Evidence map›Paper›PMID 35573973›Full record

ArticleVirus evolution2022

An antibody-escape estimator for mutations to the SARS-CoV-2 receptor-binding domain.

Allison J Greaney, Tyler N Starr, Jesse D Bloom

Open access · goldAbstract read
In one paragraph

Article in Virus evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed
18.5field-weighted citation impact, top 1% of its field
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

114 citing papers in PubMed, 167 citations in OpenAlex.

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  6. Constrained evolutionary funnels shape viral immune escape.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  20. Constrained Evolutionary Funnels Shape Viral Immune Escape.bioRxiv : the preprint server for biology · 2025
    Article

54 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Allison J GreaneyDepartment of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA, USA.
Tyler N StarrBasic Sciences and Computational Biology, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA, USA.
Jesse D BloomBasic Sciences and Computational Biology, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA, USA.ORCID https://orcid.org/0000-0003-1267-3408
Howard Hughes Medical Institute · USUniversity of Washington · US

Funding

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
NIAID NIH HHS R01 AI141707
6 · The paper itself

Abstract

A key goal of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surveillance is to rapidly identify viral variants with mutations that reduce neutralization by polyclonal antibodies elicited by vaccination or infection. Unfortunately, direct experimental characterization of new viral variants lags their sequence-based identification. Here we help address this challenge by aggregating deep mutational scanning data into an 'escape estimator' that estimates the antigenic effects of arbitrary combinations of mutations to the virus's spike receptor-binding domain. The estimator can be used to intuitively visualize how mutations impact polyclonal antibody recognition and score the expected antigenic effect of combinations of mutations. These scores correlate with neutralization assays performed on SARS-CoV-2 variants and emphasize the ominous antigenic properties of the recently described Omicron variant. An interactive version of the estimator is at https://jbloomlab.github.io/SARS2_RBD_Ab_escape_maps/escape-calc/ (last accessed 11 March 2022), and we provide a Python module for batch processing. Currently the calculator uses primarily data for antibodies elicited by Wuhan-Hu-1-like vaccination or infection and so is expected to work best for calculating escape from such immunity for mutations relative to early SARS-CoV-2 strains.

Indexed as

antibody escapedeep mutational scanningepitopeOmicronSARS-CoV-2 variants

Identifiers

PMID35573973
PMCPMC9092643
OpenAlexW4226443473

What OpenQuestion holds

Textmetadata
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.