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Computational predictions of cocrystal formation: A benchmark study of 28 assemblies comparing five methods from high‐throughput to advanced models.

Authors :
Fox, Robert
Klug, Joaquin
Thompson, Damien
Reilly, Anthony
Source :
Journal of Computational Chemistry; 11/5/2024, Vol. 45 Issue 29, p2465-2475, 11p
Publication Year :
2024

Abstract

Cocrystals are assemblies of more than one type of molecule stabilized through noncovalent interactions. They are promising materials for improved drug formulation in which the stability, solubility, or biocompatibility of the active pharmaceutical ingredient (API) is improved by including a coformer. In this work, a range of density functional theory (DFT) and density functional tight binding (DFTB) models are systematically compared for their ability to predict the lattice enthalpy of a broad range of existing pharmaceutically relevant cocrystals. These range from cocrystals containing model compounds 4,4′‐bipyridine and oxalic acid to those with the well benchmarked APIs of aspirin and paracetamol, all tested with a large set of alternative coformers. For simple cocrystals, there is a general consensus in lattice enthalpy calculated by the different DFT models. For the cocrystals with API coformers the cocrystals, enthalpy predictions depend strongly on the DFT model. The significantly lighter DFTB models predict unrealistic values of lattice enthalpy even for simple cocrystals. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01928651
Volume :
45
Issue :
29
Database :
Complementary Index
Journal :
Journal of Computational Chemistry
Publication Type :
Academic Journal
Accession number :
180044426
Full Text :
https://doi.org/10.1002/jcc.27454