Merzlikine, Alexei published the artcileDevelopment of machine learning models of β-cyclodextrin and sulfobutylether-β-cyclodextrin complexation free energies, Formula: C11H9I3N2O4, the main research area is machine learning modeling beta cyclodextrin sulfobutylether complexation energy.
A new set of 142 exptl. determined complexation constants between sulfobutylether-β-cyclodextrin and diverse organic guest mols., and 78 observations reported in literature, were used for the development of the QSPR models by the two machine learning regression methods – Cubist and Random Forest. Similar models were built for β-cyclodextrin using the 233-compound dataset available in the literature. These results demonstrate that the machine learning regression methods can successfully describe the complex formation between organic mols. and β-cyclodextrin or sulfobutylether-β-cyclodextrin. In particular, the root mean square errors for the test sets predictions by the best models are low, 1.9 and 2.7 kJ/mol, resp. The developed QSPR models can be used to predict the solubilizing effect of cyclodextrins and to help prioritizing exptl. work in drug discovery.
International Journal of Pharmaceutics published new progress about Complexation. 117-96-4 belongs to class isoquinoline, name is Diatrizoic Acid, and the molecular formula is C11H9I3N2O4, Formula: C11H9I3N2O4.
Referemce:
Isoquinoline – Wikipedia,
Isoquinoline | C9H7N – PubChem