Among materials usually employed for drug delivery, silica plays a key role, particularly in its mesoporous form. Although much research has been performed on the topic of silica drug delivery, the understanding of the interactions occurring between the material surface and drug molecules is still scarce, despite this knowledge is essential for determining the final performance of a drug-delivery system (DDS). Molecular modeling can give a precious insight on this issue, acting as a virtual microscope to study the processes occurring inside the drug carrier. Ab initio simulations, in particular, can accurately predict geometries and enthalpies of adsorption, infrared and nuclear magnetic resonance spectra, and other experimental observables that can help pharmaceutical researchers to better predict the features of novel DDSs.
Ab Initio Modeling of Hydrogen Bond Interaction at Silica Surfaces With Focus on Silica/Drugs Systems / Delle Piane, M.; Corno, M.; Ugliengo, P. - In: Modelling and Simulation in the Science of Micro- and Meso-Porous Materials[s.l] : Elsevier, 2018. - ISBN 9780128050576. - pp. 297-328 [10.1016/B978-0-12-805057-6.00009-0]
Ab Initio Modeling of Hydrogen Bond Interaction at Silica Surfaces With Focus on Silica/Drugs Systems
Delle Piane M.;
2018
Abstract
Among materials usually employed for drug delivery, silica plays a key role, particularly in its mesoporous form. Although much research has been performed on the topic of silica drug delivery, the understanding of the interactions occurring between the material surface and drug molecules is still scarce, despite this knowledge is essential for determining the final performance of a drug-delivery system (DDS). Molecular modeling can give a precious insight on this issue, acting as a virtual microscope to study the processes occurring inside the drug carrier. Ab initio simulations, in particular, can accurately predict geometries and enthalpies of adsorption, infrared and nuclear magnetic resonance spectra, and other experimental observables that can help pharmaceutical researchers to better predict the features of novel DDSs.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2977621