001     1040558
005     20260106202632.0
024 7 _ |a 10.1021/acsptsci.4c00740
|2 doi
024 7 _ |a 10.34734/FZJ-2025-01925
|2 datacite_doi
037 _ _ |a FZJ-2025-01925
082 _ _ |a 610
100 1 _ |a Carloni, Paolo
|0 P:(DE-Juel1)145614
|b 0
|e Corresponding author
|u fzj
245 _ _ |a Rational Design of Ligands with Optimized Residence Time
260 _ _ |a Washington, DC
|c 2025
|b ACS Publications
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 1767698582_17995
|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
500 _ _ |a Open access
520 _ _ |a Residence time (RT) refers to the duration that a drug remains bound to its target, affecting its efficacy and pharmacokinetic properties. RTs are key factors in drug design, yet the structure-based design of ligands with desired RTs is still in its infancy. Here, we propose that a combination of cutting-edge molecular dynamics-based methods with classical computer-aided ligand design can help identify ligands that bind not only with high affinity to their target receptors but also with the required residence time to fully exert their beneficial action without causing undesired side effects
536 _ _ |a 5241 - Molecular Information Processing in Cellular Systems (POF4-524)
|0 G:(DE-HGF)POF4-5241
|c POF4-524
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Rossetti, Giulia
|0 P:(DE-Juel1)145921
|b 1
700 1 _ |a Müller, Christa E.
|0 0000-0002-0013-6624
|b 2
773 _ _ |a 10.1021/acsptsci.4c00740
|g Vol. 8, no. 2, p. 613 - 615
|0 PERI:(DE-600)2934670-8
|n 2
|p 613 - 615
|t ACS pharmacology & translational science
|v 8
|y 2025
|x 2575-9108
856 4 _ |u https://juser.fz-juelich.de/record/1040558/files/rational-design-of-ligands-with-optimized-residence-time.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:1040558
|p openaire
|p open_access
|p driver
|p VDB
|p openCost
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)145614
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)145921
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-524
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Molecular and Cellular Information Processing
|9 G:(DE-HGF)POF4-5241
|x 0
914 1 _ |y 2025
915 p c |a APC keys set
|0 PC:(DE-HGF)0000
|2 APC
915 p c |a Helmholtz: American Chemical Society 01/01/2023
|0 PC:(DE-HGF)0122
|2 APC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2024-12-10
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2024-12-10
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2024-12-10
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b ACS PHARMACOL TRANSL : 2022
|d 2024-12-10
915 _ _ |a WoS
|0 StatID:(DE-HGF)0112
|2 StatID
|b Emerging Sources Citation Index
|d 2024-12-10
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2024-12-10
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b ACS PHARMACOL TRANSL : 2022
|d 2024-12-10
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2024-12-10
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2024-12-10
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)INM-9-20140121
|k INM-9
|l Computational Biomedicine
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-9-20140121
980 _ _ |a APC
980 1 _ |a APC
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21