Article in mAbs, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing 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.
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
14 authors.
Lidia CerdánDepartment of Microbial Biotechnology, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain.ORCID 0000-0003-4938-5848
Katixa SilvaDepartment of Macromolecular Structures, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain.
Daniel Rodríguez-MartínDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain.ORCID 0000-0002-6838-6355
Patricia PérezDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain.ORCID 0000-0001-8983-6784
María A NoriegaDepartment of Macromolecular Structures, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain.
Ana Esteban MartínDepartment of Biotechnology, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Consejo Superior de Investigaciones Científicas (INIA-CSIC), Madrid, Spain.
Alfonso Gutiérrez-AdánDepartment of Animal Reproduction, INIA-CSIC, Madrid, Spain.
Yago MargollesDepartment of Microbial Biotechnology, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain.ORCID 0000-0003-1413-060X
Juan A CorberaInstituto Universitario de Investigaciones Biomédicas y Sanitarias (IUIBS), Facultad de Veterinaria, Universidad de Las Palmas de Gran Canaria (ULPGC), Campus Universitario de Arucas, Gran Canaria, Spain.
Miguel A Martín-AcebesDepartment of Biotechnology, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Consejo Superior de Investigaciones Científicas (INIA-CSIC), Madrid, Spain.
Juan García-ArriazaDepartment of Molecular and Cellular Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain.ORCID 0000-0002-5167-5724
Juan Fernández-RecioInstituto de Ciencias de la Vid y del Vino (ICVV), CSIC - Universidad de La Rioja - Gobierno de La Rioja, Logroño, Spain.ORCID 0000-0002-3986-7686
Luis A FernándezDepartment of Microbial Biotechnology, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain.ORCID 0000-0001-5920-0638
José M CasasnovasDepartment of Macromolecular Structures, Consejo Superior de Investigaciones Científicas (CNB-CSIC), Madrid, Spain.ORCID 0000-0002-2873-6410
Funding
HORIZON EUROPE Framework Programme 101130574-ALADDINMinisterio de Ciencia, Innovación y Universidades 202020E079Ministerio de Ciencia, Innovación y Universidades 202120E079Ministerio de Ciencia, Innovación y Universidades 202340E181Ministerio de Ciencia, Innovación y Universidades CNS2022-135511Ministerio de Ciencia, Innovación y Universidades PID2020-114481RB-I00Ministerio de Ciencia, Innovación y Universidades PID2022-143215OB-I00Ministerio de Ciencia, Innovación y Universidades PLEC2021-007739NextGenerationEU SGL 2103047NextGenerationEU SGL 2103051NextGenerationEU SGL 2103053
6 · The paper itself
Abstract
To generate antibodies (Abs) against SARS-CoV-2 emerging variants, we integrated multiple tools and engineered molecules with excellent neutralizing breadth and potency. Initially, the screening of an immune library identified a nanobody (Nb), termed Nb4, specific to the receptor-binding domain (RBD) of the Omicron BA.1 variant. A Nb4-derived heavy chain antibody (hcAb4) recognized the spike (S) of the Wuhan, Beta, Delta, Omicron BA.1, and BA.5 SARS-CoV-2 variants. A high-resolution crystal structure of the Nb4 variable (VHH) domain in complex with the SARS-CoV-2 RBD (Wuhan) defined the Nb4 binding mode and interface. The Nb4 VHH domain grasped the RBD and covered most of its outer face, including the core and the receptor-binding motif (RBM), which was consistent with hcAb4 blocking RBD binding to the SARS-CoV-2 receptor. In mouse models, a humanized hcAb4 showed therapeutic potential and prevented the replication of SARS-CoV-2 BA.1 virus in the lungs of the animals.
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.
Integrating immune library probing with structure-based computational design to develop potent neutralizing nanobodies against emerging SARS-CoV-2 variants. · full record | OpenQuestion