Aug 2026· Protein Science· Vol 35· 0 citations· 57 references
Medicine
TL;DR
MAXTIA is presented, a high‐throughput kinetic screening platform that integrates cell‐free protein synthesis with high‐throughput surface plasmon resonance and demonstrates its application to alanine scanning‐based functional epitope mapping, providing a simple and versatile platform for the quantitative analysis of protein–protein interactions.
Abstract
Accurate identification of epitope residues is essential for developing biopharmaceuticals and understanding the mechanisms of immune recognition. However, experimental approaches for residue‐level epitope mapping remain time‐consuming and labor‐intensive, while accurate computational prediction of protein–protein interfaces remains challenging. Here, we present MAXTIA, a high‐throughput kinetic screening platform that integrates cell‐free protein synthesis with high‐throughput surface plasmon resonance and demonstrate its application to alanine scanning‐based functional epitope mapping. This workflow enables the rapid preparation and kinetic characterization of up to 384 protein variants, allowing the identification of functional epitope residues within 3 days while simultaneously providing binding affinity and kinetic parameters (KD, kon, and koff). We applied MAXTIA to map the epitope of the single‐domain antibody (VHH) N1 against the pentraxin domain of neuronal pentraxin‐2 (NP2 PTX). Alanine substitutions that cause substantial affinity losses clustered within a localized region on the AlphaFold3‐predicted NP2 PTX structure, defining a functional epitope site. These residues closely matched the interface observed in the NP2 PTX–VHH N1 crystal structure, validating the accuracy of MAXTIA. Beyond epitope identification, MAXTIA provides a simple and versatile platform for the quantitative analysis of protein–protein interactions, including high‐throughput screening of antibody variants for affinity optimization. This approach should accelerate biopharmaceutical development and facilitate mechanistic studies of molecular recognition.
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MOTIVATION
Antibody-antigen (Ab-Ag) interactions are central to immune recognition and widely exploited in therapeutic design, making accurate structural characterization of these complexes a central challenge in the field. While docking and artificial intelligence-based approaches can generate multiple candidate bindi...
Júlia S. Souza, Aline O. Albuquerque, Diego Almeida et al.· Bioinformatics· 0 citations
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