ArticleBMC bioinformatics2022
renz: An R package for the analysis of enzyme kinetic data.
Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- D-alanylation of lipoteichoic acids inhibitor provides anti-virulence and anti-resistance effects against methicillin-resistantAntimicrobial agents and chemotherapy · 2025Article
- Effect of Translation-Enhancing Nascent SKIK Peptide on the Arrest Peptides Containing Consecutive Proline.ACS synthetic biology · 2024Article
- Functional Activity of Isoform 2 of Human eRF1.International journal of molecular sciences · 2024Article
- The impact of mRNA poly(A) tail length on eukaryotic translation stages.Nucleic acids research · 2024Article
- Article
- Estimating and Assessing Differential Equation Models with Time-Course Data.The journal of physical chemistry. B · 2023Article
- Analysis of continuous enzyme kinetic data using ICEKAT.Methods in enzymology · 2023Article
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Authors and funding
1 author.
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Abstract
backgroundComplex enzymatic models are required for analyzing kinetic data derived under conditions that may not satisfy the assumptions associated with Michaelis-Menten kinetics. To analyze these data, several software packages have been developed. However, the complexity introduced by these programs is often dispensable when analyzing data conforming to the canonical Michaelis-Menten model. In these cases, the sophisticated routines of these packages become inefficient and unnecessarily intricated for the intended purpose, reason for which most users resort to general-purpose graphing programs. However, this approach, in addition of being time-consuming, is prone to human error, and can lead to misleading estimates of kinetic parameters, particularly when unweighted regression analyses of transformed kinetic data are performed.
resultsTo fill the existing gap between highly specialized and general-purpose software, we have developed an easy-to-use R package, renz, designed for accurate and efficient estimation of enzyme kinetic parameters. The package provides different methods that can be clustered into four categories, depending on whether they are based on data fitting to a single progress curve (evolution of substrate concentration over time) or, alternatively, based on the dependency of initial rates on substrate concentration (differential rate equation). A second criterion to be considered is whether the experimental data need to be manipulated to obtain linear functions or, alternatively, data are directly fitted using non-linear regression analysis. The current program is a cross-platform, free and open-source software that can be obtained from the CRAN repository. The package is accompanied by five vignettes, which are intended to guide users to choose the appropriate method in each case, as well as providing the basic theoretical foundations of each method. These vignettes use real experimental data to illustrate the use of the package utilities.
conclusionsrenz is a rigorous and yet easy-to-use software devoted to the analysis of kinetic data. This application has been designed to meet the needs of users who are not practicing enzymologists, but who need to accurately estimate the kinetic parameters of enzymes. The current software saves time and minimizes the risk of making mistakes or introducing biases due to uncorrected error propagation effects.
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