Evidence map›Paper›PMID 38898362›Full record

ReviewFEBS open bio2025

Nanobody engineering: computational modelling and design for biomedical and therapeutic applications.

Nehad S El Salamouni, Jordan H Cater, Lisanne M Spenkelink, Haibo Yu

Abstract readReview
In one paragraph

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 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. AVIDbase: A biologically accurate structural dataset of nanobody-antigen complexes.Protein science : a publication of the Protein Society · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Nehad S El SalamouniMolecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Australia.ORCID https://orcid.org/0000-0001-6856-6332
Jordan H CaterMolecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Australia.
Lisanne M SpenkelinkMolecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Australia.
Haibo YuMolecular Horizons and School of Chemistry and Molecular Bioscience, University of Wollongong, Australia.ORCID https://orcid.org/0000-0002-1099-2803

Funding

ARC Centre of Excellence in Quantum Biotechnology CE230100021National Health and Medical Research Council (NHMRC) 2007778
6 · The paper itself

Abstract

Nanobodies, the smallest functional antibody fragment derived from camelid heavy-chain-only antibodies, have emerged as powerful tools for diverse biomedical applications. In this comprehensive review, we discuss the structural characteristics, functional properties, and computational approaches driving the design and optimisation of synthetic nanobodies. We explore their unique antigen-binding domains, highlighting the critical role of complementarity-determining regions in target recognition and specificity. This review further underscores the advantages of nanobodies over conventional antibodies from a biosynthesis perspective, including their small size, stability, and solubility, which make them ideal candidates for economical antigen capture in diagnostics, therapeutics, and biosensing. We discuss the recent advancements in computational methods for nanobody modelling, epitope prediction, and affinity maturation, shedding light on their intricate antigen-binding mechanisms and conformational dynamics. Finally, we examine a direct example of how computational design strategies were implemented for improving a nanobody-based immunosensor, known as a Quenchbody. Through combining experimental findings and computational insights, this review elucidates the transformative impact of nanobodies in biotechnology and biomedical research, offering a roadmap for future advancements and applications in healthcare and diagnostics.

Indexed as

Protein EngineeringSingle-Domain AntibodiesAnimalsBiosensing TechniquesHumansSingle-Domain Antibodiesartificial intelligencemachine learningmolecular dynamics simulationsnanobodyquenchbodystructure prediction

Identifiers

PMID38898362
PMCPMC11788755

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.