Kinetic solubility: experimental and machine-learning modeling perspectives.
Fiche publication
Date publication
décembre 2023
Journal
Molecular informatics
Auteurs
Membres identifiés du Cancéropôle Est :
Dr GALZI Jean-Luc
Tous les auteurs :
Gilles M, Baybekov S, Llompart P, Gizzi P, Galzi JL, Ramos P, Saurel O, Bourban C, Minoletti C, Varnek A
Lien Pubmed
Résumé
[[1]](#ref-0001) Here, we investigate the reproducibility and modelability of kinetic solubility assays. We first analyzed the relationship between kinetic and thermodynamic solubility data, and then examined the consistency of data from different kinetic assays. In this contribution, we report differences between Kinetic aqueous or buffer solubility is important parameter measuring suitability of compounds for high throughput assays in early drug discovery while thermodynamic solubility is reserved for later stages of drug discovery and development. Kinetic solubility is also considered to have low inter-laboratory reproducibility because of its sensitivity to protocol parameters. Presumably, this is why little efforts have been put to build QSPR models for kinetic in comparison to thermodynamic aqueous solubility. kinetic and thermodynamic solubility data that are consistent with those reported by others[[1,2]](#ref-0001) and good agreement between data from different kinetic solubility campaigns in contrast to general expectations. The latter is confirmed by achieving high performing QSPR models trained on merged kinetic solubility datasets. The poor performance of QSPR model trained on thermodynamic solubility when applied to kinetic solubility dataset reinforces the conclusion that kinetic and thermodynamic solubilities do not correlate: one cannot be used as an ersatz for the other. This encourages for building predictive models for kinetic solubility. The kinetic solubility QSPR model developed in this study is freely accessible through the Predictor web service of the Laboratory of Chemoinformatics ([https://chematlas.chimie.unistra.fr/cgi-bin/predictor2.cgi](https://chematlas.chimie.unistra.fr/cgi-bin/predictor2.cgi)).
Mots clés
QSPR, kinetic solubility, thermodynamic solubility
Référence
Mol Inform. 2023 12 27;: