Speaker
Description
Enzyme inhibition analysis is essential in drug development and food processing, necessitating precise estimation of inhibition constants. Traditionally, these constants are estimated through experiments using multiple substrate and inhibitor concentrations, but inconsistencies across studies highlight a need for a more systematic approach to set experimental designs across all types of enzyme inhibition. Here, we address this by analyzing the error landscape of estimations in various experimental designs \cite{jang2025optimizing}. We find that nearly half of the conventional data is dispensable and even introduces bias. Instead, by incorporating the relationship between IC50 and inhibition constants into the fitting process, we find that using a single inhibitor concentration greater than IC50 suffices for precise estimation. This IC50-based optimal approach, which we name 50-BOA, substantially reduces (>75%) the number of experiments required while ensuring precision and accuracy. Additionally, we provide a user-friendly package that implements the 50-BOA.
Bibliography
@article{jang2025optimizing,
title={Optimizing enzyme inhibition analysis: precise estimation with a single inhibitor concentration},
author={Jang, Hyeong Jun and Song, Yun Min and Jeon, Jang Su and Yun, Hwi-yeol and Kim, Sang Kyum and Kim, Jae Kyoung},
journal={Nature Communications},
volume={16},
number={1},
pages={5217},
year={2025},
publisher={Nature Publishing Group UK London}
}
