Multiobjective VHH discovery through integrated high-throughput screening and AlphaFold3-guided structural prioritization
Journal article, 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.
Author
Max D. Overath
Technical University of Denmark (DTU)
Suthimon Thumtecho
Technical University of Denmark (DTU)
Faculty of Medicine, Chulalongkorn University
Esperanza Rivera-de-Torre
Technical University of Denmark (DTU)
Melisa Benard-Valle
Technical University of Denmark (DTU)
Darian S. Wolff
Technical University of Denmark (DTU)
Rahmat Grahadi
Brawijaya University
Technical University of Denmark (DTU)
Kasper H. Björnsson
Technical University of Denmark (DTU)
Andreas S.H. Rygaard
Technical University of Denmark (DTU)
Nils Hofmann
Technical University of Denmark (DTU)
Jann Ledergerber
Swiss Federal Institute of Technology in Zürich (ETH)
Technical University of Denmark (DTU)
Anne Ljungars
Technical University of Denmark (DTU)
Andreas H. Laustsen
Technical University of Denmark (DTU)
Simon Olsson
Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI
University of Gothenburg
Thomas J. Fryer
Massachusetts Institute of Technology (MIT)
Timothy P. Jenkins
Technical University of Denmark (DTU)
Science advances
2375-2548 (eISSN)
Vol. 12 40 eaef5325Subject Categories (SSIF 2025)
Infectious Medicine
DOI
10.1126/sciadv.aef5325
PubMed
42814808