Analysing binding stoichiometries in NMR titration experiments using Monte Carlo simulation and resampling techniques

12 May 2022, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The application of Monte Carlo simulation and resampling techniques to analyse possible binding stoichiometries in NMR titration experiments is presented. Four simulated NMR titration experiments having complex species with 1:1, 2:1 and 1:2 stoichiometries were each analysed using a 1:1, 2:1/1:1, 1:1/1:2 and a 2:1/1:1/1:2 model as implemented in SupraFit. Each best-fit model was inspected using Monte Carlo simulation (MC), Cross Validation (CV) and a new protocol termed Reduction Analysis (RA). The results of the statistical post-processes were used to calculate characteristic descriptors that are the base of the judgment for both, the models and individual stability constants. The results indicate promising approaches to correctly identify 1:1, 2:1/1:1 and 1:1/1:2 models, however with some limitations in case of the 2:1/1:1/1:2 model. All simulations and post-processing protocols were performed with the newly presented SupraFit.

Keywords

Chemometrics
NMR spectroscopy
Statistical analysis
Supramolecular chemistry
Titration experiment

Supplementary materials

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Additional material to "Analysing binding stoichiometries in NMR titration experiments using Monte Carlo simulation and resampling techniques"
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