Lancet Rheumatol. 2024 May 8:S2665-9913(24)00064-X. doi: 10.1016/S2665-9913(24)00064-X. Online ahead of print.

ABSTRACT

BACKGROUND: Giant cell arteritis is an age-related vasculitis that mainly affects the aorta and its branches in individuals aged 50 years and older. Current options for diagnosis and treatment are scarce, highlighting the need to better understand its underlying pathogenesis. Genome-wide association studies (GWAS) have emerged as a powerful tool for unravelling the pathogenic mechanisms involved in complex diseases. We aimed to characterise the genetic basis of giant cell arteritis by performing the largest GWAS of this vasculitis to date and to assess the functional consequences and clinical implications of identified risk loci.

METHODS: We collected and meta-analysed genomic data from patients with giant cell arteritis and healthy controls of European ancestry from ten cohorts across Europe and North America. Eligible patients required confirmation of giant cell arteritis diagnosis by positive temporal artery biopsy, positive temporal artery doppler ultrasonography, or imaging techniques confirming large-vessel vasculitis. We assessed the functional consequences of loci associated with giant cell arteritis using cell enrichment analysis, fine-mapping, and causal gene prioritisation. We also performed a drug repurposing analysis and developed a polygenic risk score to explore the clinical implications of our findings.

FINDINGS: We included a total of 3498 patients with giant cell arteritis and 15 550 controls. We identified three novel loci associated with risk of giant cell arteritis. Two loci, MFGE8 (rs8029053; p=4·96 × 10-8; OR 1·19 [95% CI 1·12-1·26]) and VTN (rs704; p=2·75 × 10-9; OR 0·84 [0·79-0·89]), were related to angiogenesis pathways and the third locus, CCDC25 (rs11782624; p=1·28 × 10-8; OR 1·18 [1·12-1·25]), was related to neutrophil extracellular traps (NETs). We also found an association between this vasculitis and HLA region and PLG. Variants associated with giant cell arteritis seemed to fulfil a specific regulatory role in crucial immune cell types. Furthermore, we identified several drugs that could represent promising candidates for treatment of this disease. The polygenic risk score model was able to identify individuals at increased risk of developing giant cell arteritis (90th percentile OR 2·87 [95% CI 2·15-3·82]; p=1·73 × 10-13).

INTERPRETATION: We have found several additional loci associated with giant cell arteritis, highlighting the crucial role of angiogenesis in disease susceptibility. Our study represents a step forward in the translation of genomic findings to clinical practice in giant cell arteritis, proposing new treatments and a method to measure genetic predisposition to this vasculitis.

FUNDING: Institute of Health Carlos III, Spanish Ministry of Science and Innovation, UK Medical Research Council, and National Institute for Health and Care Research.

PMID:38734017 | DOI:10.1016/S2665-9913(24)00064-X

Curr Microbiol. 2024 May 11;81(7):169. doi: 10.1007/s00284-024-03671-3.

ABSTRACT

The rapid spread of the SARS-CoV-2 virus has emphasized the urgent need for effective therapies to combat COVID-19. Investigating the potential targets, inhibitors, and in silico approaches pertinent to COVID-19 are of utmost need to develop novel therapeutic agents and reprofiling of existing FDA-approved drugs. This article reviews the viral enzymes and their counter receptors involved in the entry of SARS-CoV-2 into host cells, replication of genomic RNA, and controlling the host cell physiology. In addition, the study provides an overview of the computational techniques such as docking simulations, molecular dynamics, QSAR modeling, and homology modeling that have been used to find the FDA-approved drugs and other inhibitors against SARS-CoV-2. Furthermore, a comprehensive overview of virus-based and host-based druggable targets from a structural point of view, together with the reported therapeutic compounds against SARS-CoV-2 have also been presented. The current study offers future perspectives for research in the field of network pharmacology investigating the large unexplored molecular libraries. Overall, the present in-depth review aims to expedite the process of identifying and repurposing drugs for researchers involved in the field of COVID-19 drug discovery.

PMID:38733424 | DOI:10.1007/s00284-024-03671-3

Int J Mol Sci. 2024 May 2;25(9):4975. doi: 10.3390/ijms25094975.

ABSTRACT

An imbalance between production and excretion of amyloid β peptide (Aβ) in the brain tissues of Alzheimer's disease (AD) patients leads to Aβ accumulation and the formation of noxious Aβ oligomers/plaques. A promising approach to AD prevention is the reduction of free Aβ levels by directed enhancement of Aβ binding to its natural depot, human serum albumin (HSA). We previously demonstrated the ability of specific low-molecular-weight ligands (LMWLs) in HSA to improve its affinity for Aβ. Here we develop this approach through a bioinformatic search for the clinically approved AD-related LMWLs in HSA, followed by classification of the candidates according to the predicted location of their binding sites on the HSA surface, ranking of the candidates, and selective experimental validation of their impact on HSA affinity for Aβ. The top 100 candidate LMWLs were classified into five clusters. The specific representatives of the different clusters exhibit dramatically different behavior, with 3- to 13-fold changes in equilibrium dissociation constants for the HSA-Aβ40 interaction: prednisone favors HSA-Aβ interaction, mefenamic acid shows the opposite effect, and levothyroxine exhibits bidirectional effects. Overall, the LMWLs in HSA chosen here provide a basis for drug repurposing for AD prevention, and for the search of medications promoting AD progression.

PMID:38732194 | DOI:10.3390/ijms25094975

Molecules. 2024 Apr 23;29(9):1927. doi: 10.3390/molecules29091927.

ABSTRACT

Cisplatin is a potent compound in anti-tumor chemotherapy; however, its clinical utility is hampered by dose-limiting nephrotoxicity. This study investigated whether papaverine could mitigate cisplatin-induced kidney damage while preserving its chemotherapeutic efficacy. Integrative bioinformatics analysis predicted papaverine modulation of the mechanistic pathways related to cisplatin renal toxicity; notably, mitogen-activated protein kinase 1 (MAPK1) signaling. We validated protective effects in normal kidney cells without interfering with cisplatin cytotoxicity on a cancer cell line. Concurrent in vivo administration of papaverine alongside cisplatin in rats prevented elevations in nephrotoxicity markers, including serum creatinine, blood urea nitrogen, and renal oxidative stress markers (malondialdehyde, inducible nitric oxide synthase (iNOS), and pro-inflammatory cytokines), as tumor necrosis factor alpha (TNF-α), monocyte chemoattractant protein 1 (MCP-1), and interleukin-6 (IL-6). Papaverine also reduced apoptosis markers such as Bcl2 and Bcl-2-associated X protein (Bax) and kidney injury molecule-1 (KIM-1), and histological damage. In addition, it upregulates antioxidant enzymes like catalase (CAT), superoxide dismutase (SOD) and glutathione peroxidase (GPx) while boosting anti-inflammatory signaling interleukin-10 (IL-10). These effects were underlined by the ability of Papaverine to downregulate MAPK-1 expression. Overall, these findings show papaverine could protect against cisplatin kidney damage without reducing its cytotoxic activity. Further research would allow the transition of these results to clinical practice.

PMID:38731418 | DOI:10.3390/molecules29091927

Cancers (Basel). 2024 Apr 30;16(9):1754. doi: 10.3390/cancers16091754.

ABSTRACT

Outcomes for glioblastoma (GBM) remain poor despite standard-of-care treatments including surgical resection, radiation, and chemotherapy. Intratumoral heterogeneity contributes to treatment resistance and poor prognosis, thus demanding novel therapeutic approaches. Drug repositioning studies on antiretroviral therapy (ART) have shown promising potent antineoplastic effects in multiple cancers; however, its efficacy in GBM remains unclear. To better understand the pleiotropic anticancer effects of ART on GBM, we conducted a comprehensive drug repurposing analysis of ART in GBM to highlight its utility in translational neuro-oncology. To uncover the anticancer role of ART in GBM, we conducted a comprehensive bioinformatic and in vitro screen of antiretrovirals against glioblastoma. Using the DepMap repository and reversal of gene expression score, we conducted an unbiased screen of 16 antiretrovirals in 40 glioma cell lines to identify promising candidates for GBM drug repositioning. We utilized patient-derived neurospheres and glioma cell lines to assess neurosphere viability, proliferation, and stemness. Our in silico screen revealed that several ART drugs including reverse transcriptase inhibitors (RTIs) and protease inhibitors (PIs) demonstrated marked anti-glioma activity with the capability of reversing the GBM disease signature. RTIs effectively decreased cell viability, GBM stem cell markers, and proliferation. Our study provides mechanistic and functional insight into the utility of ART repurposing for malignant gliomas, which supports the current literature. Given their safety profile, preclinical efficacy, and neuropenetrance, ARTs may be a promising adjuvant treatment for GBM.

PMID:38730705 | DOI:10.3390/cancers16091754

Int J Biol Macromol. 2024 May 8:132164. doi: 10.1016/j.ijbiomac.2024.132164. Online ahead of print.

ABSTRACT

The process of developing novel compounds/drugs is arduous, time-intensive, and financially burdensome, characterized by a notably low success rate and relatively high attrition rates. To alleviate these challenges, compound/drug repositioning strategies are employed to predict potential therapeutic effects for DrugBank-approved compounds across various diseases. In this study, we devised a computational and enzyme inhibitory mechanistic approach to identify promising compounds from the pool of DrugBank-approved substances targeting Diabetes Mellitus (DM). Molecular docking analyses were employed to validate the binding interaction patterns and conformations of the screened compounds within the active site of α-glucosidase. Notably, Asp352 and Glu277 participated in interactions within the α-glucosidase-ligand complexes, mediated by conventional hydrogen bonding and van der Waals forces, respectively. The stability of the docked complexes (α-glucosidase-compounds) was scrutinized through Molecular Dynamics (MD) simulations. Subsequent in vitro analyses assessed the therapeutic potential of the repositioned compounds against α-glucosidase. Kinetic studies revealed that "Forodesine" exhibited a lower IC50 (0.24 ± 0.04 mM) compared to the control, and its inhibitory pattern corresponds to that of competitive inhibitors. In-depth in silico secondary structure content analysis detailed the interactions between Forodesine and α-glucosidase, unveiling significant alterations in enzyme conformation upon binding, impacting its catalytic activity. Overall, our findings underscore the potential of Forodesine as a promising candidate for DM treatment through α-glucosidase inhibition. Further validation through in vitro and in vivo studies is imperative to confirm the therapeutic benefits of Forodesine in conformational diseases such as DM.

PMID:38729474 | DOI:10.1016/j.ijbiomac.2024.132164

J Infect Dev Ctries. 2024 Apr 30;18(4):520-531. doi: 10.3855/jidc.18189.

ABSTRACT

INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic caused global health, economic, and population loss. Variants of the coronavirus contributed to the severity of the disease and persistent rise in infections. This study aimed to identify potential drug candidates from fifteen approved antiviral drugs against SARS-CoV-2 (6LU7), SARS-CoV (5B6O), and SARS-CoV-2 spike protein (6M0J) using virtual screening and pharmacokinetics to gain insights into COVID-19 therapeutics.

METHODOLOGY: We employed drug repurposing approach to analyze binding performance of fifteen clinically approved antiviral drugs against the main protease of SARS-CoV-2 (6LU7), SARS-CoV (5B6O), and SARS-CoV-2 spike proteins bound to ACE-2 receptor (6M0J), to provide an insight into the therapeutics of COVID-19. AutoDock Vina was used for docking studies. The binding affinities were calculated, and 2-3D structures of protein-ligand interactions were drawn.

RESULTS: Rutin, hesperidin, and nelfinavir are clinically approved antiviral drugs with high binding affinity to proteins 6LU7, 5B6O, and 6M0J. These ligands have excellent pharmacokinetics, ensuring efficient absorption, metabolism, excretion, and digestibility. Hesperidin showed the most potent interaction with spike protein 6M0J, forming four H-bonds. Nelfinavir had a high human intestinal absorption (HIA) score of 0.93, indicating maximum absorption in the body and promising interactions with 6LU7.

CONCLUSIONS: Our results indicated that rutin, hesperidin, and nelfinavir had the highest binding results against the proposed drug targets. The computational approach effectively identified SARS-CoV-2 inhibitors. COVID-19 is still a recurrent threat globally and predictive analysis using natural compounds might serve as a starting point for new drug development against SARS-CoV-2 and related viruses.

PMID:38728643 | DOI:10.3855/jidc.18189

BMC Cancer. 2024 May 9;24(1):574. doi: 10.1186/s12885-024-12338-y.

ABSTRACT

BACKGROUND: Next-generation sequencing (NGS) has been introduced to many Korean institutions to support molecular diagnostics in cancer since 2017, when it became eligible for reimbursement by the National Health Insurance Service. However, the uptake of molecularly guided treatment (MGT) based on NGS results has been limited because of stringent regulations regarding prescriptions outside of approved indications, a lack of clinical trial opportunities, and limited access to molecular tumor boards (MTB) at most institutions. The KOSMOS-II study was designed to demonstrate the feasibility and effectiveness of MGT, informed by MTBs, using a nationwide precision medicine platform.

METHODS: The KOSMOS-II trial is a large-scale nationwide master observational study. It involves a framework for screening patients with metastatic solid tumors for actionable genetic alterations based on local NGS testing. It recommends MGT through a remote and centralized MTB meeting held biweekly. MGT can include one of the following options: Tier 1, the therapeutic use of investigational drugs targeting genetic alterations such as ALK, EGFR, ERBB2, BRAF, FH, ROS1, and RET, or those with high tumor mutational burden; Tier 2, comprising drugs with approved indications or those permitted for treatment outside of the indications approved by the Health Insurance Review and Assessment Service of Korea; Tier 3, involving clinical trials matching the genetic alterations recommended by the MTB. Given the anticipated proportion of patients receiving MGT in the range of 50% ± 3.25%, this study aims to enroll 1,000 patients. Patients must have progressed to one or more lines of therapy and undergone NGS before enrollment.

DISCUSSION: This pragmatic master protocol provides a mass-screening platform for rare genetic alterations and high-quality real-world data. Collateral clinical trials, translational studies, and clinico-genomic databases will contribute to generating evidence for drug repositioning and the development of new biomarkers.

TRIAL REGISTRATION: NCT05525858.

PMID:38724991 | DOI:10.1186/s12885-024-12338-y

BMC Genomics. 2024 May 9;25(1):411. doi: 10.1186/s12864-024-10326-x.

ABSTRACT

BACKGROUND: In recent years, there has been a growing interest in utilizing computational approaches to predict drug-target binding affinity, aiming to expedite the early drug discovery process. To address the limitations of experimental methods, such as cost and time, several machine learning-based techniques have been developed. However, these methods encounter certain challenges, including the limited availability of training data, reliance on human intervention for feature selection and engineering, and a lack of validation approaches for robust evaluation in real-life applications.

RESULTS: To mitigate these limitations, in this study, we propose a method for drug-target binding affinity prediction based on deep convolutional generative adversarial networks. Additionally, we conducted a series of validation experiments and implemented adversarial control experiments using straw models. These experiments serve to demonstrate the robustness and efficacy of our predictive models. We conducted a comprehensive evaluation of our method by comparing it to baselines and state-of-the-art methods. Two recently updated datasets, namely the BindingDB and PDBBind, were used for this purpose. Our findings indicate that our method outperforms the alternative methods in terms of three performance measures when using warm-start data splitting settings. Moreover, when considering physiochemical-based cold-start data splitting settings, our method demonstrates superior predictive performance, particularly in terms of the concordance index.

CONCLUSION: The results of our study affirm the practical value of our method and its superiority over alternative approaches in predicting drug-target binding affinity across multiple validation sets. This highlights the potential of our approach in accelerating drug repurposing efforts, facilitating novel drug discovery, and ultimately enhancing disease treatment. The data and source code for this study were deposited in the GitHub repository, https://github.com/mojtabaze7/DCGAN-DTA . Furthermore, the web server for our method is accessible at https://dcgan.shinyapps.io/bindingaffinity/ .

PMID:38724911 | DOI:10.1186/s12864-024-10326-x

Mol Syst Biol. 2024 May 9. doi: 10.1038/s44320-024-00040-x. Online ahead of print.

ABSTRACT

More than 500 kinases are implicated in the control of most cellular process in mammals, and deregulation of their activity is linked to cancer and inflammatory disorders. 80 clinical kinase inhibitors (CKIs) have been approved for clinical use and hundreds are in various stages of development. However, CKIs inhibit other kinases in addition to the intended target(s), causing both enhanced clinical effects and undesired side effects that are only partially predictable based on in vitro selectivity profiling. Here, we report an integrative approach grounded on the use of chromatin modifications as unbiased, information-rich readouts of the functional effects of CKIs on macrophage activation. This approach exceeded the performance of transcriptome-based approaches and allowed us to identify similarities and differences among CKIs with identical intended targets, to recognize novel CKI specificities and to pinpoint CKIs that may be repurposed to control inflammation, thus supporting the utility of this strategy to improve selection and use of CKIs in clinical settings.

PMID:38724853 | DOI:10.1038/s44320-024-00040-x

Nat Commun. 2024 May 9;15(1):3927. doi: 10.1038/s41467-024-48077-8.

ABSTRACT

Sputum culture reversion after conversion is an indicator of tuberculosis (TB) treatment failure. We analyze data from the endTB multi-country prospective observational cohort (NCT03259269) to estimate the frequency (primary endpoint) among individuals receiving a longer (18-to-20 month) regimen for multidrug- or rifampicin-resistant (MDR/RR) TB who experienced culture conversion. We also conduct Cox proportional hazard regression analyses to identify factors associated with reversion, including comorbidities, previous treatment, cavitary disease at conversion, low body mass index (BMI) at conversion, time to conversion, and number of likely-effective drugs. Of 1,286 patients, 54 (4.2%) experienced reversion, a median of 173 days (97-306) after conversion. Cavitary disease, BMI < 18.5, hepatitis C, prior treatment with second-line drugs, and longer time to initial culture conversion were positively associated with reversion. Reversion was uncommon. Those with cavitary disease, low BMI, hepatitis C, prior treatment with second-line drugs, and in whom culture conversion is delayed may benefit from close monitoring following conversion.

PMID:38724531 | DOI:10.1038/s41467-024-48077-8

Cell Genom. 2024 May 8;4(5):100557. doi: 10.1016/j.xgen.2024.100557.

ABSTRACT

We explored the dysregulation of G-protein-coupled receptor (GPCR) ligand systems in cancer transcriptomics datasets to uncover new therapeutics opportunities in oncology. We derived an interaction network of receptors with ligands and their biosynthetic enzymes. Multiple GPCRs are differentially regulated together with their upstream partners across cancer subtypes and are associated to specific transcriptional programs and to patient survival patterns. The expression of both receptor-ligand (or enzymes) partners improved patient stratification, suggesting a synergistic role for the activation of GPCR networks in modulating cancer phenotypes. Remarkably, we identified many such axes across several cancer molecular subtypes, including many involving receptor-biosynthetic enzymes for neurotransmitters. We found that GPCRs from these actionable axes, including, e.g., muscarinic, adenosine, 5-hydroxytryptamine, and chemokine receptors, are the targets of multiple drugs displaying anti-growth effects in large-scale, cancer cell drug screens, which we further validated. We have made the results generated in this study freely available through a webapp (gpcrcanceraxes.bioinfolab.sns.it).

PMID:38723607 | DOI:10.1016/j.xgen.2024.100557

Bioorg Chem. 2024 May 3;147:107425. doi: 10.1016/j.bioorg.2024.107425. Online ahead of print.

ABSTRACT

Non-alcoholic fatty liver disease (NAFLD) comprises a broad range of liver disease including hepatocellular carcinoma (HCC) with is no FDA-approved drug. Liver pyruvate kinase (PKL) is a major regulator of metabolic flux and ATP generation in liver presenting a potential target for the treatment of NAFLD. Based on our recent finding of JNK-5A's effectiveness in inhibiting PKLR expression through a drug repositioning pipeline, this study aims to improve its efficacy further. We synthesized a series of JNK-5A analogues with targeted modifications, guided by molecular docking studies. These compounds were evaluated for their activities on PKL expression, cell viability, triacylglyceride (TAG) levels, and the expressions of steatosis-related proteins in the human HepG2 cell line. Subsequently, the efficacy of these compounds was assessed in reducing TAG level and toxicity. Compounds 40 (SET-151) and 41 (SET-152) proved to be the most efficient in reducing TAG levels (11.51 ± 0.90 % and 10.77 ± 0.67 %) and demonstrated lower toxicity (61.60 ± 5.00 % and 43.87 ± 1.42 %) in HepG2 cells. Additionally, all synthesized compounds were evaluated for their anti-cancer properties revealing that compound 74 (SET-171) exhibited the highest toxicity in cell viability with IC50 values of 8.82 µM and 2.97 µM in HepG2 and Huh7 cell lines, respectively. To summarize, compounds 40 (SET-151) and 41 (SET-152) show potential for treating NAFLD, while compound 74 (SET-171) holds potential for HCC therapy.

PMID:38714117 | DOI:10.1016/j.bioorg.2024.107425

J Chemother. 2024 May 6:1-18. doi: 10.1080/1120009X.2024.2345027. Online ahead of print.

ABSTRACT

Chemotherapy-induced intestinal mucositis is a major side effect of cancer treatment. Statins are 3-hydroxy-3-methyl glutaryl coenzyme reductase inhibitors used to treat hypercholesterolemia and atherosclerotic diseases. Recent studies have demonstrated that atorvastatin (ATV) has antioxidant, anti-inflammatory, and resulting from the regulation of different molecular pathways. In the present study, we investigated the effects of ATV on intestinal homeostasis in 5-fluorouracil (5-FU)-induced mucositis. Our results showed that ATV protected the intestinal mucosa from epithelial damage caused by 5-FU mainly due to inflammatory infiltrate and intestinal permeability reduction, downregulation of inflammatory markers, such as Tlr4, MyD88, NF-κB, Tnf-a, Il1β, and Il6 dose-dependent. ATV also improved epithelial barrier function by upregulating the mRNA transcript levels of mucin 2 (MUC2), and ZO-1 and occludin tight junction proteins. The results suggest that the ATV anti-inflammatory and protective effects on 5-FU-induced mice mucositis involve the inhibition of the TLR4/MYD88/NPRL3/NF-κB, iNos, and caspase 3.

PMID:38711347 | DOI:10.1080/1120009X.2024.2345027

Cancer Rep (Hoboken). 2024 May;7(5):e2078. doi: 10.1002/cnr2.2078.

ABSTRACT

BACKGROUND: Statins, frequently prescribed medications, work by inhibiting the rate-limiting enzyme HMG-CoA reductase (HMGCR) in the mevalonate pathway to reduce cholesterol levels. Due to their multifaceted benefits, statins are being adapted for use as cost-efficient, safe and effective anti-cancer treatments. Several studies have shown that specific types of cancer are responsive to statin medications since they rely on the mevalonate pathway for their growth and survival.

RECENT FINDINGS: Statin are a class of drugs known for their potent inhibition of cholesterol production and are typically prescribed to treat high cholesterol levels. Nevertheless, there is growing interest in repurposing statins for the treatment of malignant neoplastic diseases, often in conjunction with chemotherapy and radiotherapy. The mechanism behind statin treatment includes targeting apoptosis through the BCL2 signaling pathway, regulating the cell cycle via the p53-YAP axis, and imparting epigenetic modulations by altering methylation patterns on CpG islands and histone acetylation by downregulating DNMTs and HDACs respectively. Notably, some studies have suggested a potential chemo-preventive effect, as decreased occurrence of tumor relapse and enhanced survival rate were reported in patients undergoing long-term statin therapy. However, the definitive endorsement of statin usage in cancer therapy hinges on population based clinical studies with larger patient cohorts and extended follow-up periods.

CONCLUSIONS: The potential of anti-cancer properties of statins seems to reach beyond their influence on cholesterol production. Further investigations are necessary to uncover their effects on cancer promoting signaling pathways. Given their distinct attributes, statins might emerge as promising contenders in the fight against tumorigenesis, as they appear to enhance the efficacy and address the limitations of conventional cancer treatments.

PMID:38711272 | DOI:10.1002/cnr2.2078

Curr Rev Clin Exp Pharmacol. 2024 Feb 9;19(3):259-268. doi: 10.2174/0127724328274939231121114142.

ABSTRACT

OBJECTIVE: Pharmacotherapy is commonly used during quit attempts and has shown an increase in the likelihood of achieving abstinence. However, with established pharmacotherapies, abstinence rates following a quit attempt remain low, and relapse is common. This review aims to investigate the efficacy and harm profiles of current and emerging pharmacotherapies.

METHODS: Literature review of current and emerging pharmacotherapies for smoking cessation and tobacco use disorder.

RESULTS: Emerging pharmacotherapies include new formulations of existing therapies, drug repurposing and some new treatments. New treatments are welcome and may incorporate different mechanisms of action or different safety and tolerability profiles compared to existing treatments. However, emerging pharmacotherapies have yet to demonstrate greater efficacy compared to existing treatments. The emergence of Electronic Nicotine Delivery Systems (ENDS) or 'vaping' is a feature of the current debate around tobacco use disorder. ENDS appear to facilitate switching but not quitting and are controversial as a harm minimisation strategy.

LIMITATIONS: Studies included a broad range of therapies and trial designs that should be compared with their differences taken into consideration.

CONCLUSION: Strategies to successfully quit smoking vary between individuals and may extend beyond pharmacotherapy and involve complex psychosocial factors and pathways.

PMID:38708918 | DOI:10.2174/0127724328274939231121114142

Malar J. 2024 May 3;23(1):132. doi: 10.1186/s12936-024-04967-2.

ABSTRACT

BACKGROUND: Drug repurposing offers a strategic alternative to the development of novel compounds, leveraging the known safety and pharmacokinetic profiles of medications, such as linezolid and levofloxacin for tuberculosis (TB). Anti-malarial drugs, including quinolones and artemisinins, are already applied to other diseases and infections and could be promising for TB treatment.

METHODS: This review included studies on the activity of anti-malarial drugs, specifically quinolones and artemisinins, against Mycobacterium tuberculosis complex (MTC), summarizing results from in vitro, in vivo (animal models) studies, and clinical trials. Studies on drugs not primarily developed for TB (doxycycline, sulfonamides) and any novel developed compounds were excluded. Analysis focused on in vitro activity (minimal inhibitory concentrations), synergistic effects, pre-clinical activity, and clinical trials.

RESULTS: Nineteen studies, including one ongoing Phase 1 clinical trial, were analysed: primarily investigating quinolones like mefloquine and chloroquine, and, to a lesser extent, artemisinins. In vitro findings revealed high MIC values for anti-malarials versus standard TB drugs, suggesting a limited activity. Synergistic effects with anti-TB drugs were modest, with some synergy observed in combinations with isoniazid or pyrazinamide. In vivo animal studies showed limited activity of anti-malarials against MTC, except for one study of the combination of chloroquine with isoniazid.

CONCLUSIONS: The repurposing of anti-malarials for TB treatment is limited by high MIC values, poor synergy, and minimal in vivo effects. Concerns about potential toxicity at effective dosages and the risk of antimicrobial resistance, especially where TB and malaria overlap, further question their repurposing. These findings suggest that focusing on novel compounds might be both more beneficial and rewarding.

PMID:38702649 | DOI:10.1186/s12936-024-04967-2

Brief Bioinform. 2024 Mar 27;25(3):bbae199. doi: 10.1093/bib/bbae199.

ABSTRACT

Gliomas are the most common type of malignant brain tumors, with glioblastoma multiforme (GBM) having a median survival of 15 months due to drug resistance and relapse. The treatment of gliomas relies on surgery, radiotherapy and chemotherapy. Only 12 anti-brain tumor chemotherapies (AntiBCs), mostly alkylating agents, have been approved so far. Glioma subtype-specific metabolic models were reconstructed to simulate metabolite exchanges, in silico knockouts and the prediction of drug and drug combinations for all three subtypes. The simulations were confronted with literature, high-throughput screenings (HTSs), xenograft and clinical trial data to validate the workflow and further prioritize the drug candidates. The three subtype models accurately displayed different degrees of dependencies toward glutamine and glutamate. Furthermore, 33 single drugs, mainly antimetabolites and TXNRD1-inhibitors, as well as 17 drug combinations were predicted as potential candidates for gliomas. Half of these drug candidates have been previously tested in HTSs. Half of the tested drug candidates reduce proliferation in cell lines and two-thirds in xenografts. Most combinations were predicted to be efficient for all three glioma types. However, eflornithine/rifamycin and cannabidiol/adapalene were predicted specifically for GBM and low-grade glioma, respectively. Most drug candidates had comparable efficiency in preclinical tests, cerebrospinal fluid bioavailability and mode-of-action to AntiBCs. However, fotemustine and valganciclovir alone and eflornithine and celecoxib in combination with AntiBCs improved the survival compared to AntiBCs in two-arms, phase I/II and higher glioma clinical trials. Our work highlights the potential of metabolic modeling in advancing glioma drug discovery, which accurately predicted metabolic vulnerabilities, repurposable drugs and combinations for the glioma subtypes.

PMID:38701414 | DOI:10.1093/bib/bbae199

Brief Bioinform. 2024 Mar 27;25(3):bbae207. doi: 10.1093/bib/bbae207.

ABSTRACT

Cancer stem cells (CSCs) are a subpopulation of cancer cells within tumors that exhibit stem-like properties and represent a potentially effective therapeutic target toward long-term remission by means of differentiation induction. By leveraging an artificial intelligence approach solely based on transcriptomics data, this study scored a large library of small molecules based on their predicted ability to induce differentiation in stem-like cells. In particular, a deep neural network model was trained using publicly available single-cell RNA-Seq data obtained from untreated human-induced pluripotent stem cells at various differentiation stages and subsequently utilized to screen drug-induced gene expression profiles from the Library of Integrated Network-based Cellular Signatures (LINCS) database. The challenge of adapting such different data domains was tackled by devising an adversarial learning approach that was able to effectively identify and remove domain-specific bias during the training phase. Experimental validation in MDA-MB-231 and MCF7 cells demonstrated the efficacy of five out of six tested molecules among those scored highest by the model. In particular, the efficacy of triptolide, OTS-167, quinacrine, granisetron and A-443654 offer a potential avenue for targeted therapies against breast CSCs.

PMID:38701411 | DOI:10.1093/bib/bbae207

J Mol Neurosci. 2024 May 3;74(2):51. doi: 10.1007/s12031-024-02228-0.

ABSTRACT

Alzheimer's disease (AD) is a neurodegenerative disorder and the most common cause of dementia. Programmed cell death (PCD) is mainly characterized by unique morphological features and energy-dependent biochemical processes. The predominant pathway leading to cell death in AD has not been thoroughly analyzed, although there is evidence of neuron loss in AD and numerous pathways of PCD have been associated with this process. A better understanding of the systems biology underlying the relationship between AD and PCD could lead to the development of new therapeutic approaches. To this end, publicly available transcriptome data were examined using bioinformatic methods such as differential gene expression and weighted gene coexpression network analysis (WGCNA) to find PCD-related AD biomarkers. The diagnostic significance of these biomarkers was evaluated using a logistic regression-based predictive model. Using these biomarkers, a multifactorial regulatory network was developed. Last, a drug repositioning study was conducted to propose new drugs for the treatment of AD targeting PCD. The development of 3PM (predictive, preventive, and personalized) drugs for the treatment of AD would be enabled by additional research on the effects of these drugs on this disease.

PMID:38700745 | DOI:10.1007/s12031-024-02228-0