ReviewFEBS open bio2025
Structure-based computational design of antibody mimetics: challenges and perspectives.
Review in FEBS open bio, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Integrative Computational Prediction Strategy for Antibody-Antigen Binding: A Case Study on Interleukin-1 Beta.Journal of chemical information and modeling · 2026Article
- Artificial intelligence driven protein design and sustainable nanomedicine for advanced theranostics.Bioactive materials · 2026Review
- Af-CUT&Tag: a sensitive and antibody-free chromatin profiling method using genetically encoded tags and high-affinity binders fused to Tn5.Nature communications · 2026Article
- A step further in our commitment to support early career researchers (ECRs).FEBS open bio · 2026Article
- Artificial intelligence in antibody design and development: harnessing the power of computational approaches.Medical & biological engineering & computing · 2025Review
- Article
- Guidelines in the Preparation of Fully Synthetic, Human Single-Domain Antibody Phage Display Libraries.Antibodies (Basel, Switzerland) · 2025Article
- EvoNB: A protein language model-based workflow for nanobody mutation prediction and optimization.Journal of pharmaceutical analysis · 2025Article
- Estimating Absolute Protein-Protein Binding Free Energies by a Super Learner Model.Journal of chemical information and modeling · 2025Article
- Structural Bioinformatics: exciting times in a rapidly evolving field.FEBS open bio · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The design of antibody mimetics holds great promise for revolutionizing therapeutic interventions by offering alternatives to conventional antibody therapies. Structure-based computational approaches have emerged as indispensable tools in the rational design of those molecules, enabling the precise manipulation of their structural and functional properties. This review covers the main classes of designed antigen-binding motifs, as well as alternative strategies to develop tailored ones. We discuss the intricacies of different computational protein-protein interaction design strategies, showcased by selected successful cases in the literature. Subsequently, we explore the latest advancements in the computational techniques including the integration of machine and deep learning methodologies into the design framework, which has led to an augmented design pipeline. Finally, we verse onto the current challenges that stand in the way between high-throughput computer design of antibody mimetics and experimental realization, offering a forward-looking perspective into the field and the promises it holds to biotechnology.
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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.