Evidence map›Paper›PMID 34267764›Full record

ArticleFrontiers in immunology2021

Stabilization of the SARS-CoV-2 Spike Receptor-Binding Domain Using Deep Mutational Scanning and Structure-Based Design.

Daniel Ellis, Natalie Brunette, Katharine H D Crawford, Alexandra C Walls, Minh N Pham, Chengbo Chen, Karla-Luise Herpoldt, Brooke Fiala, Michael Murphy, Deleah Pettie and 17 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

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  4. Improving the immunogenicity ofFrontiers in immunology · 2026
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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

27 authors.

Daniel EllisInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Natalie BrunetteInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Katharine H D CrawfordBasic Sciences and Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, United States.
Alexandra C WallsDepartment of Biochemistry, University of Washington, Seattle, WA, United States.
Minh N PhamInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Chengbo ChenDepartment of Medicinal Chemistry, University of Washington, Seattle, WA, United States.
Karla-Luise HerpoldtInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Brooke FialaInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Michael MurphyInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Deleah PettieInstitute for Protein Design, University of Washington, Seattle, WA, United States.
John C KraftInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Keara D MaloneBasic Sciences and Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, United States.
Mary Jane NavarroDepartment of Biochemistry, University of Washington, Seattle, WA, United States.
Cassandra OgoharaInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Elizabeth KeplInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Rashmi RavichandranInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Claire SydemanInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Maggie AhlrichsInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Max JohnsonInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Alyssa BlackstoneInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Lauren CarterInstitute for Protein Design, University of Washington, Seattle, WA, United States.
Tyler N StarrBasic Sciences and Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, United States.
Allison J GreaneyBasic Sciences and Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, United States.
Kelly K LeeDepartment of Medicinal Chemistry, University of Washington, Seattle, WA, United States.
David VeeslerDepartment of Biochemistry, University of Washington, Seattle, WA, United States.
Jesse D BloomBasic Sciences and Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, United States.
Neil P KingInstitute for Protein Design, University of Washington, Seattle, WA, United States.

Funding

Unraveling the bat humoral immune response against zoonotic viruses to guide the design of next-generation therapeuticsDP1AI158186 · NIAID · UNIVERSITY OF WASHINGTON · PI VEESLER, DAVID · 2020 to 2024
$5.4M
ChimeraX -- Next Generation Visualization and Analysis Software for Multiscale ModelingR01GM129325 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 2018 to 2025
$5.2M
Viral Pathogenesis Training ProgramT32AI083203 · NIAID · UNIVERSITY OF WASHINGTON · PI BLOOM, JESSE D, LAGUNOFF, MICHAEL · 2009 to 2023
$2.7M
Prospectively characterizing the functional and antigenic effects of mutations to viral entry proteinsR01AI141707 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BLOOM, JESSE D · 2018 to 2022
$2.1M
Complete mapping of the functional and antigenic effects of mutations to Lassa virus glycoproteinF30AI149928 · NIAID · UNIVERSITY OF WASHINGTON · PI CRAWFORD, KATHARINE HOLT DUSENBURY · 2020 to 2021
$91k
NIAID NIH HHS DP1 AI158186NIAID NIH HHS F30 AI149928NIAID NIH HHS R01 AI141707NIAID NIH HHS T32 AI083203NIGMS NIH HHS R01 GM129325
6 · The paper itself

Abstract

The unprecedented global demand for SARS-CoV-2 vaccines has demonstrated the need for highly effective vaccine candidates that are thermostable and amenable to large-scale manufacturing. Nanoparticle immunogens presenting the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein (S) in repetitive arrays are being advanced as second-generation vaccine candidates, as they feature robust manufacturing characteristics and have shown promising immunogenicity in preclinical models. Here, we used previously reported deep mutational scanning (DMS) data to guide the design of stabilized variants of the RBD. The selected mutations fill a cavity in the RBD that has been identified as a linoleic acid binding pocket. Screening of several designs led to the selection of two lead candidates that expressed at higher yields than the wild-type RBD. These stabilized RBDs possess enhanced thermal stability and resistance to aggregation, particularly when incorporated into an icosahedral nanoparticle immunogen that maintained its integrity and antigenicity for 28 days at 35-40°C, while corresponding immunogens displaying the wild-type RBD experienced aggregation and loss of antigenicity. The stabilized immunogens preserved the potent immunogenicity of the original nanoparticle immunogen, which is currently being evaluated in a Phase I/II clinical trial. Our findings may improve the scalability and stability of RBD-based coronavirus vaccines in any format and more generally highlight the utility of comprehensive DMS data in guiding vaccine design.

Indexed as

Immunization ScheduleImmunogenicity, VaccineMutationAnimalsAntibodies, NeutralizingAntibodies, ViralChlorocebus aethiopsCOVID-19COVID-19 VaccinesFemaleHEK293 CellsHumansLinoleic AcidsMiceMice, Inbred BALB CNanoparticlesAntibodies, NeutralizingAntibodies, ViralCOVID-19 VaccinesLinoleic AcidsSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2antigen stabilizationcomputational protein designdeep mutational scanningnanoparticlereceptor-binding domainSARS-CoV-2vaccine

Identifiers

PMID34267764
PMCPMC8276696

What OpenQuestion holds

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LicenceCC BY
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.