ArticleJournal of medicinal chemistry2023
Inclusion of Control Data in Fits to Concentration-Response Curves Improves Estimates of Half-Maximal Concentrations.
Article in Journal of medicinal chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Linking biochemical and cellular efficacy of MERS coronavirus main protease inhibitors.ACS pharmacology & translational science · 2026Article
- Linking biochemical and cellular efficacy of MERS coronavirus main protease inhibitors.bioRxiv : the preprint server for biology · 2026Article
- Enzyme kinetics model for the coronavirus main protease including dimerization and ligand binding.Biophysical journal · 2025Article
- Roles of Individual Human Cytochrome P450 Enzymes in Drug Metabolism.Pharmacological reviews · 2024Review
- Antidiabetic potential of a novel hydroxyphenyl-bi-benzopyran-hexol compound from Cassia fistula as an α-amylase inhibitor: Integrated in silico screening and in vitro validation using a nonlinear regression model.Journal of Ayurveda and integrative medicineArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Concentration-response curves, in which the effect of varying the concentration on the response of an assay is measured, are widely used to evaluate biological effects of chemical compounds. While National Center for Advancing Translational Sciences guidelines specify that readouts should be normalized by the controls, recommended statistical analyses do not explicitly fit to the control data. Here, we introduce a nonlinear regression procedure based on maximum likelihood estimation that determines parameters for the classical Hill equation by fitting the model to both the curve and the control data. Simulations show that the proposed procedure provides more precise parameters compared with previously prescribed practices. Analysis of enzymatic inhibition data from the COVID Moonshot demonstrates that the proposed procedure yields a lower asymptotic standard error for estimated parameters. Benefits are most evident in the analysis of the incomplete curves. We also find that Lenth's outlier detection method appears to determine parameters more precisely.
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