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Quinuclidine-Based Carbamates as Potential CNS Active Compounds

The treatment of central nervous system (CNS) diseases related to the decrease of neurotransmitter acetylcholine in neurons is based on compounds that prevent or disrupt the action of acetylcholinesterase and butyrylcholinesterase. A series of thirteen quinuclidine carbamates were designed using qui...

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Autores principales: Matošević, Ana, Radman Kastelic, Andreja, Mikelić, Ana, Zandona, Antonio, Katalinić, Maja, Primožič, Ines, Bosak, Anita, Hrenar, Tomica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003920/
https://www.ncbi.nlm.nih.gov/pubmed/33804719
http://dx.doi.org/10.3390/pharmaceutics13030420
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author Matošević, Ana
Radman Kastelic, Andreja
Mikelić, Ana
Zandona, Antonio
Katalinić, Maja
Primožič, Ines
Bosak, Anita
Hrenar, Tomica
author_facet Matošević, Ana
Radman Kastelic, Andreja
Mikelić, Ana
Zandona, Antonio
Katalinić, Maja
Primožič, Ines
Bosak, Anita
Hrenar, Tomica
author_sort Matošević, Ana
collection PubMed
description The treatment of central nervous system (CNS) diseases related to the decrease of neurotransmitter acetylcholine in neurons is based on compounds that prevent or disrupt the action of acetylcholinesterase and butyrylcholinesterase. A series of thirteen quinuclidine carbamates were designed using quinuclidine as the structural base and a carbamate group to ensure the covalent binding to the cholinesterase, which were synthesized and tested as potential human acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitors. The synthesized compounds differed in the substituents on the amino and carbamoyl parts of the molecule. All of the prepared carbamates displayed a time-dependent inhibition with overall inhibition rate constants in the 10(3) M(−1) min(−1) range. None of the compounds showed pronounced selectivity for any of the cholinesterases. The in silico determined ability of compounds to cross the blood–brain barrier (BBB) revealed that six compounds should be able to pass the BBB by passive transport. In addition, the compounds did not show toxicity toward cells that represented the main models of individual organs. By machine learning, the most optimal regression models for the prediction of bioactivity were established and validated. Models for AChE and BChE described 89 and 90% of the total variations among the data, respectively. These models facilitated the prediction and design of new and more potent inhibitors. Altogether, our study confirmed that quinuclidinium carbamates are promising candidates for further development as CNS-active drugs, particularly for Alzheimer’s disease treatment.
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spelling pubmed-80039202021-03-28 Quinuclidine-Based Carbamates as Potential CNS Active Compounds Matošević, Ana Radman Kastelic, Andreja Mikelić, Ana Zandona, Antonio Katalinić, Maja Primožič, Ines Bosak, Anita Hrenar, Tomica Pharmaceutics Article The treatment of central nervous system (CNS) diseases related to the decrease of neurotransmitter acetylcholine in neurons is based on compounds that prevent or disrupt the action of acetylcholinesterase and butyrylcholinesterase. A series of thirteen quinuclidine carbamates were designed using quinuclidine as the structural base and a carbamate group to ensure the covalent binding to the cholinesterase, which were synthesized and tested as potential human acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitors. The synthesized compounds differed in the substituents on the amino and carbamoyl parts of the molecule. All of the prepared carbamates displayed a time-dependent inhibition with overall inhibition rate constants in the 10(3) M(−1) min(−1) range. None of the compounds showed pronounced selectivity for any of the cholinesterases. The in silico determined ability of compounds to cross the blood–brain barrier (BBB) revealed that six compounds should be able to pass the BBB by passive transport. In addition, the compounds did not show toxicity toward cells that represented the main models of individual organs. By machine learning, the most optimal regression models for the prediction of bioactivity were established and validated. Models for AChE and BChE described 89 and 90% of the total variations among the data, respectively. These models facilitated the prediction and design of new and more potent inhibitors. Altogether, our study confirmed that quinuclidinium carbamates are promising candidates for further development as CNS-active drugs, particularly for Alzheimer’s disease treatment. MDPI 2021-03-20 /pmc/articles/PMC8003920/ /pubmed/33804719 http://dx.doi.org/10.3390/pharmaceutics13030420 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Matošević, Ana
Radman Kastelic, Andreja
Mikelić, Ana
Zandona, Antonio
Katalinić, Maja
Primožič, Ines
Bosak, Anita
Hrenar, Tomica
Quinuclidine-Based Carbamates as Potential CNS Active Compounds
title Quinuclidine-Based Carbamates as Potential CNS Active Compounds
title_full Quinuclidine-Based Carbamates as Potential CNS Active Compounds
title_fullStr Quinuclidine-Based Carbamates as Potential CNS Active Compounds
title_full_unstemmed Quinuclidine-Based Carbamates as Potential CNS Active Compounds
title_short Quinuclidine-Based Carbamates as Potential CNS Active Compounds
title_sort quinuclidine-based carbamates as potential cns active compounds
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8003920/
https://www.ncbi.nlm.nih.gov/pubmed/33804719
http://dx.doi.org/10.3390/pharmaceutics13030420
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