Int J Mol Sci. 2024 Jul 23;25(15):8006. doi: 10.3390/ijms25158006.

ABSTRACT

Mesenchymal stromal cells (MSCs) display heterogeneity in origin and functional role in tissue homeostasis. Subsets of MSCs derived from the neural crest express nestin and serve as niches in bone marrow, but the possibility of coaxing MSCs into nestin-expresing cells for enhanced supportive activity is unclear. In this study, as an approach to the chemical coaxing of MSC functions, we screened libraries of clinically approved chemicals to identify compounds capable of inducing nestin expression in MSCs. Out of 2000 clinical compounds, we chose vorinostat as a candidate to coax the MSCs into neural crest-like fates. When treated with vorinostat, MSCs exhibited a significant increase in the expression of genes involved in the pluripotency and epithelial-mesenchymal transition (EMT), as well as nestin and CD146, the markers for pericytes. In addition, these nestin-induced MSCs exhibited enhanced differentiation towards neuronal cells with the upregulation of neurogenic markers, including SRY-box transcription factor 2 (Sox2), SRY-box transcription factor 10 (Sox10) and microtubule associated protein 2 (Map2) in addition to nestin. Moreover, the coaxed MSCs exhibited enhanced supporting activity for hematopoietic progenitors without supporting leukemia cells. These results demonstrate the feasibility of the drug repositioning of MSCs to induce neural crest-like properties through the chemical coaxing of cell fates.

PMID:39125577 | DOI:10.3390/ijms25158006

Molecules. 2024 Jul 27;29(15):3538. doi: 10.3390/molecules29153538.

ABSTRACT

Cancer is the second leading cause of death in the world following cardiovascular disease. Its treatment, including radiation therapy and surgical removal of the tumour, is based on pharmacotherapy, which prompts a constant search for new and more effective drugs. There are high costs associated with designing, synthesising, and marketing new substances. Drug repositioning is an attractive solution. Fluoroquinolones make up a group of synthetic antibiotics with a broad spectrum of activity in bacterial diseases. Moreover, those compounds are of particular interest to researchers as a result of reports of their antiproliferative effects on the cells of the most lethal cancers. This article presents the current progress in the development of new fluoroquinolone derivatives with potential anticancer and cytotoxic activity, as well as structure-activity relationships, along with possible directions for further development.

PMID:39124943 | DOI:10.3390/molecules29153538

Cancers (Basel). 2024 Jul 26;16(15):2671. doi: 10.3390/cancers16152671.

ABSTRACT

Colorectal cancer (CRC) remains a significant health burden globally, being the second leading cause of cancer-related mortality. Despite significant therapeutic advancements, resistance to systemic antineoplastic agents remains an important obstacle, highlighting the need for innovative screening tools to tailor patient-specific treatment. This review explores the application of patient-derived tumor organoids (PDTOs), three-dimensional, self-organizing models derived from patient tumor samples, as screening tools for drug resistance in CRC. PDTOs offer unique advantages over traditional models by recapitulating the tumor architecture, cellular heterogeneity, and genomic landscape and are a valuable ex vivo predictive drug screening tool. This review provides an overview of the current literature surrounding the use of PDTOs as an instrument for predicting therapy responses in CRC. We also explore more complex models, such as co-cultures with important stromal cells, such as cancer-associated fibroblasts, and organ-on-a-chip models. Furthermore, we discuss the use of PDTOs for drug repurposing, offering a new approach to identify the existing drugs effective against drug-resistant CRC. Additionally, we explore how PDTOs serve as models to gain insights into drug resistance mechanisms, using newer techniques, such as single-cell RNA sequencing and CRISPR-Cas9 genome editing. Through this review, we aim to highlight the potential of PDTOs in advancing our understanding of predicting therapy responses, drug resistance, and biomarker identification in CRC management.

PMID:39123399 | DOI:10.3390/cancers16152671

Cancers (Basel). 2024 Jul 24;16(15):2630. doi: 10.3390/cancers16152630.

ABSTRACT

Lck, a member of the Src kinase family, is a non-receptor tyrosine kinase involved in immune cell activation, antigen recognition, tumor growth, and cytotoxic response. The enzyme has usually been linked to T lymphocyte activation upon antigen recognition. Lck activation is central to CD4, CD8, and NK activation. However, recently, it has become clearer that activating the enzyme in CD8 cells can be independent of antigen presentation and enhance the cytotoxic response. The role of Lck in NK cytotoxic function has been controversial in a similar fashion as the role of the enzyme in CAR T cells. Inhibiting tyrosine kinases has been a highly successful approach to treating hematologic malignancies. The inhibitors may be useful in treating other tumor types, and they may be useful to prevent cell exhaustion. New, more selective inhibitors have been documented, and they have shown interesting activities not only in tumor growth but in the treatment of autoimmune diseases, asthma, and graft vs. host disease. Drug repurposing and bioinformatics can aid in solving several unsolved issues about the role of Lck in cancer. In summary, the role of Lck in immune response and tumor growth is not a simple event and requires more research.

PMID:39123358 | DOI:10.3390/cancers16152630

Chin Med. 2024 Aug 9;19(1):105. doi: 10.1186/s13020-024-00962-6.

ABSTRACT

BACKGROUND: Acute gouty arthritis (AGA) is classified as 'arthritis' in traditional Chinese medicine (TCM) theory. Shirebi granules (SGs), derived from the classic prescription SiMiaoWan, exerts satisfying therapeutic efficacy in ameliorating AGA clinically. However, the underlying mechanisms of SGs against AGA remain unclarified.

METHODS: AGA-related biological processes, signal pathways and biomarker genes were mined from the GEO database through bioinformatics. SGs components were systematically recognized using the UPLC-Q-TOF-MS/MS. A correlation network was established based on the biomarker genes and the chemical components, from which the signal pathway used for further study was selected. Finally, we established an AGA model using SD rats injected with monosodium urate (MSU) in the ankle joint for experimental validation. A combination of behavioral tests, H&E, safranin O- fast green, western blotting, and immunofluorescence were employed to reveal the mechanism of action of SGs on AGA.

RESULTS: The deterioration of AGA was significantly related to the imbalance between immunity and inflammation, neutrophil chemotaxis and inflammatory factor activation. HDAC5, PRKCB, NFκB1, MPO, PRKCA, PIK3CA were identified to be the candidate targets of SGs against AGA, associated with neutrophil extracellular traps (NETs) signal pathway. Animal experiments demonstrated that SGs effectively repaired cartilage damage, blocked TLR4 activation, and inhibited the expression of NETs indicators and inflammatory factors. In addition, SGs prominently alleviated joint redness and swelling, improved joint dysfunction, inhibited inflammatory infiltration of AGA rats.

CONCLUSION: Our data reveal that SGs may effectively alleviate the disease severity of AGA by suppressing NETs-promoted imbalance between immunity and inflammation.

PMID:39123236 | DOI:10.1186/s13020-024-00962-6

ACS Infect Dis. 2024 Aug 9. doi: 10.1021/acsinfecdis.4c00394. Online ahead of print.

ABSTRACT

RNA editing pathway is a validated target in kinetoplastid parasites (Trypanosoma brucei, Trypanosoma cruzi, and Leishmania spp.) that cause severe diseases in humans and livestock. An essential large protein complex, the editosome, mediates uridine insertion and deletion in RNA editing through a stepwise process. This study details the discovery of editosome inhibitors by screening a library of widely used human drugs using our previously developed in vitro biochemical Ribozyme Insertion Deletion Editing (RIDE) assay. Subsequent studies on the mode of action of the identified hits and hit expansion efforts unveiled compounds that interfere with RNA-editosome interactions and novel ligase inhibitors with IC50 values in the low micromolar range. Docking studies on the ligase demonstrated similar binding characteristics for ATP and our novel epigallocatechin gallate inhibitor. The inhibitors demonstrated potent trypanocidal activity and are promising candidates for drug repurposing due to their lack of cytotoxic effects. Further studies are necessary to validate these targets using more definitive gene-editing techniques and to enhance the safety profile.

PMID:39118542 | DOI:10.1021/acsinfecdis.4c00394

BMC Bioinformatics. 2024 Aug 8;25(1):261. doi: 10.1186/s12859-024-05893-5.

ABSTRACT

BACKGROUND: Conducting traditional wet experiments to guide drug development is an expensive, time-consuming and risky process. Analyzing drug function and repositioning plays a key role in identifying new therapeutic potential of approved drugs and discovering therapeutic approaches for untreated diseases. Exploring drug-disease associations has far-reaching implications for identifying disease pathogenesis and treatment. However, reliable detection of drug-disease relationships via traditional methods is costly and slow. Therefore, investigations into computational methods for predicting drug-disease associations are currently needed.

RESULTS: This paper presents a novel drug-disease association prediction method, RAFGAE. First, RAFGAE integrates known associations between diseases and drugs into a bipartite network. Second, RAFGAE designs the Re_GAT framework, which includes multilayer graph attention networks (GATs) and two residual networks. The multilayer GATs are utilized for learning the node embeddings, which is achieved by aggregating information from multihop neighbors. The two residual networks are used to alleviate the deep network oversmoothing problem, and an attention mechanism is introduced to combine the node embeddings from different attention layers. Third, two graph autoencoders (GAEs) with collaborative training are constructed to simulate label propagation to predict potential associations. On this basis, free multiscale adversarial training (FMAT) is introduced. FMAT enhances node feature quality through small gradient adversarial perturbation iterations, improving the prediction performance. Finally, tenfold cross-validations on two benchmark datasets show that RAFGAE outperforms current methods. In addition, case studies have confirmed that RAFGAE can detect novel drug-disease associations.

CONCLUSIONS: The comprehensive experimental results validate the utility and accuracy of RAFGAE. We believe that this method may serve as an excellent predictor for identifying unobserved disease-drug associations.

PMID:39118000 | DOI:10.1186/s12859-024-05893-5

Bioinformatics. 2024 Aug 8:btae496. doi: 10.1093/bioinformatics/btae496. Online ahead of print.

ABSTRACT

MOTIVATION: Drug-target interactions (DTIs) hold a pivotal role in drug repurposing and elucidation of drug mechanisms of action. While single-targeted drugs have demonstrated clinical success, they often exhibit limited efficacy against complex diseases, such as cancers, whose development and treatment is dependent on several biological processes. Therefore, a comprehensive understanding of primary, secondary and even inactive targets becomes essential in the quest for effective and safe treatments for cancer and other indications. The human proteome offers over a thousand druggable targets, yet most FDA-approved drugs bind to only a small fraction of these targets.

RESULTS: This study introduces an attention-based method (called as MMAtt-DTA) to predict drug-target bioactivities across human proteins within seven superfamilies. We meticulously examined nine different descriptor sets to identify optimal signature descriptors for predicting novel DTIs. Our testing results demonstrated Spearman correlations exceeding 0.72 (P < 0.001) for six out of seven superfamilies. The proposed method outperformed fourteen state-of-the-art machine learning, deep learning and graph-based methods and maintained relatively high performance for most target superfamilies when tested with independent bioactivity data sources. We computationally validated 185,676 drug-target pairs from ChEMBL-V33 that were not available during model training, achieving a reasonable performance with Spearman correlation greater than 0.57 (P < 0.001) for most superfamilies. This underscores the robustness of the proposed method for predicting novel DTIs. Finally, we applied our method to predict missing bioactivities among 3,492 approved molecules in ChEMBL-V33, offering a valuable tool for advancing drug mechanism discovery and repurposing existing drugs for new indications.

AVAILABILITY: https://github.com/AronSchulman/MMAtt-DTA.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:39115379 | DOI:10.1093/bioinformatics/btae496

Arch Biochem Biophys. 2024 Aug 5:110111. doi: 10.1016/j.abb.2024.110111. Online ahead of print.

ABSTRACT

Chikungunya virus (CHIKV), transmitted by mosquitoes, poses a significant global health threat. Presently, no effective treatment options are available to reduce the disease burden. The lack of approved therapeutics against CHIKV and the complex spectrum of chronic musculoskeletal and neurological manifestations raise significant concerns, and repurposing drugs could offer swift avenues in the development of effective treatment strategies. RNA capping is a crucial step meditated by non-structural protein 1 (nsP1) in CHIKV replication. In this study, FDA-approved antivirals targeting CHIKV nsP1 methyltransferase (MTase) have been identified by structure-based virtual screening. Berbamine Hydrochloride (BH), ABT199/Venetoclax (ABT), and Ponatinib (PT) were the top hits, which exhibited robust binding energies. Tryptophan fluorescence spectroscopy-based assay confirmed binding of BH-, ABT-, and PT to purified nsP1 with KD values ∼5.45 μM, ∼161.3 μM, and ∼3.83μM, respectively. In a capillary electrophoresis-based assay, a decrease in CHIKV nsP1 MTase activity was observed in a dose-dependent manner. Treatment with BH, ABT, and PT lead to a dose-dependent reduction in the virus titer with IC50 <100, ∼6.75, and <3.9 nM, respectively, and reduced viral mRNA levels. The nsP1 MTases are highly conserved among alphaviruses; therefore, BH, ABT, and PT, as expected, inhibited replication machinery in Sindbis virus (SINV) replicon assay with IC50 ∼1.94, ∼0.23, and >1.25 μM, respectively. These results underscore the efficacy and promise of repurposing drugs as rapid and effective antiviral therapeutics against CHIKV.

PMID:39111614 | DOI:10.1016/j.abb.2024.110111

J Chem Inf Model. 2024 Aug 7. doi: 10.1021/acs.jcim.4c00718. Online ahead of print.

ABSTRACT

Thrombocytopenia, which is associated with thrombopoietin (TPO) deficiency, presents very limited treatment options and can lead to life-threatening complications. Discovering new therapeutic agents against thrombocytopenia has proven to be a challenging task using traditional screening approaches. Fortunately, machine learning (ML) techniques offer a rapid avenue for exploring chemical space, thereby increasing the likelihood of uncovering new drug candidates. In this study, we focused on computational modeling for drug-induced megakaryocyte differentiation and platelet production using ML methods, aiming to gain insights into the structural characteristics of hematopoietic activity. We developed 112 different classifiers by combining eight ML algorithms with 14 molecule features. The top-performing model achieved good results on both 5-fold cross-validation (with an accuracy of 81.6% and MCC value of 0.589) and external validation (with an accuracy of 83.1% and MCC value of 0.642). Additionally, by leveraging the Shapley additive explanations method, the best model provided quantitative assessments of molecular properties and structures that significantly contributed to the predictions. Furthermore, we employed an ensemble strategy to integrate predictions from multiple models and performed in silico predictions for new molecules with potential activity against thrombocytopenia, sourced from traditional Chinese medicine and the Drug Repurposing Hub. The findings of this study could offer valuable insights into the structural characteristics and computational prediction of thrombopoiesis inducers.

PMID:39109515 | DOI:10.1021/acs.jcim.4c00718

Curr Comput Aided Drug Des. 2024 Aug 6. doi: 10.2174/0115734099326517240801035901. Online ahead of print.

NO ABSTRACT

PMID:39108125 | DOI:10.2174/0115734099326517240801035901

Biol Sex Differ. 2024 Aug 6;15(1):62. doi: 10.1186/s13293-024-00634-y.

ABSTRACT

BACKGROUND: Lung adenocarcinoma (LUAD) has been observed to have significant sex differences in incidence, prognosis, and response to therapy. However, the molecular mechanisms responsible for these disparities have not been investigated extensively.

METHODS: Sample-specific gene regulatory network methods were used to analyze RNA sequencing data from non-cancerous human lung samples from The Genotype Tissue Expression Project (GTEx) and lung adenocarcinoma primary tumor samples from The Cancer Genome Atlas (TCGA); results were validated on independent data.

RESULTS: We found that genes associated with key biological pathways including cell proliferation, immune response and drug metabolism are differentially regulated between males and females in both healthy lung tissue and tumor, and that these regulatory differences are further perturbed by tobacco smoking. We also discovered significant sex bias in transcription factor targeting patterns of clinically actionable oncogenes and tumor suppressor genes, including AKT2 and KRAS. Using differentially regulated genes between healthy and tumor samples in conjunction with a drug repurposing tool, we identified several small-molecule drugs that might have sex-biased efficacy as cancer therapeutics and further validated this observation using an independent cell line database.

CONCLUSIONS: These findings underscore the importance of including sex as a biological variable and considering gene regulatory processes in developing strategies for disease prevention and management.

PMID:39107837 | DOI:10.1186/s13293-024-00634-y

Med Oncol. 2024 Aug 6;41(9):219. doi: 10.1007/s12032-024-02461-y.

ABSTRACT

Bladder cancer is a common malignancy worldwide, posing a substantial healthcare challenge. Current standard treatment regimens are primarily based on cisplatin, but their success is often limited by cisplatin resistance and associated toxicities. Therefore, there is an urgent need to develop effective and less toxic therapies as alternatives to cisplatin. We screened the activity of FDA-approved anti-cancer drugs on a panel of cisplatin-resistant bladder cancer cell lines. Based on initial responses, cabazitaxel was selected for further evaluation of its inhibitory effects on the phenotypic properties of these cells. Cabazitaxel, primarily used for metastatic castration-resistant prostate cancer, demonstrated remarkable efficacy in inhibiting colony formation, proliferation, and migration of cisplatin-resistant bladder cancer cells. This study highlights the potential of drug repurposing as a cost-effective and efficient strategy to overcome drug resistance in bladder cancer.

PMID:39105986 | DOI:10.1007/s12032-024-02461-y

Front Pharmacol. 2024 Jul 22;15:1411285. doi: 10.3389/fphar.2024.1411285. eCollection 2024.

ABSTRACT

INTRODUCTION: Romosozumab is a monoclonal antibody approved for osteoporosis which targets sclerostin, an endogenous inhibitor of Wnt/β-catenin pathway. Given the essential roles of the Wnt/β-catenin pathway in various tissues, we hypothesized romosozumab treatment may influence other conditions.

METHODS: This cohort study included patients prescribed romosozumab or parathyroid receptor (PTHR) agonists after 1 January 2019, using a Japanese electronic medical record database. The outcomes of interest included autoimmune disease, interstitial pneumonia, cardiovascular outcome, Alzheimer's disease, Parkinson's disease (PD), serious infections, and malignancies. A stabilized inverse probability-weighted Cox proportional hazard model was used to estimate the hazard ratios. Age- and gender-based subgroup analyses were conducted. Exploratory outcomes based on three-digit International Classification of Diseases 10th Revision-based were also examined.

RESULTS: In total, 2,673 patients treated with romosozumab and 5,980 treated with PTHR agonists were identified, respectively. While most outcomes of interest showed no association with romosozumab, the risk of PD decreased with romosozumab (hazard ratio [95% confidence interval], 0.37 [0.14-0.94]) compared with PTHR agonist. Regarding the cardiovascular outcome, no notable association was identified overall; however, gender-based subgroup analysis suggested that male sex may be a potential risk factor with romosozumab treatment. Only 16 of 903 exploratory outcomes were potentially influenced by romosozumab.

CONCLUSION: Romosozumab lowered the risk of PD development compared with PTHR agonist. The study also highlights the utility of routinely collected health data for drug repositioning. While further validation is warranted, the findings suggest that the Wnt-β-catenin pathway holds promise as a therapeutic target for PD.

PMID:39104397 | PMC:PMC11298754 | DOI:10.3389/fphar.2024.1411285

Hum Genet. 2024 Aug 6. doi: 10.1007/s00439-024-02696-9. Online ahead of print.

ABSTRACT

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease accompanied by both local and systemic comorbidities. Genetic factors play a role in the development of IPF and certain associated comorbidities. Nevertheless, it is uncertain whether there are shared genetic factors underlying IPF and these comorbidities. To bridge this knowledge gap, we conducted a systematic investigation into the shared genetic architecture between IPF and ten prevalent heritable comorbidities (i.e., body mass index [BMI], coronary artery disease [CAD], chronic obstructive pulmonary disease [COPD], gastroesophageal reflux disease, lung cancer, major depressive disorder [MDD], obstructive sleep apnoea, pulmonary hypertension [PH], stroke, and type 2 diabetes), by utilizing large-scale summary data from their respective genome-wide association studies and multi-omics studies. We revealed significant (false discovery rate [FDR] < 0.05) and moderate genetic correlations between IPF and seven comorbidities, excluding lung cancer, MDD and PH. Evidence suggested a partially putative causal effect of IPF on CAD. Notably, we observed FDR-significant genetic enrichments in lung for the cross-trait between IPF and CAD and in liver for the cross-trait between IPF and COPD. Additionally, we identified 65 FDR-significant genes over-represented in 20 biological pathways related to the etiology of IPF, BMI, and COPD, including inflammation-related mucin gene clusters. Several of these genes were associated with clinically relevant drugs for the treatment of IPF, CAD, and/or COPD. Our results underscore the pervasive shared genetic basis between IPF and its common comorbidities and hold future implications for early diagnosis of IPF-related comorbidities, drug repurposing, and the development of novel therapies for IPF.

PMID:39103522 | DOI:10.1007/s00439-024-02696-9

ChemistryOpen. 2024 Aug 5:e202400091. doi: 10.1002/open.202400091. Online ahead of print.

ABSTRACT

The emergence of drug-resistant viruses and novel strains necessitates the rapid development of novel antiviral therapies. This need was particularly demanding during the COVID-19 pandemic. While de novo drug development is a time-consuming process, repurposing existing approved medications offers a more expedient approach. In our prior in silico screening of the DrugBank database, fidaxomicin emerged as a potential SARS-CoV-2 papain-like protease inhibitor. This study extends those findings by investigating fidaxomicin's antiviral properties in vitro. Our results support further exploration of fidaxomicin as a therapeutic candidate against SARS-CoV-2, given its promising in vitro antiviral activity and favorable safety profile.

PMID:39099532 | DOI:10.1002/open.202400091

Cell Signal. 2024 Aug 2:111329. doi: 10.1016/j.cellsig.2024.111329. Online ahead of print.

ABSTRACT

Mitochondria, traditionally known as cellular powerhouses, now emerge as critical signaling centers influencing cancer progression and drug resistance. The review highlights the role that apoptotic signaling, DNA mutations, mitochondrial dynamics and metabolism play in the development of resistance mechanisms and the advancement of cancer. Targeted approaches are discussed, with an emphasis on managing mitophagy, fusion, and fission of the mitochondria to make resistant cancer cells more susceptible to traditional treatments. Additionally, metabolic reprogramming can be used to effectively target metabolic enzymes such GLUT1, HKII, PDK, and PKM2 in order to avoid resistance mechanisms. Although there are potential possibilities for therapy, the complex structure of mitochondria and their subtle role in tumor development hamper clinical translation. Novel targeted medicines are put forth, providing fresh insights on combating drug resistance in cancer. The study also emphasizes the significance of glutamine metabolism, mitochondrial respiratory complexes, and apoptotic pathways as potential targets to improve treatment effectiveness against drug-resistant cancers. Combining complementary and nanoparticle-based techniques to target mitochondria has demonstrated encouraging results in the treatment of cancer, opening doors to reduce resistance and enable individualized treatment plans catered to the unique characteristics of each patient. Suggesting innovative approaches such as drug repositioning and mitochondrial drug delivery to enhance the efficacy of mitochondria-targeting therapies, presenting a pathway for advancements in cancer treatment. This thorough investigation is a major step forward in the treatment of cancer and has the potential to influence clinical practice and enhance patient outcomes.

PMID:39098704 | DOI:10.1016/j.cellsig.2024.111329

Cell Genom. 2024 Jul 29:100627. doi: 10.1016/j.xgen.2024.100627. Online ahead of print.

ABSTRACT

Excision repair cross-complementation group 2 (ERCC2) encodes the DNA helicase xeroderma pigmentosum group D, which functions in transcription and nucleotide excision repair. Point mutations in ERCC2 are putative drivers in around 10% of bladder cancers (BLCAs) and a potential positive biomarker for cisplatin therapy response. Nevertheless, the prognostic significance directly attributed to ERCC2 mutations and its pathogenic role in genome instability remain poorly understood. We first demonstrated that mutant ERCC2 is an independent predictor of prognosis in BLCA. We then examined its impact on the somatic mutational landscape using a cohort of ERCC2 wild-type (n = 343) and mutant (n = 39) BLCA whole genomes. The genome-wide distribution of somatic mutations is significantly altered in ERCC2 mutants, including T[C>T]N enrichment, altered replication time correlations, and CTCF-cohesin binding site mutation hotspots. We leverage these alterations to develop a machine learning model for predicting pathogenic ERCC2 mutations, which may be useful to inform treatment of patients with BLCA.

PMID:39096913 | DOI:10.1016/j.xgen.2024.100627

Mol Genet Metab. 2024 Jul 17;143(1-2):108538. doi: 10.1016/j.ymgme.2024.108538. Online ahead of print.

ABSTRACT

Phosphomannomutase 2 deficiency (PMM2-CDG), the most frequent congenital disorder of glycosylation, is an autosomal recessive disease caused by biallelic pathogenic variants in the PMM2 gene. There is no cure for this multisystemic syndrome. Some of the therapeutic approaches that are currently in development include mannose-1-phosphate replacement therapy, drug repurposing, and the use of small chemical molecules to correct folding defects. Preclinical models are needed to evaluate the efficacy of treatments to overcome the high lethality of the available animal model. In addition, the number of variants with unknown significance is increasing in clinical settings. This study presents the generation of a cellular disease model by knocking out the PMM2 gene in the hepatoma HepG2 cell line using CRISPR-Cas9 gene editing. The HepG2 knockout model accurately replicates the PMM2-CDG phenotype, exhibiting a complete absence of PMM2 protein and mRNA, a 90% decrease in PMM enzymatic activity, and altered ICAM-1, LAMP1 and A1AT glycoprotein patterns. The evaluation of PMM2 disease-causing variants validates the model's utility for studying new PMM2 clinical variants, providing insights for diagnosis and potentially for evaluating therapies. A CRISPR-Cas9-generated HepG2 knockout model accurately recapitulates the PMM2-CDG phenotype, providing a valuable tool for assessing disease-causing variants and advancing therapeutic strategies.

PMID:39096554 | DOI:10.1016/j.ymgme.2024.108538

ACS Chem Neurosci. 2024 Aug 3. doi: 10.1021/acschemneuro.4c00150. Online ahead of print.

ABSTRACT

The misfolding and aggregation of beta-amyloid (Aβ) peptides have been implicated as key pathogenic events in the early stages of Alzheimer's disease (AD). Inhibiting Aβ aggregation represents a potential disease-modifying therapeutic approach to AD treatment. Previous studies have identified various molecules that inhibit Aβ aggregation, some of which share common chemical substructures (fragments) that may be key to their inhibitory activity. Employing fragment-based drug discovery (FBDD) methods may facilitate the identification of these fragments, which can subsequently be used to screen new inhibitors and provide leads for further drug development. In this study, we used an in silico FBDD approach to identify 17 fragment clusters that are significantly enriched among Aβ aggregation inhibitors. These fragments were then used to screen anti-infective agents, a promising drug class for repurposing against amyloid aggregation. This screening process identified 16 anti-infective drugs, 5 of which were chosen for further investigation. Among the 5 candidates, anidulafungin, an antifungal compound, showed high efficacy in inhibiting Aβ aggregation in vitro. Kinetic analysis revealed that anidulafungin selectively blocks the primary nucleation step of Aβ aggregation, substantially delaying Aβ fibril formation. Cell viability assays demonstrated that anidulafungin can reduce the toxicity of oligomeric Aβ on BV2 microglia cells. Molecular docking simulations predicted that anidulafungin interacted with various Aβ species, including monomers, oligomers, and fibrils, potentially explaining its activity against Aβ aggregation and toxicity. This study suggests that anidulafungin is a potential drug to be repurposed for AD, and FBDD is a promising approach for discovering drugs to combat Aβ aggregation.

PMID:39096284 | DOI:10.1021/acschemneuro.4c00150