A Whole Output Strategy for Polymorph Screening:  Combining Crystal Structure Prediction, Graph Set Analysis, and Targeted Crystallization Experiments in the Case of Diflunisal

• Published in: Crystal growth & design Vol. 3; no. 2; pp. 151 - 158
• Main Authors: Cross, Wendy I, Blagden, Nicholas, Davey, Roger J, Pritchard, Robin G, Neumann, Marcus A, Roberts, Ronald J, Rowe, Raymond C
• Format: Journal Article
• Language: English
• Published: Washington,DC American Chemical Society 01-03-2003
• Subjects: Condensed matter: structure, mechanical and thermal properties; Cross-disciplinary physics: materials science; rheology; Crystalline state (including molecular motions in solids); Crystallographic aspects of phase transformations; pressure effects; Exact sciences and technology; Materials science; Methods of crystal growth; physics of crystal growth; Physics; Structure of solids and liquids; crystallography; Theory and models of crystal growth; physics of crystal growth, crystal morphology and orientation; Theory of crystal structure, crystal symmetry; calculations and modeling; Prediction; Theoretical study; Diflunisal; Computerized simulation; Carboxylic acids; Experimental study; Biological activity; Non steroidal antiinflammatory agent; Optimal strategy; Hydrogen bonds; Benzenic compound; Crystal growth from solutions; Fabrication structure relation; Fluorine Organic compounds; Organic compounds; Solvent effects; Polymorphism; Crystal structure
• ISSN: 1528-7483; 1528-7505
• DOI: 10.1021/cg025589n

This paper describes the combined application of crystal structure prediction and targeted experimental crystallization to diflunisal, a fluorinated, aromatic carboxylic acid. Graph set analysis has been used to analyze and classify the structural predictions, and crystallization solvents have been selected to promote the formation of crystals containing the most commonly predicted hydrogen-bonding motifs. Accordingly, four new crystal structures of this material were solved, two solvates and two new polymorphs. This example further highlights both the insight offered by crystal structure prediction software and the limitations of current solution crystallization strategies.