ArticlemAbs2016
VH-VL orientation prediction for antibody humanization candidate selection: A case study.
Article in mAbs, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
What it found
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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.
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.
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Who cites it
32 citing papers in PubMed, 41 citations in OpenAlex.
- Article
- Computational design and translational development of TCR-mimic scFv antibodies for peptide-HLA neoantigen targeting.npj drug discovery · 2026Review
- Antibody screening for tumor and immune hotspot targets: The frontier of new methods and technologies.Journal of pharmaceutical analysis · 2026Review
- Data-optimal scaling of paired antibody language models.bioRxiv : the preprint server for biology · 2025Article
- Conserved heavy/light contacts and germline preferences revealed by a large-scale analysis of natively paired human antibody sequences and structural data.Communications biology · 2025Article
- Affinity targeting of therapeutic proteins to the bone surface-local delivery of sclerostin-neutralizing antibody enhances efficacy.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2024Article
- Tetraspanins: structure, dynamics, and principles of partner-protein recognition.Trends in cell biology · 2024Review
- Bispecific antibody shuttles targeting CD98hc mediate efficient and long-lived brain delivery of IgGs.Cell chemical biology · 2024Article
- Structure and Dynamics Guiding Design of Antibody Therapeutics and Vaccines.Antibodies (Basel, Switzerland) · 2023Review
- Defining and Studying B Cell Receptor and TCR Interactions.Journal of immunology (Baltimore, Md. : 1950) · 2023Article
- Insights into the Structural Conformations of the Tau Protein in Different Aggregation Status.Molecules (Basel, Switzerland) · 2023Review
- A universal in silico V(D)J recombination strategy for developing humanized monoclonal antibodies.Journal of nanobiotechnology · 2022Article
- Comparing Antibody Interfaces to Inform Rational Design of New Antibody Formats.Frontiers in molecular biosciences · 2022Article
- High-specificity antibodies and detection methods for quantifying phosphorylated tau from clinical samples.Antibody therapeutics · 2021Review
- Mutation of Framework Residue H71 Results in Different Antibody Paratope States in Solution.Frontiers in immunology · 2021Article
- Structural Basis of Antibody Conformation and Stability Modulation by Framework Somatic Hypermutation.Frontiers in immunology · 2021Article
- Germline-Dependent Antibody Paratope States and Pairing Specific VFrontiers in immunology · 2021Article
- Antibodies exhibit multiple paratope states influencing VCommunications biology · 2020Article
- VProteins · 2020Article
- Machine Learning-Guided Prediction of Antigen-Reactive In Silico Clonotypes Based on Changes in Clonal Abundance through Bio-Panning.Biomolecules · 2020Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antibody humanization describes the procedure of grafting a non-human antibody's complementarity-determining regions, i.e., the variable loop regions that mediate specific interactions with the antigen, onto a β-sheet framework that is representative of the human variable region germline repertoire, thus reducing the number of potentially antigenic epitopes that might trigger an anti-antibody response. The selection criterion for the so-called acceptor frameworks (one for the heavy and one for the light chain variable region) is traditionally based on sequence similarity. Here, we propose a novel approach that selects acceptor frameworks such that the relative orientation of the 2 variable domains in 3D space, and thereby the geometry of the antigen-binding site, is conserved throughout the process of humanization. The methodology relies on a machine learning-based predictor of antibody variable domain orientation that has recently been shown to improve the quality of antibody homology models. Using data from 3 humanization campaigns, we demonstrate that preselecting humanization variants based on the predicted difference in variable domain orientation with regard to the original antibody leads to subsets of variants with a significant improvement in binding affinity.
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Registered trials
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.