Multiobjective VHH discovery through integrated high-throughput screening and AlphaFold3-guided structural prioritization
Artikel i vetenskaplig tidskrift, 2026
Finding therapeutic antibodies that bind multiple related targets with high affinity and favorable biophysical properties remains challenging and resource-intensive. For snakebite antivenoms, this challenge is critical as treatments must neutralize toxins across multiple snake species. We developed a pipeline combining high-throughput yeast screening, deep sequencing, and AlphaFold3 structure prediction to identify polyspecific variable domains of heavy chain-only antibodies (VHHs) against long-chain α-neurotoxins. Multiplexed yeast display screening generated a dataset of diverse hits with varying binding specificities. AlphaFold3-generated VHH-toxin complex predictions enabled stringent high-precision structural triage of polyspecific VHHs that bind conserved epitopes across multiple toxins, with a representative subset experimentally confirmed to block toxin binding to the acetylcholine receptor. These structural insights provided a starting point for computational optimization of affinity and soluble expression of the VHHs, with experimental validation confirming that optimized VHH variants maintained broad binding specificity across toxins. This integrated approach supports structure-guided prioritization of polyspecific VHH hits, offering a high-precision filter that could reduce future reliance on extensive experimental specificity screening and providing a framework applicable to other therapeutic contexts, in which substantial antigen variation occurs and broad neutralization is essential.
Författare
Max D. Overath
Danmarks Tekniske Universitet (DTU)
Suthimon Thumtecho
Danmarks Tekniske Universitet (DTU)
Faculty of Medicine, Chulalongkorn University
Esperanza Rivera-de-Torre
Danmarks Tekniske Universitet (DTU)
Melisa Benard-Valle
Danmarks Tekniske Universitet (DTU)
Darian S. Wolff
Danmarks Tekniske Universitet (DTU)
Rahmat Grahadi
Brawijaya University
Danmarks Tekniske Universitet (DTU)
Kasper H. Björnsson
Danmarks Tekniske Universitet (DTU)
Andreas S.H. Rygaard
Danmarks Tekniske Universitet (DTU)
Nils Hofmann
Danmarks Tekniske Universitet (DTU)
Jann Ledergerber
Eidgenössische Technische Hochschule Zürich (ETH)
Danmarks Tekniske Universitet (DTU)
Anne Ljungars
Danmarks Tekniske Universitet (DTU)
Andreas H. Laustsen
Danmarks Tekniske Universitet (DTU)
Simon Olsson
Chalmers, Data- och informationsteknik, Data Science och AI
Göteborgs universitet
Thomas J. Fryer
Massachusetts Institute of Technology (MIT)
Timothy P. Jenkins
Danmarks Tekniske Universitet (DTU)
Science advances
2375-2548 (eISSN)
Vol. 12 40 eaef5325Ämneskategorier (SSIF 2025)
Infektionsmedicin
DOI
10.1126/sciadv.aef5325
PubMed
42814808