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Dataset to support : Polymorph identification for flexible molecules: linear regression analysis of experimental and calculated solution- and solid-state NMR data
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Rahman, Mohammed (2023) Dataset to support : Polymorph identification for flexible molecules: linear regression analysis of experimental and calculated solution- and solid-state NMR data. [Dataset]
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Polymorph identification for flexible molecules linear regression analysis of experimental and calculated solution- and solid-state NMR data_dataset.zip - Published Version Available under License Creative Commons Attribution 4.0. Download (98Mb) |
Abstract
The Δδ regression approach of Blade et al. [ J. Phys. Chem. A 2020, 124(43), 8959–8977] for accurately discriminating between solid forms using a combination of experimental solution- and solid-state NMR data with density functional theory (DFT) calculation is here extended to molecules with multiple conformational degrees of freedom, using furosemide polymorphs as an exemplar. As before, the differences in measured 1H and 13C chemical shifts between solution-state NMR and solid-state magic-angle spinning (MAS) NMR (Δδexperimental) are compared to those determined by gauge-including projector augmented wave (GIPAW) calculations (Δδcalculated) by regression analysis and a t-test, allowing the correct furosemide polymorph to be precisely identified. Monte Carlo random sampling is used to calculate solution-state NMR chemical shifts, reducing computation times by avoiding the need to systematically sample the multidimensional conformational landscape that furosemide occupies in solution. The solvent conditions should be chosen to match the molecule’s charge state between the solution and solid states. The Δδ regression approach indicates whether or not correlations between Δδexperimental and Δδcalculated are statistically significant; the approach is differently sensitive to the popular root mean squared error (RMSE) method, being shown to exhibit a much greater dynamic range. An alternative method for estimating solution-state NMR chemical shifts by approximating the measured solution-state dynamic 3D behavior with an ensemble of 54 furosemide crystal structures (polymorphs and cocrystals) from the Cambridge Structural Database (CSD) was also successful in this case, suggesting new avenues for this method that may overcome its current dependency on the prior determination of solution dynamic 3D structures.
Item Type: | Dataset | ||||||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Chemistry | ||||||||||||
Type of Data: | NMR data and castep files used in the study | ||||||||||||
Publisher: | University of Warwick, Department of Chemistry | ||||||||||||
Official Date: | 2 October 2023 | ||||||||||||
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Status: | Not Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Media of Output (format): | .csv, .magres, .txt | ||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||
Date of first compliant deposit: | 28 February 2024 | ||||||||||||
Date of first compliant Open Access: | 28 February 2024 | ||||||||||||
RIOXX Funder/Project Grant: |
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