Evidence map›Paper›PMID 38495738›Full record

ArticleFrontiers in molecular biosciences2023

Unveiling the affinity-stability relationship in anti-measles virus antibodies: a computational approach for hotspots prediction.

Rimpa Paul, Keisuke Kasahara, Jiei Sasaki, Jorge Fernández Pérez, Ryo Matsunaga, Takao Hashiguchi, Daisuke Kuroda, Kouhei Tsumoto

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in molecular biosciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

8 authors at 2 institutions in 1 country.

Rimpa PaulDepartment of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.
Keisuke KasaharaDepartment of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.
Jiei SasakiInstitute for Life and Medical Sciences, Kyoto University, Sakyo-ku, Kyoto, Japan.
Jorge Fernández PérezDepartment of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.
Ryo MatsunagaDepartment of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.
Takao HashiguchiInstitute for Life and Medical Sciences, Kyoto University, Sakyo-ku, Kyoto, Japan.
Daisuke KurodaDepartment of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.
Kouhei TsumotoDepartment of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.
The University of Tokyo · JPKyoto University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent years have seen an uptick in the use of computational applications in antibody engineering. These tools have enhanced our ability to predict interactions with antigens and immunogenicity, facilitate humanization, and serve other critical functions. However, several studies highlight the concern of potential trade-offs between antibody affinity and stability in antibody engineering. In this study, we analyzed anti-measles virus antibodies as a case study, to examine the relationship between binding affinity and stability, upon identifying the binding hotspots. We leverage

Indexed as

antibody engineeringcomputer-aided designhotspotsmeasles virus hemagglutininmolecular dynamicsrelative hydropathy

Identifiers

PMID38495738
PMCPMC10941800
OpenAlexW4392358752

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.