Despite the existence of efficient chemotherapy, tuberculosis remains a leading cause of mortality worldwide. New drugs are urgently needed to reduce the potential impact of the emergence of multidrug-resistant strains of the causative agent Mycobacterium tuberculosis (Mtb). The front-line antibiotic isoniazid (INH), and several other drugs, target the biosynthesis of mycolic acids and especially the Fatty Acid Synthase-II (FAS-II) elongation system. This biosynthetic pathway is essential and specific for mycobacteria and still represents a valuable system for the search of new anti-tuberculous agents. Several data, in the literature, suggest the existence of protein-protein interactions within the FAS-II system. These interactions themselves might serve as targets for a new generation of drugs directed against Mtb. By using an extensive in vivo yeast two-hybrid approach and in vitro co-immunoprecipitation, we have demonstrated the existence of both homotypic and heterotypic interactions between the known components of FAS-II. The condensing enzymes KasA, KasB and mtFabH interact with each other and with the reductases MabA and InhA. Furthermore, we have designed and constructed point mutations of the FAS-II reductase MabA, able to disrupt its homotypic interactions and perturb the interaction pattern of this protein within FAS-II. Finally, we showed by a transdominant genetic approach that these mutants are dominant negative in both non-pathogenic and pathogenic mycobacteria. These data allowed us to draw a dynamic model of the organization of FAS-II. They also represent an important step towards the design of a new generation of anti-tuberculous agents, as being inhibitors of essential protein-protein interactions.
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http://dx.doi.org/10.1111/j.1365-2958.2004.04334.x | DOI Listing |
Biochem Biophys Rep
March 2025
Department of Genetics and Molecular Biology, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Introduction: Gastric cancer (GC) is among the deadliest malignancies globally, characterized by hypoxia-driven pathways that promote cancer progression, including stemness mechanisms facilitating invasion and metastasis. This study aimed to develop a prognostic decision tree using genes implicated in hypoxia and stemness pathways to predict outcomes in GC patients.
Materials And Methods: GC RNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed to compute hypoxia and stemness scores using Gene Set Variation Analysis (GSVA) and the mRNA expression-based stemness index (mRNAsi).
Int J Cardiol Heart Vasc
February 2025
Department of Geriatrics, Peking University Third Hospital, Beijing 100191, PR China.
Background: Ferroptosis is a cell death process that depends on iron and reactive oxygen species. It significantly contributes to cardiovascular diseases. However, its exact role in ischemic cardiomyopathy (ICM) is still unclear.
View Article and Find Full Text PDFEndocr Metab Immune Disord Drug Targets
January 2025
Department of Orthopaedics, Xiaolan People's Hospital of Zhongshan, Zhongshan, Guangdong Province, People's Republic of China.
Background: Panax notoginseng (Burk.) F. H.
View Article and Find Full Text PDFRespir Res
January 2025
Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Background: The emergence of new molecular targeted drugs marks a breakthrough in asthma treatment, particularly for severe cases. Yet, options for moderate-to-severe asthma treatment remain limited, highlighting the urgent need for novel therapeutic drug targets. In this study, we aimed to identify new treatment targets for asthma using the Mendelian randomization method and large-scale genome-wide association data (GWAS).
View Article and Find Full Text PDFJ Transl Med
January 2025
School of Clinical Laboratory Science, Guizhou Medical University, Guiyang, Guizhou, 550000, China.
Background: Human kinesin family member 11 (KIF11) plays a vital role in regulating the cell cycle and is implicated in the tumorigenesis and progression of various cancers, but its role in endometrial cancer (EC) is still unclear. Our current research explored the prognostic value, biological function and targeting strategy of KIF11 in EC through approaches including bioinformatics, machine learning and experimental studies.
Methods: The GSE17025 dataset from the GEO database was analyzed via the limma package to identify differentially expressed genes (DEGs) in EC.
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