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Tytuł:
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Application of deep generative model for design of Pyrrolo[2,3-d] pyrimidine derivatives as new selective TANK binding kinase 1 (TBK1) inhibitors.
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Autorzy:
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Song S; School of Pharmacy, Jinan University, #855 Xingye Avenue, Guangzhou, 510632, China.
Tang H; Division of Antitumor Pharmacology, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, #555 Zuchongzhi Road, Shanghai, 201203, China; University of Chinese Academy of Sciences, No.19(A) Yuquan Road, Shijingshan District, Beijing, 100049, China.
Ran T; Division of Drug and Vaccine Research, Guangzhou Laboratory, Guangzhou, 510530, China.
Fang F; Division of Antitumor Pharmacology, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, #555 Zuchongzhi Road, Shanghai, 201203, China.
Tong L; Division of Antitumor Pharmacology, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, #555 Zuchongzhi Road, Shanghai, 201203, China.
Chen H; Division of Drug and Vaccine Research, Guangzhou Laboratory, Guangzhou, 510530, China. Electronic address: chen_.
Xie H; Division of Antitumor Pharmacology, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, #555 Zuchongzhi Road, Shanghai, 201203, China; Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Cuiheng New District, Zhongshan City, China. Electronic address: .
Lu X; School of Pharmacy, Jinan University, #855 Xingye Avenue, Guangzhou, 510632, China. Electronic address: .
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Źródło:
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European journal of medicinal chemistry [Eur J Med Chem] 2023 Feb 05; Vol. 247, pp. 115034. Date of Electronic Publication: 2022 Dec 22.
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Publication: Paris : Editions Scientifiques Elsevier
Original Publication: Paris, S.E.C.T. [etc.]
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MeSH Terms:
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Drug Discovery*
Pyrimidines*/pharmacology
Pyrimidines*/chemistry
Humans ; Structure-Activity Relationship ; Protein Kinase Inhibitors/pharmacology ; Protein Kinase Inhibitors/chemistry ; Protein Serine-Threonine Kinases
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Contributed Indexing:
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Keywords: Generative modelling; Structure-activity relationship; SyntaLinker; TBK1 inhibitor; pyrrolo[2,3-d]pyrimidine
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Substance Nomenclature:
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0 (Pyrimidines)
0 (Protein Kinase Inhibitors)
EC 2.7.11.1 (TBK1 protein, human)
EC 2.7.11.1 (Protein Serine-Threonine Kinases)
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Entry Date(s):
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Date Created: 20230105 Date Completed: 20230117 Latest Revision: 20230117
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Update Code:
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20240105
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DOI:
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10.1016/j.ejmech.2022.115034
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PMID:
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36603506
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The deep conditional transformer neural network SyntaLinker was applied to identify compounds with pyrrolo[2,3-d]pyrimidine scaffold as potent selective TBK1 inhibitor. Further medicinal chemistry optimization campaign led to the discovery of the most potent compound 7l, which exhibited strong enzymatic inhibitory activity against TBK1 with an IC 50 value of 22.4 nM 7l had a superior inhibitory activity in human monocytic THP1-Blue cells reporter gene assay than MRT67307. Furthermore, 7l significantly inhibited TBK1 downstream target genes cxcl10 and ifnβ expression in THP1 and RAW264.7 cells induced by poly (I:C) and lipopolysaccharide, respectively. This study suggested that combination of deep conditional transformer neural network SyntaLinker and transfer learning could be a powerful tool for scaffold hopping in drug discovery.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2022. Published by Elsevier Masson SAS.)
