Optimizing enzyme inhibition analysis: precise estimation with a single inhibitor concentration

Hyeong Jun Jang, Yun Min Song, Jang Su Jeon, Hwi-yeol Yun, Sang Kyum Kim, Jae Kyoung Kim

Abstract: 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. 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. In this work the authors present an alternative method for accurate and precise estimation of enzyme inhibition constants from a single inhibitor concentration, enhancing efficiency, reducing bias, and supporting broad applications in drug development and safety testing.

External IDs:doi:10.1038/s41467-025-60468-z