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Article

Assessment of Computational Tools for Predicting Supramolecular Synthons

Department of Chemistry, Kansas State University, Manhattan, KS 66506, USA
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Author to whom correspondence should be addressed.
Academic Editors: Catherine Housecroft and Katharina M. Fromm
Received: 25 March 2021 / Revised: 23 April 2021 / Accepted: 25 April 2021 / Published: 3 May 2021
The ability to predict the most likely supramolecular synthons in a crystalline solid is a valuable starting point for subsequently predicting the full crystal structure of a molecule with multiple competing molecular recognition sites. Energy and informatics-based prediction models based on molecular electrostatic potentials (MEPs), hydrogen-bond energies (HBE), hydrogen-bond propensity (HBP), and hydrogen-bond coordination (HBC) were applied to the crystal structures of twelve pyrazole-based molecules. HBE, the most successful method, correctly predicted 100% of the experimentally observed primary intermolecular-interactions, followed by HBP (87.5%), and HBC = MEPs (62.5%). A further HBC analysis suggested a risk of synthon crossover and synthon polymorphism in molecules with multiple binding sites. These easy-to-use models (based on just 2-D chemical structure) can offer a valuable risk assessment of potential formulation challenges. View Full-Text
Keywords: hydrogen-bond propensity; hydrogen-bond coordination; supramolecular synthon; hydrogen-bond energies; Cambridge Structural Database; molecular electrostatic potential; pyrazoles hydrogen-bond propensity; hydrogen-bond coordination; supramolecular synthon; hydrogen-bond energies; Cambridge Structural Database; molecular electrostatic potential; pyrazoles
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MDPI and ACS Style

Sandhu, B.; McLean, A.; Sinha, A.S.; Desper, J.; Aakerӧy, C.B. Assessment of Computational Tools for Predicting Supramolecular Synthons. Chemistry 2021, 3, 612-629. https://0-doi-org.brum.beds.ac.uk/10.3390/chemistry3020043

AMA Style

Sandhu B, McLean A, Sinha AS, Desper J, Aakerӧy CB. Assessment of Computational Tools for Predicting Supramolecular Synthons. Chemistry. 2021; 3(2):612-629. https://0-doi-org.brum.beds.ac.uk/10.3390/chemistry3020043

Chicago/Turabian Style

Sandhu, Bhupinder, Ann McLean, Abhijeet S. Sinha, John Desper, and Christer B. Aakerӧy 2021. "Assessment of Computational Tools for Predicting Supramolecular Synthons" Chemistry 3, no. 2: 612-629. https://0-doi-org.brum.beds.ac.uk/10.3390/chemistry3020043

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