Broad-spectrum activity against mosquito-borne flaviviruses achieved by a targeted protein degradation mechanism

Viral genetic diversity presents significant challenges in developing antivirals with broad-spectrum activity and high barriers to resistance. Here we report development of proteolysis targeting chimeras (PROTACs) targeting the dengue virus envelope (E) protein through coupling of known E fusion inhibitors to ligands of the CRL4CRBN E3 ubiquitin ligase. The resulting small molecules block viral entry through inhibition of E-mediated membrane fusion and interfere with viral particle production by depleting intracellular E in infected Huh 7.5 cells. This activity is retained in the presence of point mutations previously shown to confer partial resistance to the parental inhibitors due to decreased inhibitor-binding. The E PROTACs also exhibit broadened spectrum of activity compared to the parental E inhibitors against a panel of mosquito-borne flaviviruses. These findings encourage further exploration of targeted protein degradation as a differentiated and potentially advantageous modality for development of broad-spectrum direct-acting antivirals.


Statistics
For all statistical analyses, confirm that the following items are present in in the figure legend, table legend, main text, or or Methods section.

n/a Confirmed
The exact sample size (n) for each experimental group/condition, given as as a discrete number and unit of of measurement A statement on on whether measurements were taken from distinct samples or or whether the same sample was measured repeatedly The statistical test(s) used AND whether they are one-or or two-sided Only common tests should be described solely by name; describe more complex techniques in the Methods section.

A description of of all covariates tested
A description of of any assumptions or or corrections, such as as tests of of normality and adjustment for multiple comparisons A full description of of the statistical parameters including central tendency (e.g.means) or or other basic estimates (e.g.regression coefficient) AND variation (e.g. standard deviation) or or associated estimates of of uncertainty (e.g.confidence intervals) For null hypothesis testing, the test statistic (e.g.F, t, r) with confidence intervals, effect sizes, degrees of of freedom and P value noted Give P values as exact values whenever suitable.
For Bayesian analysis, information on on the choice of of priors and Markov chain Monte Carlo settings For hierarchical and complex designs, identification of of the appropriate level for tests and full reporting of of outcomes Estimates of of effect sizes (e.g.Cohen's d, Pearson's r), ), indicating how they were calculated Our web collection on statistics for biologists contains articles on many of the points above.

Data analysis
For manuscripts utilizing custom algorithms or or software that are central to to the research but not yet described in in published literature, software must be be made available to to editors and reviewers.We We strongly encourage code deposition in in a community repository (e.g.GitHub).See the Nature Portfolio guidelines for submitting code & software for further information.

Reporting on sex and gender
Reporting on race, ethnicity, or other socially relevant groupings

Ethics oversight
Note that full information on the approval of the study protocol must also be provided in the manuscript.

Field-specific reporting
Please select the one below that is the best fit for your research.If you are not sure, read the appropriate sections before making your selection.

Life sciences
Behavioural & social sciences Ecological, evolutionary & environmental sciences For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf

Life sciences study design
All studies must disclose on these points even when the disclosure is negative.

Blinding
Reporting for specific materials, systems and methods We require information from authors about some types of materials, experimental systems and methods used in many studies.Here, indicate whether each material, system or method listed is relevant to your study.If you are not sure if a list item applies to your research, read the appropriate section before selecting a response.
Use the terms sex (biological attribute) and gender (shaped by social and cultural circumstances) carefully in order to avoid confusing both terms.Indicate if findings apply to only one sex or gender; describe whether sex and gender were considered in study design; whether sex and/or gender was determined based on self-reporting or assigned and methods used.Provide in the source data disaggregated sex and gender data, where this information has been collected, and if consent has been obtained for sharing of individual-level data; provide overall numbers in this Reporting Summary.Please state if this information has not been collected.Report sex-and gender-based analyses where performed, justify reasons for lack of sex-and gender-based analysis.
Please specify the socially constructed or socially relevant categorization variable(s) used in your manuscript and explain why they were used.Please note that such variables should not be used as proxies for other socially constructed/relevant variables (for example, race or ethnicity should not be used as a proxy for socioeconomic status).Provide clear definitions of the relevant terms used, how they were provided (by the participants/respondents, the researchers, or third parties), and the method(s) used to classify people into the different categories (e.g.self-report, census or administrative data, social media data, etc.) Please provide details about how you controlled for confounding variables in your analyses.
Describe the covariate-relevant population characteristics of the human research participants (e.g.age, genotypic information, past and current diagnosis and treatment categories).If you filled out the behavioural & social sciences study design questions and have nothing to add here, write "See above." Describe how participants were recruited.Outline any potential self-selection bias or other biases that may be present and how these are likely to impact results.
Identify the organization(s) that approved the study protocol.
No statistical method was used to predetermine sample sizes.Sample size are described in the figure legends.All the studies were calculated with at least 2 or more independent experiments.
No data were excluded from analysis.
In each study, at least two or more experiments were performed independently as noted in the manuscript.All attempts at replication were successful.
Randomization for different experimental groups was not relevant.The studies were performed on the cell lines acquired from collaborator or commercial sources.
The study does not involve animals or human subjects.The investigators were not blinded to in vitro cell based experiments for accurate identification of samples, data collection, and analysis.