ArticleNature communications2025
Optimizing enzyme inhibition analysis: precise estimation with a single inhibitor concentration.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- Natural compounds from Fernandoa adenophylla (Wall. ex G.Don) Steenis as beta-secretase 1 and monoamine oxidase-b inhibitors: in vitro and computational evidence.Journal of computer-aided molecular design · 2026Article
- Calorimetry informed visual digital model for continuous flow photobromination.Communications chemistry · 2026Article
- Structure-Activity Relationships of Anabaenopeptins as Carboxypeptidase and Phosphatase Inhibitors.ACS chemical biology · 2026Review
- Structure-Based Insights into Stefin-Mediated Targeting of Fowlerpain-1: Towards Novel Therapeutics forPharmaceuticals (Basel, Switzerland) · 2025Article
- Optimizing enzyme inhibition analysis: precise estimation with a single inhibitor concentration.Nature communications · 2025Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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 IC
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