Evidence map›Paper›PMID 35475123›Full record

ArticleChemical science2021

Computational maturation of a single-domain antibody against Aβ42 aggregation.

Jiacheng Lin, Chiara Figazzolo, Michael A Metrick, Pietro Sormanni, Michele Vendruscolo

Open access · diamondAbstract read
In one paragraph

Article in Chemical science, 2021. 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
0.6field-weighted citation impact, top 33% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  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

5 authors at 1 institution in 1 country.

Jiacheng LinCentre for Misfolding Diseases, Department of Chemistry, University of Cambridge Cambridge CB2 1EW UK ps589@cam.ac.uk mv245@cam.ac.uk.ORCID https://orcid.org/0000-0002-1207-9364
Chiara FigazzoloCentre for Misfolding Diseases, Department of Chemistry, University of Cambridge Cambridge CB2 1EW UK ps589@cam.ac.uk mv245@cam.ac.uk.
Michael A MetrickCentre for Misfolding Diseases, Department of Chemistry, University of Cambridge Cambridge CB2 1EW UK ps589@cam.ac.uk mv245@cam.ac.uk.ORCID https://orcid.org/0000-0002-9998-4630
Pietro SormanniCentre for Misfolding Diseases, Department of Chemistry, University of Cambridge Cambridge CB2 1EW UK ps589@cam.ac.uk mv245@cam.ac.uk.
Michele VendruscoloCentre for Misfolding Diseases, Department of Chemistry, University of Cambridge Cambridge CB2 1EW UK ps589@cam.ac.uk mv245@cam.ac.uk.ORCID https://orcid.org/0000-0002-3616-1610
University of Cambridge · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The expansion of structural databases and the increase in computing power are enabling approaches for antibody discovery based on computational design. It has already been shown that it is possible to use this approach to generate antibodies for specific epitopes on challenging targets. Here we describe an application of this procedure for antibody maturation through the computational design of mutational variants of increased potency. We illustrate this procedure in the case of a single-domain antibody targeting an epitope in the N-terminal region of Aβ42, a peptide whose aggregation is closely associated with Alzheimer's disease. We show that this approach enables the generation of an antibody variant with over 200-fold increased potency against the primary nucleation process in Aβ42 aggregation. Our results thus demonstrate that potentiated antibody variants can be obtained by computational maturation.

Identifiers

PMID35475123
PMCPMC8901120
OpenAlexW3202909743

What OpenQuestion holds

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LicenceCC BY-NC
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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.