ArticleeLife2024
Accurate prediction of CDR-H3 loop structures of antibodies with deep learning.
Article in eLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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
9 citing papers in PubMed.
- Mapping the TNFR2-targeting antibody patent landscape: Insights from macro trends to structural signatures.Human vaccines & immunotherapeutics · 2026Article
- CD98hc-targeted antibody shuttles for central nervous system delivery with broad cross-species reactivity.Nature biomedical engineering · 2026Article
- Cell-Based Immunization Combined with Single-Round Cell Panning Enables Discovery of PSMA-Targeting Nanobodies from Phage Display Libraries.Biomolecules · 2026Article
- Benchmarking antibody modeling tools across structure prediction, docking, and paratope-epitope interface analysis.Bioinformatics advances · 2026Article
- Exploring Experimental and In Silico Approaches for Antibody-Drug Conjugates in Oncology Therapies.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Improving the solubility of single domain antibodies using VH-like hallmark residues.Protein science : a publication of the Protein Society · 2025Article
- Unveiling the new chapter in nanobody engineering: advances in traditional construction and AI-driven optimization.Journal of nanobiotechnology · 2025Review
- An outlook on structural biology after AlphaFold: tools, limits and perspectives.FEBS open bio · 2025Review
- Multimeric protein interaction and complex prediction: Structure, dynamics and function.Computational and structural biotechnology journal · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Accurate prediction of the structurally diverse complementarity determining region heavy chain 3 (CDR-H3) loop structure remains a primary and long-standing challenge for antibody modeling. Here, we present the H3-OPT toolkit for predicting the 3D structures of monoclonal antibodies and nanobodies. H3-OPT combines the strengths of AlphaFold2 with a pre-trained protein language model and provides a 2.24 Å average RMSD
Indexed as
Identifiers
What OpenQuestion holds
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.