Evidence map›Paper›PMID 20012671›Full record

ArticleJournal of computer-aided molecular design2010

Interactions between anti-ErbB2 antibody A21 and the ErbB2 extracellular domain provide a basis for improving A21 affinity.

Liang Chang, Changhai Zhou, Man Xu, Jing Liu

Abstract read
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In one paragraph

Article in Journal of computer-aided molecular design, 2010. 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
0.4field-weighted citation impact, top 34% 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, 4 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

4 authors at 2 institutions in 1 country.

Liang ChangLab of Cellular and Molecular Immunology, School of Life Sciences, University of Science and Technology of China, 230027 Hefei, People's Republic of China.
Changhai Zhou
Man Xu
Jing Liu
University of Science and Technology of China · CNHefei National Center for Physical Sciences at Nanoscale · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anti-ErbB2 antibodies are well researched for the therapy of ErbB2-overexpressing tumors. The therapeutic potential and efficacy of these antibodies are closely related to their affinities to ErbB2. Previously we reported that an anti-ErbB2 antibody A21 targeting a conformational epitope comprising several loops in ErbB2 extracellular subdomain I and II could inhibit the proliferation of ErbB2-overexpressing cancer cells in vitro and in vivo. Here we found that another structureless and non-conserved loop in subdomain I of ErbB2 extracellular domain (ECD) was important for binding to A21, and then the antigen-contact sites on A21 were determined by site-directed mutation. The loop was constructed by molecular modeling, and a new model of A21-ErbB2 complex was generated by docking using the crystal structure of the scfv A21 and the model of ErbB2 ECD with the loop built. Based on the complex model, computational design for A21 affinity improvement was performed to enhance its affinity to ErbB2. Two mutants with about 1.7-fold improvement in affinity were obtained. Our study provided a rational molecular basis for affinity improvement and mechanism investigation of A21.

Indexed as

Antibody AffinityAmino Acid SequenceAntibodies, MonoclonalEpitopesErb-b2 Receptor Tyrosine KinasesHumansModels, MolecularMolecular Sequence DataNeoplasmsPoint MutationProtein Structure, TertiarySequence AlignmentSingle-Chain AntibodiesAntibodies, MonoclonalEpitopesErb-b2 Receptor Tyrosine Kinasesmonoclonal antibody scFv A21Single-Chain Antibodies

Identifiers

PMID20012671
OpenAlexW2063796843

What OpenQuestion holds

Textmetadata
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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.