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Carboxylesterases 1A (CES1A) is a key enzyme responsible for the hydrolytic metabolism of a great deal of endogenous and exogenous substrates bearing ester- or amide-bond(s). This study aimed to decipher the species difference in CES1A-mediated hydrolytic metabolism by using a newly developed bioluminescence CES1A sensor (termed NLMe) as the probe substrate, while the liver microsomes from six different mammalian species (human, cynomolgus monkey, dog, minipig, rat and mouse) were used as the enzyme sources. Metabolite profiling demonstrated that all tested liver microsomes from various species could catalyze NLMe hydrolysis, but significant difference in hydrolytic rate was observed. Kinetic plots of NLMe hydrolysis in liver microsomes from different species showed that the inherent clearance rates (C) of NLMe in human liver microsomes (HLM), cynomolgus monkey liver microsomes (CyLM), and pig liver microsome (PLM) were comparable, while the C values of NLMe in dog liver microsomes (DLM), mouse liver microsomes (MLM), and rat liver microsomes (RLM) were relatively small. Moreover, chemical inhibition assays showed that NLMe hydrolysis in all tested liver microsomes could be competently inhibited by BNPP (a potent broad-spectrum inhibitor of CES), but CUA (a selective inhibitor of human CES1A) only inhibited NLMe hydrolysis in human liver microsomes and dog liver microsomes. In summary, the species differences in CES1A-catalyzed NLMe hydrolysis were carefully investigated from the views of the similarities in metabolite profile, hydrolytic kinetics and inhibitor response. All these findings provide new insights into the species differences in CES1A-mediated hydrolytic metabolism and suggest that it is necessary for the pharmacologists to choose appropriate animal models to replace humans for evaluating the in vivo effects of CES1A inhibitors.
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http://dx.doi.org/10.1016/j.cbi.2022.110197 | DOI Listing |
Front Vet Sci
August 2025
Guangdong Key Laboratory for Veterinary Drug Development and Safety Evaluation, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Amphenmulin is a novel pleuromutilin derivative with proven excellent antibacterial activity. To investigate its metabolism in animals, ultra-high-performance liquid chromatography coupled with quadrupole/time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS) was employed to analyze and identify metabolites in rats and chickens and using human, rat, pig, chicken and beagle dog liver microsomes. We identified 18 metabolites from liver microsomes and 24 and 17 metabolites for rats and chickens, respectively.
View Article and Find Full Text PDFAnal Methods
September 2025
Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, P.O. Box 2457, Riyadh 11451, Saudi Arabia.
Avapritinib (Ayvakit™) is a highly selective inhibitor of the platelet-derived growth factor receptor alpha (PDGFRA), including D842V mutations. Avapritinib (APB) is authorized in the United States for individuals with metastatic or unresectable gastrointestinal stromal tumors (GISTs). APB is considered the exclusive therapy for adults with indolent systemic mastocytosis.
View Article and Find Full Text PDFBioorg Chem
September 2025
Chemistry Department, Faculty of Science, Menoufia University, Shebin El-Koam 32511, Egypt. Electronic address:
Targeting Cyclin-Dependent Kinase 2 (CDK2) remains a critical strategy in anticancer drug discovery. This study unveils a highly promising series of novel [1,2,4]triazolo[1,5-a]pyrimidine (TP) derivatives, achieved through innovative S/N-glycerolylation and peptide conjugation strategies. We report the rational design, efficient multi-step synthesis (yields up to 85 %), and comprehensive biological and computational evaluation.
View Article and Find Full Text PDFJ Cheminform
September 2025
College of Pharmacy, Chung-Ang University, Seoul, 06974, Republic of Korea.
The metabolic stability of a drug is a crucial determinant of its pharmacokinetic properties, including clearance, half-life, and oral bioavailability. Accurate predictions of metabolic stability can significantly streamline the drug discovery process. In this study, we present MetaboGNN, an advanced model for predicting liver metabolic stability based on Graph Neural Networks (GNNs) and Graph Contrastive Learning (GCL).
View Article and Find Full Text PDFJ Cheminform
September 2025
Korea Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, 34141, Republic of Korea.
The Korea Chemical Bank (KCB) has generated a dataset containing metabolic stability data for approximately 4,000 compounds that have been tested on human and mouse liver microsomes. The first South Korea Data Challenge, named the Jump AI Challenge for Drug Discovery (JUMP AI 2023), was opened using the metabolic stability data of KCB in 2023. The objective of the JUMP AI 2023 was to promote and encourage the development of new drugs using artificial intelligence (AI) technology in South Korea.
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