ArticlemAbs2015
Antibody humanization by structure-based computational protein design.
Article in mAbs, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
42 citing papers in PubMed, 86 citations in OpenAlex.
- Antibody screening for tumor and immune hotspot targets: The frontier of new methods and technologies.Journal of pharmaceutical analysis · 2026Review
- HuAbDiffusion: a discrete language diffusion model used for antibody humanization.Briefings in bioinformatics · 2025Article
- Advances in Techniques for the Structure and Functional Optimization of Therapeutic Monoclonal Antibodies.Biomedicines · 2025Review
- A humanized antibody against mucormycosis targets angioinvasion and augments the host immune response.Science translational medicine · 2025Article
- 50 Years of Antibody Numbering Schemes: A Statistical and Structural Evaluation Reveals Key Differences and Limitations.Antibodies (Basel, Switzerland) · 2024Article
- A humanized neutralizing antibody protects against human adenovirus type 7 infection in humanized desmoglein-2 and CD46 double-receptor transgenic mice.Virology journal · 2024Article
- Monoclonal antibodies: From magic bullet to precision weapon.Molecular biomedicine · 2024Review
- Humanization of Pan-HLA-DR mAb 44H10 Hinges on Critical Residues in the Antibody Framework.Antibodies (Basel, Switzerland) · 2024Article
- Article
- The rise of big data: deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design.Journal of biomedical science · 2024Review
- Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody-Antigen Interactions.Bioengineering (Basel, Switzerland) · 2024Review
- Computational optimization of antibody humanness and stability by systematic energy-based ranking.Nature biomedical engineering · 2024Article
- Prospects for the computational humanization of antibodies and nanobodies.Frontiers in immunology · 2024Review
- How can we discover developable antibody-based biotherapeutics?Frontiers in molecular biosciences · 2023Review
- Analytical Method for Experimental Validation of Computer-Designed Antibody.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space.Nature communications · 2022Article
- Engineering a natural ligand-based CAR: directed evolution of the stress-receptor NKp30.Cancer immunology, immunotherapy : CII · 2022Article
- A Novel Humanized Anti-Abrin A Chain Antibody Inhibits Abrin ToxicityFrontiers in immunology · 2022Article
- Redesigning an antibody H3 loop by virtual screening of a small library of human germline-derived sequences.Scientific reports · 2021Article
- Deimmunization of protein therapeutics - Recent advances in experimental and computational epitope prediction and deletion.Computational and structural biotechnology journal · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Antibodies derived from non-human sources must be modified for therapeutic use so as to mitigate undesirable immune responses. While complementarity-determining region (CDR) grafting-based humanization techniques have been successfully applied in many cases, it remains challenging to maintain the desired stability and antigen binding affinity upon grafting. We developed an alternative humanization approach called CoDAH ("Computationally-Driven Antibody Humanization") in which computational protein design methods directly select sets of amino acids to incorporate from human germline sequences to increase humanness while maintaining structural stability. Retrospective studies show that CoDAH is able to identify variants deemed beneficial according to both humanness and structural stability criteria, even for targets lacking crystal structures. Prospective application to TZ47, a murine anti-human B7H6 antibody, demonstrates the approach. Four diverse humanized variants were designed, and all possible unique VH/VL combinations were produced as full-length IgG1 antibodies. Soluble and cell surface expressed antigen binding assays showed that 75% (6 of 8) of the computationally designed VH/VL variants were successfully expressed and competed with the murine TZ47 for binding to B7H6 antigen. Furthermore, 4 of the 6 bound with an estimated KD within an order of magnitude of the original TZ47 antibody. In contrast, a traditional CDR-grafted variant could not be expressed. These results suggest that the computational protein design approach described here can be used to efficiently generate functional humanized antibodies and provide humanized templates for further affinity maturation.
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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.