Evidence map›Paper›PMID 40494884›Full record

ArticleNature microbiology2025

Viral evolution prediction identifies broadly neutralizing antibodies to existing and prospective SARS-CoV-2 variants.

Fanchong Jian, Anna Z Wec, Leilei Feng, Yuanling Yu, Lei Wang, Peng Wang, Lingling Yu, Jing Wang, Jacob Hou, Daniela Montes Berrueta and 19 more

Abstract read
In one paragraph

Article in Nature microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Functional and antigenic constraints on the Nipah virus fusion protein.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  16. Article
  17. Article
  18. Functional and antigenic constraints on the Nipah virus fusion protein.bioRxiv : the preprint server for biology · 2026
    Article
  19. Article
  20. Review
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

29 authors.

Fanchong Jian *Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.ORCID http://orcid.org/0000-0001-8703-3507
Anna Z Wec *Moderna Inc., Cambridge, MA, USA.
Leilei Feng *CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Yuanling YuChangping Laboratory, Beijing, China.
Lei WangCAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.
Peng WangChangping Laboratory, Beijing, China.
Lingling YuChangping Laboratory, Beijing, China.
Jing WangBiomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.ORCID http://orcid.org/0000-0002-9084-9985
Jacob HouModerna Inc., Cambridge, MA, USA.
Daniela Montes BerruetaModerna Inc., Cambridge, MA, USA.
Diana LeeModerna Inc., Cambridge, MA, USA.
Tessa SpeidelModerna Inc., Cambridge, MA, USA.
LingZhi MaModerna Inc., Cambridge, MA, USA.
Thu KimModerna Inc., Cambridge, MA, USA.ORCID http://orcid.org/0000-0002-8299-6627
Ayijiang YisimayiBiomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.ORCID http://orcid.org/0000-0003-0648-1864
Weiliang SongBiomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.
Jing WangChangping Laboratory, Beijing, China.
Lu LiuChangping Laboratory, Beijing, China.
Sijie YangBiomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.ORCID http://orcid.org/0009-0001-9834-4340
Xiao NiuBiomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.
Tianhe XiaoBiomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.
Ran AnChangping Laboratory, Beijing, China.
Yao WangChangping Laboratory, Beijing, China.
Fei ShaoChangping Laboratory, Beijing, China.
Youchun WangChangping Laboratory, Beijing, China.ORCID http://orcid.org/0000-0001-9769-5141
Simone PecettaModerna Inc., Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-9898-4324
Xiangxi WangCAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China. xiangxi@ibp.ac.cn.ORCID http://orcid.org/0000-0003-0635-278X
Laura M WalkerModerna Inc., Cambridge, MA, USA. laura.walker@modernatx.com.ORCID http://orcid.org/0000-0001-7704-3197
Yunlong CaoBiomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China. yunlongcao@pku.edu.cn.ORCID http://orcid.org/0000-0001-5918-1078

Funding

Ministry of Science and Technology of the People's Republic of China (Chinese Ministry of Science and Technology) 2022ZD0115002National Natural Science Foundation of China (National Science Foundation of China) 32222030
6 · The paper itself

Abstract

Monoclonal antibodies (mAbs) targeting the SARS-CoV-2 receptor-binding domain are used to treat and prevent COVID-19. However, the rapid evolution of SARS-CoV-2 drives continuous escape from therapeutic mAbs. Therefore, the ability to identify broadly neutralizing antibodies (bnAbs) to future variants is needed. Here we use deep mutational scanning to predict viral receptor-binding domain evolution and to select for mAbs neutralizing both existing and prospective variants. A retrospective analysis of 1,103 SARS-CoV-2 wild-type-elicited mAbs shows that this method can increase the probability of identifying effective bnAbs to the XBB.1.5 strain from 1% to 40% in an early pandemic set-up. Among these bnAbs, BD55-1205 showed potent activity to all tested variants. Cryogenic electron microscopy structural analyses revealed the receptor mimicry of BD55-1205, explaining its broad reactivity. Delivery of mRNA-lipid nanoparticles encoding BD55-1205-IgG in mice resulted in serum half-maximal neutralizing antibody titre values of ~5,000 to XBB.1.5, HK.3.1 and JN.1 variants. Combining bnAb identification using viral evolution prediction with the versatility of mRNA delivery technology can enable rapid development of next-generation antibody-based countermeasures against SARS-CoV-2 and potentially other pathogens with pandemic potential.

Indexed as

Antibodies, NeutralizingAntibodies, ViralBroadly Neutralizing AntibodiesCOVID-19SARS-CoV-2AnimalsAntibodies, MonoclonalCryoelectron MicroscopyEvolution, MolecularFemaleHumansMiceMutationRetrospective StudiesSpike Glycoprotein, CoronavirusAntibodies, MonoclonalAntibodies, NeutralizingAntibodies, ViralBroadly Neutralizing AntibodiesSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2

Identifiers

PMID40494884
PMCPMC12313522

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.