# Quantitative analysis of inhibitor‐induced assembly disruption in human UDP‐GlcNAc 2‐epimerase using mass photometry

## TL;DR

This study uses mass photometry to analyze how inhibitors affect the assembly of an enzyme involved in sialic acid biosynthesis, offering insights into drug-target interactions.

## Contribution

The study demonstrates mass photometry's potential for label-free, quantitative analysis of small-molecule inhibitors' effects on protein oligomerization.

## Key findings

- Substrate binding stabilizes tetramer formation of GNE by increasing dimer-dimer affinity 98-fold.
- All inhibitors destabilize GNE tetramers in a concentration-dependent manner with low micromolar IC50 values.
- Molecular docking confirms competitive binding of inhibitors and explains potency trends.

## Abstract

Uridine diphosphate N‐acetylglucosamine (UDP‐GlcNAc) 2‐epimerase (GNE)/N‐acetylmannosamine kinase is the rate‐limiting enzyme in sialic acid biosynthesis and a promising therapeutic target. We applied mass photometry (MP) to investigate GNE oligomerization and its modulation by three small‐molecule inhibitors (C5, C13, and C15). Substrate‐binding (UDP‐GlcNAc) stabilized tetramer formation by increasing dimer–dimer affinity 98‐fold. All inhibitors destabilized tetramers in a concentration‐dependent manner, with IC50 values in the low micromolar range. Using a modified Cheng–Prusoff equation, IC50 values were converted into K
B,app values. Schild analysis and Operational Model of Allosterically Modulated Agonism were applied to estimate an apparent K
B,app value and assess cooperative inhibition effects. Molecular docking confirmed competitive binding for all inhibitors and helped rationalize observed potency trends. While MP has previously been used to study protein assembly, our work demonstrates its applicability for the label‐free, quantitative characterization of small‐molecule inhibitors affecting protein oligomerization. These findings provide a foundation for further mechanistic studies and underscore the potential of MP in drug‐target interaction profiling.