Identification and evaluation of small-molecule inhibitors against the dNTPase SAMHD1viaa comprehensive screening funnel DOI Creative Commons
Si Min Zhang, Cynthia B. J. Paulin, Maurice Michel

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 18, 2023

Abstract Sterile alpha motif and histidine-aspartic acid domain containing protein-1 (SAMHD1) is a deoxynucleoside triphosphate (dNTP) triphosphohydrolase central to cellular nucleotide pool homeostasis. Recent literature has also demonstrated how SAMHD1 can detoxify chemotherapy metabolites thereby controlling their clinical responses. To further understand biology investigate the potential of targeting this enzyme as neoadjuvant existing chemotherapies we set out discover selective small molecule-based inhibitors SAMHD1. Here report discovery pipeline encompassing biochemical screening campaign complementary biochemical, biophysical, cell-based readouts for characterisation screen output. The identified hit compound TH6342 its analogues, accompanied by inactive negative control analogue TH7126, specific, low μM potency in inhibiting hydrolysis both natural substrates therapeutics, shown using enzyme-coupled direct enzymatic activity assays. Their mode inhibition was subsequently detailed coupling kinetic studies with thermal shift assays, where analogues were engage pre-tetrameric deter oligomerisation allosteric activation without occupying binding pockets. We outline development application multiple assays assessing target engagement associated functional effects, including CETSA an in-cell dNTP hydrolase assay, which highlighted future optimisation strategies chemotype. In summary, novel inhibition, broaden tool compounds available deciphering enzymology functions, furthermore, reported herein represents thorough framework inhibitor development. Figure

Language: Английский

Nanomedicines Targeting Metabolic Pathways in the Tumor Microenvironment: Future Perspectives and the Role of AI DOI Creative Commons

Shuai Fan,

Wenyu Wang,

Wieqi Che

et al.

Metabolites, Journal Year: 2025, Volume and Issue: 15(3), P. 201 - 201

Published: March 13, 2025

Background: Tumor cells engage in continuous self-replication by utilizing a large number of resources and capabilities, typically within an aberrant metabolic regulatory network to meet their own demands. This dysregulation leads the formation tumor microenvironment (TME) most solid tumors. Nanomedicines, due unique physicochemical properties, can achieve passive targeting certain tumors through enhanced permeability retention (EPR) effect, or active deliberate design optimization, resulting accumulation TME. The use nanomedicines target critical pathways holds significant promise. However, requires careful selection relevant drugs materials, taking into account multiple factors. traditional trial-and-error process is relatively inefficient. Artificial intelligence (AI) integrate big data evaluate delivery efficiency nanomedicines, thereby assisting nanodrugs. Methods: We have conducted detailed review key papers from databases, such as ScienceDirect, Scopus, Wiley, Web Science, PubMed, focusing on reprogramming, mechanisms action development metabolism, application AI empowering nanomedicines. integrated content present current status research metabolism potential future directions this field. Results: Nanomedicines possess excellent TME which be utilized disrupt cells, including glycolysis, lipid amino acid nucleotide metabolism. disruption selective killing disturbance Extensive has demonstrated that AI-driven methodologies revolutionized nanomedicine development, while concurrently enabling precise identification molecular regulators involved oncogenic reprogramming pathways, catalyzing transformative innovations targeted cancer therapeutics. Conclusions: great Additionally, will accelerate discovery metabolism-related targets, empower optimization help minimize toxicity, providing new paradigm for development.

Language: Английский

Citations

2

Formate overflow drives toxic folate trapping in MTHFD1 inhibited cancer cells DOI Creative Commons
Alanna C. Green, Petra Marttila, Nicole Kiweler

et al.

Nature Metabolism, Journal Year: 2023, Volume and Issue: 5(4), P. 642 - 659

Published: April 3, 2023

Abstract Cancer cells fuel their increased need for nucleotide supply by upregulating one-carbon (1C) metabolism, including the enzymes methylenetetrahydrofolate dehydrogenase–cyclohydrolase 1 and 2 (MTHFD1 MTHFD2). TH9619 is a potent inhibitor of dehydrogenase cyclohydrolase activities in both MTHFD1 MTHFD2, selectively kills cancer cells. Here, we reveal that, cells, targets nuclear MTHFD2 but does not inhibit mitochondrial MTHFD2. Hence, overflow formate from mitochondria continues presence TH9619. inhibits activity occurring downstream release, leading to accumulation 10-formyl-tetrahydrofolate, which term ‘folate trap’. This results thymidylate depletion death MTHFD2-expressing previously uncharacterized folate trapping mechanism exacerbated physiological hypoxanthine levels that block de novo purine synthesis pathway, additionally prevent 10-formyl-tetrahydrofolate consumption synthesis. The described here differs other MTHFD1/2 inhibitors antifolates. Thus, our findings uncover an approach attack regulatory 1C metabolism.

Language: Английский

Citations

23

Role of MTH1 in Oxidative Stress and Therapeutic Targeting of Cancer DOI Creative Commons

Aaliya Taiyab,

Anam Ashraf,

Md Nayab Sulaimani

et al.

Redox Biology, Journal Year: 2024, Volume and Issue: 77, P. 103394 - 103394

Published: Oct. 11, 2024

Cancer cells maintain high levels of reactive oxygen species (ROS) to drive their growth, but ROS can trigger cell death through oxidative stress and DNA damage. To survive enhanced levels, cancer activate antioxidant defenses. One such defense is MTH1, an enzyme that prevents the incorporation oxidized nucleotides into DNA, thus preventing damage allowing proliferate. MTH1 are often elevated in many cancers, thus, inhibiting attractive strategy for suppressing tumor growth metastasis. Targeted inhibition induce cells, exploiting vulnerability selectively targeting them destruction. Targeting promising treatment because normal have lower less dependent on these pathways, making approach both effective specific cancer. This review aims investigate potential as a therapeutic target, especially treatment, offering detailed insights its structure, function, role disease progression. We also discussed various inhibitors been developed though effectiveness varies. In addition, this provide deeper mechanistic prevention management diseases.

Language: Английский

Citations

6

Epigenetic–Metabolic Interplay in the DNA Damage Response and Therapeutic Resistance of Breast Cancer DOI Open Access
Chandrima Das, Swagata Adhikari, Apoorva Bhattacharya

et al.

Cancer Research, Journal Year: 2023, Volume and Issue: 83(5), P. 657 - 666

Published: Jan. 18, 2023

Abstract Therapy resistance is imposing a daunting challenge on effective clinical management of breast cancer. Although the development to drugs multifaceted, reprogramming energy metabolism pathways emerging as central but heterogenous regulator this therapeutic challenge. Metabolic heterogeneity in cancer cells intricately associated with alterations different signaling networks and activation DNA damage response pathways. Here we consider how dynamic metabolic milieu regulates their repair ability ultimately contribute therapy resistance. Diverse epigenetic regulators are crucial remodeling landscape This epigenetic–metabolic interplay profoundly affects genomic stability well genotoxic therapies. These observations identify defining mechanisms epigenetics–metabolism–DNA axis that can be critical for devising novel, targeted approaches could sensitize conventional treatment strategies.

Language: Английский

Citations

13

The roles of lncRNAs in the development of drug resistance of oral cancers DOI Open Access
Wenjing Wang, Yi Liu, Jianan Wu

et al.

Biomedicine & Pharmacotherapy, Journal Year: 2024, Volume and Issue: 180, P. 117458 - 117458

Published: Oct. 15, 2024

Language: Английский

Citations

5

Understanding the interplay between dNTP metabolism and genome stability in cancer DOI Creative Commons
Miriam Yagüe-Capilla, Sean G. Rudd

Disease Models & Mechanisms, Journal Year: 2024, Volume and Issue: 17(8)

Published: Aug. 1, 2024

ABSTRACT The size and composition of the intracellular DNA precursor pool is integral to maintenance genome stability, this relationship fundamental our understanding cancer. Key aspects carcinogenesis, including elevated mutation rates induction certain types damage in cancer cells, can be linked disturbances deoxynucleoside triphosphate (dNTP) pools. Furthermore, approaches treat heavily exploit metabolic interplay between dNTP pool, with a long-standing example being use antimetabolite-based therapies, strategy continues show promise development new targeted therapies. In Review, we compile current knowledge on both causes consequences perturbations together their impact stability. We outline several outstanding questions remaining field, such as role catabolism stability expansion. Importantly, detail how mechanistic these processes utilised aim providing better informed treatment options patients

Language: Английский

Citations

3

Integration of single-cell transcriptomics and bulk transcriptomics to explore prognostic and immunotherapeutic characteristics of nucleotide metabolism in lung adenocarcinoma DOI Creative Commons
Kai Zhang,

Luyao Wang,

Huili Chen

et al.

Frontiers in Genetics, Journal Year: 2025, Volume and Issue: 15

Published: Jan. 8, 2025

Lung adenocarcinoma (LUAD) is a highly aggressive tumor with one of the highest morbidity and mortality rates in world. Nucleotide metabolic processes are critical for cancer development, progression, alteration microenvironment. However, effect nucleotide metabolism on LUAD remains to be thoroughly investigated. Transcriptomic clinical data were downloaded organized from TCGA GEO databases. Genes related Msigdb database. associated prognosis identified using univariate COX analysis, prognostic risk model was constructed machine learning combination Lasso + Stepcox. The model's predictive validity evaluated KM survival timeROC curves. Based model, patients classified into different subtypes, differences between subtypes explored terms genomic mutations, functional enrichment, immune characteristics, immunotherapy responses. Finally, key gene SNRPA screened, series vitro experiments performed cell lines explore role LUAD. could accurately categorized based metabolism-related score (NMBRS). There significant NMBRS showed high accuracy predicting patients. In addition, mutation enrichment exhibited anti-tumor profiles. Importantly, can used predict responsiveness immunotherapy. results cellular indicate that plays an important development progression lung adenocarcinoma. This study comprehensively reveals value application A signature genes predicted patients, this as guide

Language: Английский

Citations

0

Integrating machine learning and multi-omics analysis to reveal nucleotide metabolism-related immune genes and their functional validation in ischemic stroke DOI Creative Commons
Tianzhi Li,

X. T. Kang,

Sijie Zhang

et al.

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: March 26, 2025

Background Ischemic stroke (IS) is a major global cause of death and disability, linked to nucleotide metabolism imbalances. This study aimed identify metabolism-related genes associated with IS explore their roles in disease mechanisms for new diagnostic therapeutic strategies. Methods gene expression data were sourced from the GEO database. Differential analysis weighted co-expression network (WGCNA) conducted R, intersecting results genes. Functional enrichment connectivity map (cMAP) analyses identified key potential agents. Core immune-related determined using LASSO regression, SVM-RFE, Random Forest algorithms. Immune cell infiltration levels correlations analyzed via CIBERSORT. Single-cell RNA sequencing (scRNA-seq) molecular docking assessed expression, localization, gene-drug binding. In vivo experiments validated core expression. Results Thirty-three candidate identified, mainly involved immune inflammatory responses. CFL1, HMCES , GIMAP1 emerged as genes, showing high potential. cMAP indicated these drug targets. scRNA-seq clarified confirmed strong significant IS. Conclusion underscores role IS, identifying biomarkers targets, providing insights diagnosis therapy development.

Language: Английский

Citations

0

Proteomic Profiles of Neutrophils from Behcet’s Uveitis Patients and their Sex Differences DOI Creative Commons
Rong Liu, Qingfeng Wang,

Qingyan Jiang

et al.

Inflammation, Journal Year: 2025, Volume and Issue: unknown

Published: April 22, 2025

Language: Английский

Citations

0

Mitochondria-Targeted Thymidylate Synthase Inhibitor Based on Fluorescent Molecularly Imprinted Polymers for Tumor Antimetabolic Therapy DOI

Yusheng Feng,

Yating Qin,

Zhuang Ji

et al.

ACS Applied Materials & Interfaces, Journal Year: 2023, Volume and Issue: 15(26), P. 31139 - 31149

Published: June 23, 2023

Antimetabolites targeting thymidylate synthase (TS), such as 5-fluorouracil and capecitabine, have been widely used in tumor therapy the past decades. Here, we present a strategy to construct mitochondria-targeted antimetabolic therapeutic nanomedicines based on fluorescent molecularly imprinted polymers (FMIP), nanomedicine was denoted Mito-FMIP. Mito-FMIP, synthesized using dye-doped silica carrier amino acid sequence containing active center of TS template peptide, could specifically recognize bind site TS, thus inhibiting catalytic activity therefore hindering subsequent DNA biosynthesis, ultimately growth. The imprinting factor FMIP reached 2.9, modification CTPB endowed Mito-FMIP with ability target mitochondria. In vitro experiments demonstrated that able efficiently aggregate mitochondria inhibit CT26 cell proliferation by 59.9%. results flow cytometric analysis showed relative mean fluorescence intensity accumulated 3.4-fold FMIP. vivo volume Mito-FMIP-treated group only one third untreated group. addition, exibited maximum emission wavelength at 682 nm, which allowed it be for imaging tumors. Taken together, this study provides new construction functions polymers.

Language: Английский

Citations

7