Evidence map›Paper›PMID 41980104›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Quantifying and combating zoonotic viruses poised for emergence: Using multiplex receptor screening and decoy engineering technologies.

Alex Odoom, Eugene M Obeng, Christian K O Dzuvor

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alex OdoomDepartment of Medical Microbiology, University of Ghana Medical School, Accra KB 4236, Ghana.ORCID 0000-0001-5761-1564
Eugene M ObengSchool of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW 2006, Australia.ORCID 0000-0001-6525-7577
Christian K O DzuvorDepartment of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115.ORCID 0000-0002-9109-051X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viral discovery efforts have uncovered millions of zoonotic viruses across multiple continents, listed on the World Health Organization's pandemic risk register. Over two-thirds of these zoonotic viruses pose significant risks, are poised to infect humans, and expose the limitations of current reactive countermeasures, such as vaccines, monoclonal antibodies, and small-molecule antivirals. To mediate infection, these viruses must undergo significant adaptation and exploit specific receptors on human cells, causing "spillover events." Identifying which human receptors these zoonotic viruses utilize is crucial for assessing spillover risk, understanding viral tropism, and preparing for emergence-ultimately providing insights for pandemic preparedness, development of new antiviral therapeutics, and potentially saving many lives. However, we hypothesize that these advances will require a systemic understanding and scalable platform technologies on an unprecedented scale. Therefore, we propose and evaluate a new and unique paradigm shift toward proactive antiviral interventions centered on host-identified multivalent "decoy" receptor therapeutics that can impose high evolutionary barriers to resistance, even in convergent evolution scenarios. Specifically, we introduce a unified framework that integrates unique, unbiased high-throughput or multiplex receptor screening platforms with AI-driven design to guide the de novo engineering of pandemic-ready broad-spectrum decoys. We also discuss prominent modular engineering strategies that can translate mere molecular affinities into the avidity necessary for potent pan-viral prophylaxis and therapy. The overall integrated pipeline proposed is expected to facilitate the preemptive development of robust countermeasures that will fundamentally reshape our approach to quantifying and combating known and future zoonotic viral threats.

Indexed as

Receptors, VirusViral ZoonosesVirusesZoonosesAnimalsAntiviral AgentsHumansAntiviral AgentsReceptors, Virusdecoy receptorsmultiplex screeningpandemic preparednesstherapeuticszoonotic spillover

Identifiers

PMID41980104
PMCPMC13099566

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.