

a, Selected natural and semisynthetic streptogramin analogues. Modifications installed by semisynthesis are highlighted in blue. b, 2.5-Å cryo-EM structure of VM2 bound to the 50S subunit of the E. coli ribosome. Coulomb potential density is contoured in dark blue at 4.0σ and light grey at 1.0σ. Atom colouring of VM2 mirrors the building blocks used in its synthesis (see Fig. 2). c, Binding interactions between VM2 and residues in the ribosomal binding site. d, X-ray crystal structure VM1 bound to the resistance protein VatA (PDB ID: 4HUS). e, Binding interactions between VM1 and VatA, highlighting the extensive hydrophobic interactions at C3–C6. Acetylation occurs at the C14 alcohol. f, g, Conformational energy of VM2 showing contributions on a per atom basis when refined with standard CIF-based restraints generated by ‘phenix.eLBOW’ (f) and when refined with OPLS3e/VSGB2.1 force field (g). Colour indicates low strain (green, −14 kcal mol−1) up to high strain (red, 10 kcal mol−1), with total conformational energy of 39.5 kcal mol−1 (f) and −88.3 (g). Hydrogens were added and optimized with fixed heavy atoms for the CIF-based refined conformation using ‘prepwizard’; the PHENIX-OPLS3e/VSGB2.1 refined conformation was taken as is. Energies were calculated using Prime and per atom contribution visualized using Maestro’s prime energy visualization.

Extended Data Fig. 2 List of streptogramins tested for inhibitory activity.

Fully synthetic group A streptogramins tested for inhibitory activity against 20 strains of bacteria (see Extended Data Figs. 3, 4).

Extended Data Fig. 3 Inhibitory activity against Gram-positive organisms.

MIC values for selected analogues against an expanded panel of Gram-positive pathogens. Source data

Extended Data Fig. 4 Inhibitory activity against Gram-negative organisms.

MIC values for selected analogues against an expanded panel of Gram-negative pathogens. Source data

Extended Data Fig. 5 Cryo-EM density for all compounds bound to the E. coli ribosome.

a, 2.6-Å cryo-EM structure of VM2 bound to the 50S subunit of the E. coli ribosome. Coulomb potential density is contoured in dark blue at 4.0σ and light grey at 1.0σ for the entire figure. b, 2.8-Å cryo-EM structure of 21 bound to the 50S subunit of the E. coli ribosome. c, 2.8-Å cryo-EM structure of 40e bound to the 50S subunit of the E. coli ribosome. d, 2.5-Å cryo-EM structure of 40o bound to the 50S subunit of the E. coli ribosome. e, 2.8-Å cryo-EM structure of 40q bound to the 50S subunit of the E. coli ribosome. f, 2.6-Å cryo-EM structure of 41q bound to the 50S subunit of the E. coli ribosome. g, 2.5-Å cryo-EM structure of 46 bound to the 50S subunit of the E. coli ribosome. h, 2.5-Å cryo-EM structure of 47 bound to the 50S subunit of the E. coli ribosome. i, 2.7-Å cryo-EM structure of 46/VS1 bound to the 50S subunit of the E. coli ribosome. j, 2.8-Å cryo-EM structure of 47/VS1 bound to the 50S subunit of the E. coli ribosome.

Extended Data Fig. 6 Gold standard and map to model Fourier shell correlation plots.

aj, The particle Fourier shell correlation (FSC) curves for reconstructions obtained by cisTEM using a molecular mass of 1.8 MDa are shown in blue with unmasked map–model FSC curves obtained from ‘phenix.mtriage’ shown in orange. Dashed lines indicate FSC of 0.143 for estimating gold standard resolution and FSC of 0.5 for estimating map–model resolution.

Extended Data Fig. 7 Conformations of 46 and 47 in the ribosome and in VatA.

a, The conformation of 46 minimized by quantum mechanical methods in low dielectric, shows how the isoquinoline side chain packs over the macrocycle. b, By contrast, the ribosome-bound conformations of 46 determined by cryo-EM show that the side chain extends away from the macrocycle due to interactions formed in the binding site. c, Model of 47 in the conformation bound to the ribosome modelled into the active site of VatA (shown in surface). d, Model of 46 in the conformation bound to the ribosome modelled into the active site of VatA. e, Low energy model of 46 modelled into the active site of VatA. f, Overlay of VatA-bound (marine), ribosome-bound (violet), and ribosome with VS1-bound (light pink) conformations of 47. g, X-ray crystal structures of VM1 bound to VatA (PDB code 4HUS; 2.4 Å) and 46 bound to VatA at 2.8-Å resolution.

Extended Data Table 1 Ligand energies by different refinement schemes
Extended Data Table 2 Comparative energies of ligands bound to VatA and to the ribosome
Extended Data Table 3 Statistical analyses of mouse thigh in vivo data, MIC assays and VatA kinetics data
Extended Data Table 4 X-Ray data collection, processing, and model refinement statistics
Extended Data Table 5 Cryo-EM data collection, processing, and model refinement statistics

Supplementary information

Supplementary Information

Procedures for MIC determination and chemical synthesis.

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Excel file containing MIC data featured in the manuscript and extended data.

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Li, Q., Pellegrino, J., Lee, D.J. et al. Synthetic group A streptogramin antibiotics that overcome Vat resistance. Nature 586, 145–150 (2020). https://doi.org/10.1038/s41586-020-2761-3

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