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Record W3215800873 · doi:10.1126/science.abl6251

Structural basis for continued antibody evasion by the SARS-CoV-2 receptor binding domain

2022· article· en· W3215800873 on OpenAlexaff
Katherine Nabel Smith, Sarah A. Clark, Sundaresh Shankar, Junhua Pan, Lars E. Clark, Pan Yang, Adrian Coscia, Lindsay G. A. McKay, Haley Varnum, Vesna Brusic, Nicole V. Tolan, Guohai Zhou, Michaël Desjardins, Sarah E. Turbett, Sanjat Kanjilal, Amy C Sherman, Anand S. Dighe, Regina C. LaRocque, Edward T. Ryan, Casey Tylek, Joël F.G. Cohen-Solal, Anhdao T. Darcy, Davide Tavella, Anca Clabbers, Yao Fan, Anthony Griffiths, Ivan Correia, Jane Seagal, Lindsey R. Baden, Richelle C. Charles, Jonathan Abraham

Bibliographic record

VenueScience · 2022
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesNational Institute of General Medical SciencesCenters for Disease Control and Prevention
KeywordsNeutralizationAntibodyVirologyImmune escapeSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)BiologyReceptorCoronavirus disease 2019 (COVID-19)Neutralizing antibodyGlycan2019-20 coronavirus outbreakMutationImmunologyGeneGeneticsGlycoproteinMedicineImmune system

Abstract

fetched live from OpenAlex

Many studies have examined the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants on neutralizing antibody activity after they have become dominant strains. Here, we evaluate the consequences of further viral evolution. We demonstrate mechanisms through which the SARS-CoV-2 receptor binding domain (RBD) can tolerate large numbers of simultaneous antibody escape mutations and show that pseudotypes containing up to seven mutations, as opposed to the one to three found in previously studied variants of concern, are more resistant to neutralization by therapeutic antibodies and serum from vaccine recipients. We identify an antibody that binds the RBD core to neutralize pseudotypes for all tested variants but show that the RBD can acquire an N-linked glycan to escape neutralization. Our findings portend continued emergence of escape variants as SARS-CoV-2 adapts to humans.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.389
Teacher spread0.336 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations88
Published2022
Admission routes1
Has abstractyes

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