Publication | Closed Access
Virtual Screening Identifies New Cocrystals of Nalidixic Acid
62
Citations
36
References
2014
Year
Crystal StructureBioorganic ChemistryEngineeringOrganic ChemistryChemistryReagentChemical BiologyInorganic MaterialChemical EngineeringAppropriate CcfsStructure ElucidationCalcium AluminateNalidixic AcidMaterials ScienceInorganic ChemistryBiochemistryMost Promising CcfsCrystallographyCrystal Structure DesignBio-orthogonal ChemistryNatural SciencesX-ray Powder Diffraction
Formulation of solids as cocrystals offers an opportunity to modulate physical properties, so identification of cocrystal formers (CCFs) for an active pharmaceutical ingredient is an area of significant interest. Exhaustive experimental screening would be time-consuming, but we have developed a computational method for identifying CCFs that have a high chance of success based on calculated functional group interaction energies. This virtual screening tool has been applied to nalidixic acid cocrystals. Calculations on a library of 310 compounds identified the 44 most promising CCFs for formation of nalidixic acid cocrystals. Six of these compounds were already known to form cocrystals, and experimental work was undertaken on the remaining 38 compounds. X-ray powder diffraction (XRPD) of mixtures obtained from grinding experiments identified seven CCFs that form new solid phases with nalidixic acid. Infrared spectroscopy and differential scanning calorimetry confirm that these new solid phases are different from the pure components. Further structural characterization was not possible for the skatole, 2,4-dihydroxybenzoic acid, and 3,4-dihydroxybenzoic acid cocrystals, but X-ray crystal structures were obtained from single crystals of the 1:1 tert-butylhydroquinone cocrystal and of the 1:1 propyl gallate cocrystal and from the XRPD pattern for the 1:1 2-phenylphenol cocrystal and for the 1:2 indole cocrystal. The results suggest that success rates in cocrystal screening can be significantly improved by application of computational filters to select the most appropriate CCFs for experimental study.
| Year | Citations | |
|---|---|---|
Page 1
Page 1