ArticleCurrent opinion in biomedical engineering2023
AI Models for Protein Design are Driving Antibody Engineering.
Article in Current opinion in biomedical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed.
- Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics.Bioactive materials · 2026Review
- Protein Design Enters the Artificial Intelligence Era: Foundations, Tools, and Emerging Paradigms.Computational and structural biotechnology journal · 2026Review
- Exploring the Blueprint of Life: The Innovation in Antibody and Protein Design.Combinatorial chemistry & high throughput screening · 2026Article
- Fitness Landscape for Antibodies 2: Benchmarking Reveals That Protein AI Models Cannot Yet Consistently Predict Developability Properties.bioRxiv : the preprint server for biology · 2025Article
- Benchmarking all-atom biomolecular structure prediction with FoldBench.Nature communications · 2025Article
- Artificial intelligence in antibody design and development: harnessing the power of computational approaches.Medical & biological engineering & computing · 2025Review
- What does AlphaFold3 learn about antibody and nanobody docking, and what remains unsolved?mAbs · 2025Article
- Fifty years of monoclonals: the past, present and future of antibody therapeutics.Nature reviews. Immunology · 2025Article
- Applications of Artificial Intelligence in Biotech Drug Discovery and Product Development.MedComm · 2025Review
- Article
- AI-driven antibody design with generative diffusion models: current insights and future directions.Acta pharmacologica Sinica · 2025Review
- ProteinReDiff: Complex-based ligand-binding proteins redesign by equivariant diffusion-based generative models.Structural dynamics (Melville, N.Y.) · 2024Article
- ABodyBuilder3: improved and scalable antibody structure predictions.Bioinformatics (Oxford, England) · 2024Article
- Antibody design using deep learning: from sequence and structure design to affinity maturation.Briefings in bioinformatics · 2024Review
- A survey of generative AI for de novo drug design: new frontiers in molecule and protein generation.Briefings in bioinformatics · 2024Article
- Computational peptide discovery with a genetic programming approach.Journal of computer-aided molecular design · 2024Article
- Next generation of multispecific antibody engineering.Antibody therapeutics · 2024Review
- Stabilization challenges and aggregation in protein-based therapeutics in the pharmaceutical industry.RSC advances · 2023Review
- Computational Peptide Discovery with a Genetic Programming Approach.Research square · 2023Article
- Improving antibody optimization ability of generative adversarial network through large language model.Computational and structural biotechnology journal · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Therapeutic antibody engineering seeks to identify antibody sequences with specific binding to a target and optimized drug-like properties. When guided by deep learning, antibody generation methods can draw on prior knowledge and experimental efforts to improve this process. By leveraging the increasing quantity and quality of predicted structures of antibodies and target antigens, powerful structure-based generative models are emerging. In this review, we tie the advancements in deep learning-based protein structure prediction and design to the study of antibody therapeutics.
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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.