| 1. |
- Battisti, Umberto Maria, et al.
(författare)
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Ellagic Acid and Its Metabolites as Potent and Selective Allosteric Inhibitors of Liver Pyruvate Kinase
- 2023
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Ingår i: Nutrients. - : MDPI AG. - 2072-6643. ; 15:3
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Tidskriftsartikel (refereegranskat)abstract
- Liver pyruvate kinase (PKL) has recently emerged as a new target for non-alcoholic fatty liver disease (NAFLD), and inhibitors of this enzyme could represent a new therapeutic option. However, this breakthrough is complicated by selectivity issues since pyruvate kinase exists in four different isoforms. In this work, we report that ellagic acid (EA) and its derivatives, present in numerous fruits and vegetables, can inhibit PKL potently and selectively. Several polyphenolic analogues of EA were synthesized and tested to identify the chemical features responsible for the desired activity. Molecular modelling studies suggested that this inhibition is related to the stabilization of the PKL inactive state. This unique inhibition mechanism could potentially herald the development of new therapeutics for NAFLD.
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| 2. |
- Battisti, Umberto Maria, et al.
(författare)
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Exploration of Novel Urolithin C Derivatives as Non-Competitive Inhibitors of Liver Pyruvate Kinase
- 2023
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Ingår i: Pharmaceuticals. - : MDPI AG. - 1424-8247. ; 16:5
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Tidskriftsartikel (refereegranskat)abstract
- The inhibition of liver pyruvate kinase could be beneficial to halt or reverse non-alcoholic fatty liver disease (NAFLD), a progressive accumulation of fat in the liver that can lead eventually to cirrhosis. Recently, urolithin C has been reported as a new scaffold for the development of allosteric inhibitors of liver pyruvate kinase (PKL). In this work, a comprehensive structure-activity analysis of urolithin C was carried out. More than 50 analogues were synthesized and tested regarding the chemical features responsible for the desired activity. These data could pave the way to the development of more potent and selective PKL allosteric inhibitors.
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| 3. |
- Battisti, U. M., et al.
(författare)
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Serendipitous Identification of a Covalent Activator of Liver Pyruvate Kinase
- 2023
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Ingår i: ChemBioChem. - : Wiley. - 1439-4227 .- 1439-7633. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- Enzymes are effective biological catalysts that accelerate almost all metabolic reactions in living organisms. Synthetic modulators of enzymes are useful tools for the study of enzymatic reactions and can provide starting points for the design of new drugs. Here, we report on the discovery of a class of biologically active compounds that covalently modifies lysine residues in human liver pyruvate kinase (PKL), leading to allosteric activation of the enzyme (EC50=0.29 μM). Surprisingly, the allosteric activation control point resides on the lysine residue K282 present in the catalytic site of PKL. These findings were confirmed by structural data, MS/MS experiments, and molecular modelling studies. Altogether, our study provides a molecular basis for the activation mechanism and establishes a framework for further development of human liver pyruvate kinase covalent activators.
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| 4. |
- Bayraktar, Abdulahad, et al.
(författare)
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Drug repositioning targeting glutaminase reveals drug candidates for the treatment of Alzheimer's disease patients
- 2023
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Ingår i: Journal of Translational Medicine. - : BMC. - 1479-5876. ; 21:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundDespite numerous clinical trials and decades of endeavour, there is still no effective cure for Alzheimer's disease. Computational drug repositioning approaches may be employed for the development of new treatment strategies for Alzheimer's patients since an extensive amount of omics data has been generated during pre-clinical and clinical studies. However, targeting the most critical pathophysiological mechanisms and determining drugs with proper pharmacodynamics and good efficacy are equally crucial in drug repurposing and often imbalanced in Alzheimer's studies.MethodsHere, we investigated central co-expressed genes upregulated in Alzheimer's disease to determine a proper therapeutic target. We backed our reasoning by checking the target gene's estimated non-essentiality for survival in multiple human tissues. We screened transcriptome profiles of various human cell lines perturbed by drug induction (for 6798 compounds) and gene knockout using data available in the Connectivity Map database. Then, we applied a profile-based drug repositioning approach to discover drugs targeting the target gene based on the correlations between these transcriptome profiles. We evaluated the bioavailability, functional enrichment profiles and drug-protein interactions of these repurposed agents and evidenced their cellular viability and efficacy in glial cell culture by experimental assays and Western blotting. Finally, we evaluated their pharmacokinetics to anticipate to which degree their efficacy can be improved.ResultsWe identified glutaminase as a promising drug target. Glutaminase overexpression may fuel the glutamate excitotoxicity in neurons, leading to mitochondrial dysfunction and other neurodegeneration hallmark processes. The computational drug repurposing revealed eight drugs: mitoxantrone, bortezomib, parbendazole, crizotinib, withaferin-a, SA-25547 and two unstudied compounds. We demonstrated that the proposed drugs could effectively suppress glutaminase and reduce glutamate production in the diseased brain through multiple neurodegeneration-associated mechanisms, including cytoskeleton and proteostasis. We also estimated the human blood-brain barrier permeability of parbendazole and SA-25547 using the SwissADME tool.ConclusionsThis study method effectively identified an Alzheimer's disease marker and compounds targeting the marker and interconnected biological processes by use of multiple computational approaches. Our results highlight the importance of synaptic glutamate signalling in Alzheimer's disease progression. We suggest repurposable drugs (like parbendazole) with well-evidenced activities that we linked to glutamate synthesis hereby and novel molecules (SA-25547) with estimated mechanisms for the treatment of Alzheimer's patients.
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| 5. |
- Graves, Occam Kelly, et al.
(författare)
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Discovery of drug targets and therapeutic agents based on drug repositioning to treat lung adenocarcinoma
- 2023
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Ingår i: Biomedicine and Pharmacotherapy. - : Elsevier BV. - 0753-3322 .- 1950-6007. ; 161
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Tidskriftsartikel (refereegranskat)abstract
- Background: Lung adenocarcinoma (LUAD) is the one of the most common subtypes in lung cancer. Although various targeted therapies have been used in the clinical practice, the 5-year overall survival rate of patients is still low. Thus, it is urgent to identify new therapeutic targets and develop new drugs for the treatment of the LUAD patients. Methods: Survival analysis was used to identify the prognostic genes. Gene co-expression network analysis was used to identify the hub genes driving the tumor development. A profile-based drug repositioning approach was used to repurpose the potentially useful drugs for targeting the hub genes. MTT and LDH assay were used to measure the cell viability and drug cytotoxicity, respectively. Western blot was used to detect the expression of the proteins. Findings: We identified 341 consistent prognostic genes from two independent LUAD cohorts, whose high expression was associated with poor survival outcomes of patients. Among them, eight genes were identified as hub genes due to their high centrality in the key functional modules in the gene-co-expression network analysis and these genes were associated with the various hallmarks of cancer (e.g., DNA replication and cell cycle). We performed drug repositioning analysis for three of the eight genes (CDCA8, MCM6, and TTK) based on our drug repositioning approach. Finally, we repurposed five drugs for inhibiting the protein expression level of each target gene and validated the drug efficacy by performing in vitro experiments. Interpretation: We found the consensus targetable genes for the treatment of LUAD patients with different races and geographic characteristics. We also proved the feasibility of our drug repositioning approach for the development of new drugs for disease treatment.
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| 6. |
- Kim, Woonghee, et al.
(författare)
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Characterization of an in vitro steatosis model simulating activated de novo lipogenesis in MAFLD patients
- 2023
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Ingår i: iScience. - : Elsevier BV. - 2589-0042. ; 26:10
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Tidskriftsartikel (refereegranskat)abstract
- Activated de novo lipogenesis (DNL) is the critical pathway involved in the progression of metabolic-associated fatty liver disease (MAFLD). We present an in vitro steatosis model for MAFLD that induces steatosis through activated DNL. This model utilizes insulin and LXR receptor ligand T0901317, eliminating the need for fatty acid treatment. Significant increases in triglycerides (TAGs) and expression of DNL-related transcription factors were observed. Transcriptomic analysis revealed distinct gene expression profiles between the DNL and conventional oleic acid (OA)-induced steatosis model. DNL steatosis model exhibited elevated pathways related to glycolysis, cholesterol homeostasis, and bile acid metabolism, reflecting its clinical relevance to MAFLD. Moreover, C75 and JNK-IN-5A compounds effectively reduced TAG accumulation and steatosis-related protein expression in the DNL model, whereas they had no significant impact on TAG accumulation in the OA model. In conclusion, we introduce an ideal model for steatosis study, which could help in understanding the MAFLD mechanisms.
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| 7. |
- Liao, Xinmeng, et al.
(författare)
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Open MoA : revealing the mechanism of action (MoA) based on network topology and hierarchy
- 2023
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Ingår i: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 39:11
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Tidskriftsartikel (refereegranskat)abstract
- MOTIVATION: Many approaches in systems biology have been applied in drug repositioning due to the increased availability of the omics data and computational biology tools. Using a multi-omics integrated network, which contains information of various biological interactions, could offer a more comprehensive inspective and interpretation for the drug mechanism of action (MoA). RESULTS: We developed a computational pipeline for dissecting the hidden MoAs of drugs (Open MoA). Our pipeline computes confidence scores to edges that represent connections between genes/proteins in the integrated network. The interactions showing the highest confidence score could indicate potential drug targets and infer the underlying molecular MoAs. Open MoA was also validated by testing some well-established targets. Additionally, we applied Open MoA to reveal the MoA of a repositioned drug (JNK-IN-5A) that modulates the PKLR expression in HepG2 cells and found STAT1 is the key transcription factor. Overall, Open MoA represents a first-generation tool that could be utilized for predicting the potential MoA of repurposed drugs and dissecting de novo targets for developing effective treatments. AVAILABILITY AND IMPLEMENTATION: Source code is available at https://github.com/XinmengLiao/Open_MoA.
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