High-Resolution Quantification of Two-Way Nanobody Synergy Using Automated Liquid Handling and Computational Modeling

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Authors: Natasha M. Bourgeois, Satchel Bell, Jean Paul Olivier, Michael P. Rout, John D. Aitchison, Fred David Mast
Cited by: 0
References: 7

Abstract

Evaluating single-domain antibody cooperativity is essential for developing potent, escape-resistant antiviral biologics. Here, we present a protocol that reproducibly quantifies functional synergy between neutralizing nanobody pairs in standardized viral infectivity assays. Controlled automated liquid handling prepares two-dimensional concentration matrices, minimizing pipetting variance and systematic error. Neutralization data are fitted using quantitative models that independently estimate potency, cooperativity, and efficacy to distinguish additive, synergistic, and antagonistic effects between nanobody pairs. Replicated measurements enable statistically interpretable parameter estimates, supporting robust evaluation of combinatorial nanobody therapeutics with commonly available equipment and open-source analysis tools. This framework is broadly applicable to assessing cooperative effects among other classes of binding or inhibitory molecules, facilitating systematic discovery of synergistic combinations. Key features • Understanding functional synergistic effects between antiviral nanobodies advances their rational therapeutic design. • Performing nanobody synergy experiments with an automated liquid handling workflow enables high-throughput and highly reproducible analysis of nanobody cooperativity. • Evaluating a two-dimensional matrix of nanobody concentrations using the MuSyC model provides the resolution needed to understand how one nanobody can be influenced by another. • This protocol integrates experimental, computational, and visualization procedures into a unified framework to identify and characterize synergistic antiviral nanobody combinations.

Fields of Study & Subjects

Monoclonal and Polyclonal Antibodies Research Protein purification and stability SARS-CoV-2 and COVID-19 Research

Publication details

Journal / source
BIO-PROTOCOL
Volume
16
Issue
1392
Pages
e5615–e5615
Publication date
1 January 2026
Language
EN