Evidence map›Paper›PMID 39690439›Full record

ArticlemAbs2025

Analysis of how antigen mutations disrupt antibody binding interactions toward enabling rapid and reliable antibody repurposing.

Sumaiya Islam, Varun M Chauhan, Robert J Pantazes

Abstract read
In one paragraph

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Sumaiya IslamDepartment of Chemical Engineering, Auburn University, Auburn, AL, USA.ORCID 0000-0002-2214-4684
Varun M ChauhanDepartment of Chemical Engineering, Auburn University, Auburn, AL, USA.ORCID 0000-0001-8498-1077
Robert J PantazesDepartment of Chemical Engineering, Auburn University, Auburn, AL, USA.ORCID 0000-0002-0994-007X

Funding

The Development and Experimental Verification of Computational Methods to Design and Predict the Properties of Therapeutic ProteinsR35GM138220 · NIGMS · AUBURN UNIVERSITY AT AUBURN · PI PANTAZES, ROBERT J · 2020 to 2024
$1.7M
National Science Foundation 2027066NIGMS NIH HHS R35 GM138220
6 · The paper itself

Abstract

Antibody repurposing is the process of changing a known antibody so that it binds to a mutated antigen. One of the findings to emerge from the Coronavirus Disease 2019 (COVID-19) pandemic was that it was possible to repurpose neutralizing antibodies for Severe Acute Respiratory Syndrome, a related disease, to work for COVID-19. Thus, antibody repurposing is a possible pathway to prepare for and respond to future pandemics, as well as personalizing cancer therapies. For antibodies to be successfully repurposed, it is necessary to know both how antigen mutations disrupt their binding and how they should be mutated to recover binding, with this work describing an analysis to address the first of these topics. Every possible antigen point mutation in the interface of 246 antibody-protein complexes were analyzed using the Rosetta molecular mechanics force field. The results highlight a number of features of how antigen mutations affect antibody binding, including the effects of mutating critical hotspot residues versus other positions, how many mutations are necessary to be likely to disrupt binding, the prevalence of indirect effects of mutations on binding, and the relative importance of changing attractive versus repulsive energies. These data are expected to be useful in guiding future antibody repurposing experiments.

Indexed as

COVID-19SARS-CoV-2Antibodies, NeutralizingAntibodies, ViralAntigen-Antibody ComplexDrug RepositioningHumansMutationProtein BindingAntibodies, NeutralizingAntibodies, ViralAntigen-Antibody ComplexAntibody repurposingantigen mutationscomputational analysishotspot residuespoint mutations

Identifiers

PMID39690439
PMCPMC11657118

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Registered trials

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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.