Samenvatting
Metal-organic frameworks (MOFs) have become promising materials for multiple applications due to their controlled dimensionality and tunable properties. The incorporation of chirality into their frameworks opens new strategies for chiral separation, a key technology in the pharmaceutical industry as each enantiomer of a racemic drug must be isolated. Here, we describe the use of a combination of computational modeling and experiments to demonstrate that high-performance liquid chromatography (HPLC) columns packed with TAMOF-1 as the chiral stationary phase are efficient, versatile, robust, and reusable with a wide array of mobile phases (polar and non-polar). As proof of concept, in this article, we report the resolution with TAMOF-1 HPLC columns of nine racemic mixtures with different molecular sizes, geometries, and functional groups. Initial in silico studies allowed us to predict plausible separations in chiral compounds from different families, including terpenes, calcium channel blockers, or P-stereogenic compounds. The experimental data confirmed the validity of the models and the robust performance of TAMOF-1 columns. The added value of in silico screening is an unprecedented achievement in chiral chromatography.
Originele taal-2 | Engels |
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Pagina's (van-tot) | 39594−39605 |
Aantal pagina's | 12 |
Tijdschrift | ACS Applied Materials and Interfaces |
Volume | 15 |
Nummer van het tijdschrift | 33 |
DOI's | |
Status | Gepubliceerd - 23 aug. 2023 |
Bibliografische nota
Funding Information:The authors thank the support from projects PID2021-124796OB-I00 and PID2020-115658GB-I00, funded by MCIN/AEI/10.13039/501100011033/, and the Generalitat de Catalunya (2021 SGR 01107 and 2021-SGR-1154). ICIQ is supported by the Ministerio de Ciencia e Innovación through the Severo Ochoa Excellence Accreditations CEX2019-000925-S (MIC/AEI) and by the CERCA Programme/Generalitat de Catalunya. S.R.G.B. was supported by grant FJC2018-035697-I and project PID2019-105479RB-I00 funded by MCIN/AEI/10.13039/501100011033, and by grant POSTDOC_21_00069 funded by Agencia Andaluza de Conocimiento, Secretaría General de Universidades, Investigación y Tecnología 2021, Junta de Andalucía.
Financiering
The authors thank the support from projects PID2021-124796OB-I00 and PID2020-115658GB-I00, funded by MCIN/AEI/10.13039/501100011033/, and the Generalitat de Catalunya (2021 SGR 01107 and 2021-SGR-1154). ICIQ is supported by the Ministerio de Ciencia e Innovación through the Severo Ochoa Excellence Accreditations CEX2019-000925-S (MIC/AEI) and by the CERCA Programme/Generalitat de Catalunya. S.R.G.B. was supported by grant FJC2018-035697-I and project PID2019-105479RB-I00 funded by MCIN/AEI/10.13039/501100011033, and by grant POSTDOC_21_00069 funded by Agencia Andaluza de Conocimiento, Secretaría General de Universidades, Investigación y Tecnología 2021, Junta de Andalucía.