001     890393
005     20210921141730.0
024 7 _ |a 10.1080/14756366.2021.1876685
|2 doi
024 7 _ |a 1475-6366
|2 ISSN
024 7 _ |a 1475-6374
|2 ISSN
024 7 _ |a 2128/27115
|2 Handle
024 7 _ |a altmetric:99065915
|2 altmetric
024 7 _ |a 33478277
|2 pmid
024 7 _ |a WOS:000609548000001
|2 WOS
037 _ _ |a FZJ-2021-00926
082 _ _ |a 570
100 1 _ |a David, Benoit
|0 P:(DE-HGF)0
|b 0
245 _ _ |a Discovery of new acetylcholinesterase inhibitors for Alzheimer’s disease: virtual screening and in vitro characterisation
260 _ _ |a Abingdon
|c 2021
|b Taylor & Francis Group
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1632146565_22547
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a For more than two decades, the development of potent acetylcholinesterase (AChE) inhibitors has been an ongoing task to treat dementia associated with Alzheimer’s disease and improve the pharmacokinetic properties of existing drugs. In the present study, we used three docking-based virtual screening approaches to screen both ZINC15 and MolPort databases for synthetic analogs of physostigmine and donepezil, two highly potent AChE inhibitors. We characterised the in vitro inhibitory concentration of 11 compounds, ranging from 14 to 985 μM. The most potent of these compounds, S-I 26, showed a fivefold improved inhibitory concentration in comparison to rivastigmine. Moderate inhibitors carrying novel scaffolds were identified and could be improved for the development of new classes of AChE inhibitors.
536 _ _ |a 511 - Enabling Computational- & Data-Intensive Science and Engineering (POF4-511)
|0 G:(DE-HGF)POF4-511
|c POF4-511
|f POF IV
|x 0
536 _ _ |a Forschergruppe Gohlke (hkf7_20200501)
|0 G:(DE-Juel1)hkf7_20200501
|c hkf7_20200501
|f Forschergruppe Gohlke
|x 1
536 _ _ |a 2171 - Biological and environmental resources for sustainable use (POF4-217)
|0 G:(DE-HGF)POF4-2171
|c POF4-217
|f POF IV
|x 2
588 _ _ |a Dataset connected to CrossRef
700 1 _ |a Schneider, Pascal
|0 P:(DE-Juel1)176354
|b 1
700 1 _ |a Schäfer, Philipp
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Pietruszka, Jörg
|0 P:(DE-Juel1)128906
|b 3
|u fzj
700 1 _ |a Gohlke, Holger
|0 P:(DE-Juel1)172663
|b 4
|e Corresponding author
773 _ _ |a 10.1080/14756366.2021.1876685
|g Vol. 36, no. 1, p. 491 - 496
|0 PERI:(DE-600)2049579-1
|n 1
|p 491 - 496
|t Journal of enzyme inhibition and medicinal chemistry
|v 36
|y 2021
|x 1475-6374
856 4 _ |u https://juser.fz-juelich.de/record/890393/files/Discovery%20of%20new%20acetylcholinesterase%20inhibitors%20for%20Alzheimer%20s%20disease%20virtual%20screening%20and%20in%20vitro%20characterisation.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:890393
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)176354
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)128906
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)172663
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|x 0
913 1 _ |a DE-HGF
|b Forschungsbereich Erde und Umwelt
|l Erde im Wandel – Unsere Zukunft nachhaltig gestalten
|1 G:(DE-HGF)POF4-210
|0 G:(DE-HGF)POF4-217
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-200
|4 G:(DE-HGF)POF
|v Für eine nachhaltige Bio-Ökonomie – von Ressourcen zu Produkten
|9 G:(DE-HGF)POF4-2171
|x 1
913 0 _ |a DE-HGF
|b Key Technologies
|l Supercomputing & Big Data
|1 G:(DE-HGF)POF3-510
|0 G:(DE-HGF)POF3-511
|3 G:(DE-HGF)POF3
|2 G:(DE-HGF)POF3-500
|4 G:(DE-HGF)POF
|v Computational Science and Mathematical Methods
|x 0
913 0 _ |a DE-HGF
|b Key Technologies
|l Key Technologies for the Bioeconomy
|1 G:(DE-HGF)POF3-580
|0 G:(DE-HGF)POF3-583
|3 G:(DE-HGF)POF3
|2 G:(DE-HGF)POF3-500
|4 G:(DE-HGF)POF
|v Innovative Synergisms
|x 1
914 1 _ |y 2021
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2020-08-20
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2020-08-20
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1200
|2 StatID
|b Chemical Reactions
|d 2020-08-20
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2020-08-20
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2020-08-20
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2020-08-20
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2020-08-20
|w ger
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2020-08-20
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2020-08-20
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2020-08-20
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2020-08-20
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2020-08-20
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b J ENZYM INHIB MED CH : 2018
|d 2020-08-20
915 _ _ |a Creative Commons Attribution-NonCommercial CC BY-NC 4.0
|0 LIC:(DE-HGF)CCBYNC4
|2 HGFVOC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1210
|2 StatID
|b Index Chemicus
|d 2020-08-20
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2020-08-20
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2020-08-20
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2020-08-20
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2020-08-20
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2020-08-20
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2020-08-20
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0320
|2 StatID
|b PubMed Central
|d 2020-08-20
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)NIC-20090406
|k NIC
|l John von Neumann - Institut für Computing
|x 0
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 1
920 1 _ |0 I:(DE-Juel1)IBI-7-20200312
|k IBI-7
|l Strukturbiochemie
|x 2
920 1 _ |0 I:(DE-Juel1)IBG-1-20101118
|k IBG-1
|l Biotechnologie
|x 3
920 1 _ |0 I:(DE-Juel1)IBOC-20090406
|k IBOC
|l Institut für Bioorganische Chemie (HHUD)
|x 4
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)NIC-20090406
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a I:(DE-Juel1)IBI-7-20200312
980 _ _ |a I:(DE-Juel1)IBG-1-20101118
980 _ _ |a I:(DE-Juel1)IBOC-20090406
980 _ _ |a UNRESTRICTED
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21