Evidence map›Paper›PMID 37261904›Full record

ArticleJCI insight2023

Modeling of ACE2 and antibodies bound to SARS-CoV-2 provides insights into infectivity and immune evasion.

Joseph H Lubin, Christopher Markosian, D Balamurugan, Minh T Ma, Chih-Hsiung Chen, Dongfang Liu, Renata Pasqualini, Wadih Arap, Stephen K Burley, Sagar D Khare

Open access · goldAbstract read
In one paragraph

Article in JCI insight, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 1 institution in 2 countries.

Joseph H LubinDepartment of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA.
Christopher MarkosianRutgers Cancer Institute of New Jersey, Newark, New Jersey, USA.
D BalamuruganOffice of Advanced Research Computing, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA.
Minh T MaDepartment of Pathology, Immunology, and Laboratory Medicine.
Chih-Hsiung ChenDepartment of Pathology, Immunology, and Laboratory Medicine.
Dongfang LiuDepartment of Pathology, Immunology, and Laboratory Medicine.
Renata PasqualiniRutgers Cancer Institute of New Jersey, Newark, New Jersey, USA.
Wadih ArapRutgers Cancer Institute of New Jersey, Newark, New Jersey, USA.
Stephen K BurleyDepartment of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA.
Sagar D KhareDepartment of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, New Jersey, USA.
Rutgers, The State University of New Jersey · US

Funding

PDB MANAGEMENT BY THE RESEARCH COLLABORATORY FOR STRUCTURAL BIOINFORMATICSR01GM133198 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI BURLEY, STEPHEN K · 2019 to 2023
$19.3M
The adaptor protein Crk in immune responsesR01AI130197 · NIAID · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI Dongfang Liu · 2018 to 2026
$4.2M
Principles for Designing Stimulus-Responsive EnzymesR01GM132565 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI KHARE, SAGAR D · 2019 to 2022
$1.8M
The adaptor protein Crk in immune responsesR56AI130197 · NIAID · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI LIU, DONGFANG · 2017 to 2023
$874k
Seeing the Unseen: High-Throughput Prospective Profiling and inhibition of SARS-CoV-2 receptor-binding domain variantsR21AI174157 · NIAID · RUTGERS, THE STATE UNIV OF N.J. · PI KHARE, SAGAR D · 2023 to 2024
$425k
CD147-CAR-NK Cells for Hepatocellular Carcinoma TreatmentR21CA267368 · NCI · RUTGERS BIOMEDICAL AND HEALTH SCIENCES · PI LIU, DONGFANG · 2022 to 2023
$391k
NCI NIH HHS R21 CA267368NIAID NIH HHS R01 AI130197NIAID NIH HHS R21 AI174157NIAID NIH HHS R56 AI130197NIGMS NIH HHS R01 GM132565NIGMS NIH HHS R01 GM133198
6 · The paper itself

Abstract

Given the COVID-19 pandemic, there is interest in understanding ligand-receptor features and targeted antibody-binding attributes against emerging SARS-CoV-2 variants. Here, we developed a large-scale structure-based pipeline for analysis of protein-protein interactions regulating SARS-CoV-2 immune evasion. First, we generated computed structural models of the Spike protein of 3 SARS-CoV-2 variants (B.1.1.529, BA.2.12.1, and BA.5) bound either to a native receptor (ACE2) or to a large panel of targeted ligands (n = 282), which included neutralizing or therapeutic monoclonal antibodies. Moreover, by using the Barnes classification, we noted an overall loss of interfacial interactions (with gain of new interactions in certain cases) at the receptor-binding domain (RBD) mediated by substituted residues for neutralizing complexes in classes 1 and 2, whereas less destabilization was observed for classes 3 and 4. Finally, an experimental validation of predicted weakened therapeutic antibody binding was performed in a cell-based assay. Compared with the original Omicron variant (B.1.1.529), derivative variants featured progressive destabilization of antibody-RBD interfaces mediated by a larger set of substituted residues, thereby providing a molecular basis for immune evasion. This approach and findings provide a framework for rapidly and efficiently generating structural models for SARS-CoV-2 variants bound to ligands of mechanistic and therapeutic value.

Indexed as

COVID-19SARS-CoV-2Angiotensin-Converting Enzyme 2Antibodies, MonoclonalHumansImmune EvasionLigandsPandemicsAngiotensin-Converting Enzyme 2Antibodies, MonoclonalLigandsBioinformaticsCOVID-19ImmunoglobulinsStructural biology

Identifiers

PMID37261904
PMCPMC10371346
OpenAlexW4379056128

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.