Bioscience Reports最新文献

Human somatic angiotensin-converting enzyme (ACE) is a key zinc metallopeptidase that plays a pivotal role in the renin-angiotensin-aldosterone system (RAAS) by regulating blood pressure and electrolyte balance. Inhibition of ACE is a cornerstone in the management of hypertension, cardiovascular diseases, and renal disorders. Recent advances in structural biology techniques have provided invaluable insights into the molecular mechanisms underlying ACE inhibition, facilitating the design and development of more effective therapeutic agents. This review focuses on the latest advancements in elucidating the structural basis for ACE inhibition. High-resolution crystallographic studies of minimally glycosylated individual domains of ACE have revealed intricate molecular details of the ACE catalytic N- and C-domains, and their detailed interactions with clinically relevant and newly designed domain-specific inhibitors. In addition, the recently elucidated structure of the glycosylated form of full-length ACE by cryo-electron microscopy (cryo-EM) has shed light on the mechanism of ACE dimerization and revealed continuous conformational changes which occur prior to ligand binding. In addition to these experimental techniques, computational approaches have also played a pivotal role in elucidating the structural basis for ACE inhibition. Molecular dynamics simulations and computational docking studies have provided atomic details of inhibitor binding kinetics and energetics, facilitating the rational design of novel ACE inhibitors with improved potency and selectivity. Furthermore, computational analysis of the motions observed by cryo-EM allowed the identification of allosteric binding sites on ACE. This affords new opportunities for the development of next-generation allosteric inhibitors with enhanced pharmacological properties. Overall, the insights highlighted in this review could enable the rational design of novel ACE inhibitors with improved efficacy and safety profiles, ultimately leading to better therapeutic outcomes for patients with hypertension and cardiovascular diseases.

Obesity during pregnancy has been escalating, becoming a huge problem that poses consequences not only for the health of the offspring but also for the maternal well-being. Women's adipose and hepatic tissue metabolism undergoes significant changes during the gestational period. During pregnancy, obesity is a primary instigator of steatosis, increasing the risk of non-alcholic fatty liver disease (NAFLD), now recognized under the updated nomenclature metabolic dysfunction-associated steatotic liver disease (MASLD). Pregnant women with obesity present higher levels of free fatty acids and glucose, reduction in insulin sensitivity, and adipose tissue endocrine dysregulation. Furthermore, obesity-induced modifications in clock genes and lipid-associated gene expression within adipose tissue disrupt crucial metabolic adaptations, potentially culminating in adipose tissue dysfunction. Thus, the liver experiences increased exposure to free fatty acids through the portal vein. Higher uptake of free fatty acids into the liver disrupts hepatic lipid oxidation while enhances lipogenesis, thereby predisposing to ectopic fat deposition within the liver. This review focuses on the obesity-induced changes during pregnancy in both liver and adipose tissue metabolism, elucidating how the metabolic crosstalk between these two organs can be dysregulated in pregnant women living with obesity.

The heterotrimeric eIF2 complex consists of a core eIF2γ subunit to which binds eIF2α and eIF2β subunits and plays an important role in delivering the Met-tRNAiMet to the 40S ribosome and start codon selection. The intricacies of eIF2β-γ interaction in promoting Met-tRNAiMet binding are not clearly understood. Previously, the zinc-binding domain (ZBD) eIF2βS264Y mutation was reported to cause Met-tRNAiMet binding defect due to the intrinsic GTPase activity. We showed that the eIF2βS264Y mutation has eIF2β-γ interaction defect. Consistently, the eIF2βT238A intragenic suppressor mutation restored the eIF2β-γ and Met-tRNAiMet binding. The eIF2β-ZBD residues Asn252Asp and Arg253Ala mutation caused Met-tRNAiMet binding defect that was partially rescued by the eIF2βT238A mutation, suggesting the eIF2β-ZBD modulates Met-tRNAiMet binding. The suppressor mutation rescued the translation initiation fidelity defect of the eIF2γN135D SW-I mutation and eIF2βF217A/Q221A double mutation in the HTH domain. The eIF2βT238A suppressor mutation could not rescue the eIF2β binding defect of the eIF2γV281K mutation; however, combining the eIF2βS264Y mutation with the eIF2γV281K mutation was lethal. In addition to the previously known interaction of eIF2β with the eIF2γ subunit via its α1-helix, the eIF2β-ZBD also interacts with the eIF2γ subunit via guanine nucleotide-binding interface; thus, the eIF2β-γ interacts via two distinct binding sites.

Learning and memory impairment (LMI), a common degenerative central nervous system disease. Recently, more and more studies have shown that Ganoderma lucidum (GL) can improve the symptoms of LMI. The active ingredients in GL and their corresponding targets were screened through TCMSP (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform) and BATMAN-TCM (Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine) databases, and the potential LMI targets were searched for through GeneCard (GeneCards Human Gene Database) and DrugBank. Then, we construct a 'main active ingredient-target' network and a protein-protein interaction (PPI) network diagram.The GO (Gene Ontology) functional enrichment analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway annotation analysis were performed on the common targets through DAVID (Database for Annotation Visualization and Integrated Discovery) to clarify the potential molecular mechanism of action of active ingredients in GL. The tumor necrosis factor (TNF) protein was verified by Western blot; Twenty one active ingredients in GL and 142 corresponding targets were screened out, including 59 targets shared with LMI. The 448 biological processes shown by the GO functional annotation results and 55 signal pathways shown by KEGG enrichment analysis were related to the improvement of LMI by GL, among which the correlation of Alzheimer's disease pathway is the highest, and TNF was the most important protein; TNF can improve LMI. GL can improve LMI mainly by 10 active ingredients in it, and they may play a role by regulating Alzheimer's disease pathway and TNF protein.