Mol Neurobiol. 2024 Mar 26. doi: 10.1007/s12035-024-04130-7. Online ahead of print.

ABSTRACT

The cell cycle is the sequence of events orchestrated by a complex network of cell cycle proteins. Unlike normal cells, mature neurons subsist in a quiescent state of the cell cycle, and aberrant cell cycle activation triggers neuronal death accompanied by neurodegeneration. The periodicity of cell cycle events is choreographed by various mechanisms, including DNA damage repair, oxidative stress, neurotrophin activity, and ubiquitin-mediated degradation. Given the relevance of cell cycle processes in cancer and neurodegeneration, this review delineates the overlapping cell cycle events, signaling pathways, and mechanisms associated with cell cycle aberrations in cancer and the major neurodegenerative disorders. We suggest that dysregulation of some common fundamental signaling processes triggers anomalous cell cycle activation in cancer cells and neurons. We discussed the possible use of cell cycle inhibitors for neurodegenerative disorders and described the associated challenges. We propose that a greater understanding of the common mechanisms driving cell cycle aberrations in cancer and neurodegenerative disorders will open a new avenue for the development of repurposed drugs.

PMID:38532240 | DOI:10.1007/s12035-024-04130-7

Int Microbiol. 2024 Mar 27. doi: 10.1007/s10123-024-00506-w. Online ahead of print.

ABSTRACT

Drug repurposing constitutes a strategy to combat antimicrobial resistance, by using agents with known safety, pharmacokinetics, and pharmacodynamics. Previous studies have implemented new fusidic acid (FA) front-loading-dose regimens, allowing higher serum levels than those achievable with ordinary doses. As susceptibility breakpoints are affected by serum level, we evaluated the repurposing of FA as an antimicrobial product against enterococci. FA minimum inhibitory concentrations (MICs) against standard enterococci strains; Enterococcus faecalis ATCC 29212 and Enterococcus faecium ATCC 27270 were 2 and 4 µg/mL, respectively. The MIC against 98 enterococcal clinical isolates was ≤ 8 µg/mL; all would be susceptible if categorized according to recalculated breakpoints (≥ 16 µg/mL), based on the serum level achieved using the front-loading regimen. FA administration in vivo, using the BALB/c mouse infection model, significantly reduced bacterial burden by two to three log10 units in the liver and spleen of mice infected with vancomycin-susceptible and -resistant strains. Exposure of the standard enterococcal strains to increasing, but not fixed, FA concentrations resulted in resistant strains (MIC = 128 µg/mL), with thicker cell walls and slower growth rates. Only one mutation (M651I) was detected in the fusA gene of the resistant strain derived from serial passage of E. faecium ATCC 27270, which was retained in the revertant strain after passage in the FA-free medium. In conclusion, FA can be repurposed as an antimicrobial drug against enterococci with a low probability of mutational resistance development, and can be employed for treatment of infections attributable to vancomycin-resistant enterococci.

PMID:38532184 | DOI:10.1007/s10123-024-00506-w

FEBS Open Bio. 2024 Mar 26. doi: 10.1002/2211-5463.13796. Online ahead of print.

ABSTRACT

Drug repurposing is promising because approving a drug for a new indication requires fewer resources than approving a new drug. Signature reversion detects drug perturbations most inversely related to the disease-associated gene signature to identify drugs that may reverse that signature. We assessed the performance and biological relevance of three approaches for constructing disease-associated gene signatures (i.e., limma, DESeq2, and MultiPLIER) and prioritized the resulting drug repurposing candidates for four low-survival human cancers. Our results were enriched for candidates that had been used in clinical trials or performed well in the PRISM drug screen. Additionally, we found that pamidronate and nimodipine, drugs predicted to be efficacious against the brain tumor glioblastoma (GBM), inhibited the growth of a GBM cell line and cells isolated from a patient-derived xenograft (PDX). Our results demonstrate that by applying multiple disease-associated gene signature methods, we prioritized several drug repurposing candidates for low-survival cancers.

PMID:38531616 | DOI:10.1002/2211-5463.13796

Med Res Rev. 2024 Mar 26. doi: 10.1002/med.22033. Online ahead of print.

ABSTRACT

As the world population ages, there will be an increasing need for effective therapies for aging-associated neurodegenerative disorders, which remain untreatable. Dementia due to Alzheimer's disease (AD) is one of the leading neurological diseases in the aging population. Current therapeutic approaches to treat this disorder are solely symptomatic, making the need for new molecular entities acting on the causes of the disease extremely urgent. One of the potential solutions is to use compounds that are already in the market. The structures have known pharmacokinetics, pharmacodynamics, toxicity profiles, and patient data available in several countries. Several drugs have been used successfully to treat diseases different from their original purposes, such as autoimmunity and peripheral inflammation. Herein, we divulge the repurposing of drugs in the area of neurodegenerative diseases, focusing on the therapeutic potential of antineoplastics to treat dementia due to AD and dementia. We briefly touch upon the shared pathological mechanism between AD and cancer and drug repurposing strategies, with a focus on artificial intelligence. Next, we bring out the current status of research on the development of drugs, provide supporting evidence from retrospective, clinical, and preclinical studies on antineoplastic use, and bring in new areas, such as repurposing drugs for the prion-like spreading of pathologies in treating AD.

PMID:38530106 | DOI:10.1002/med.22033

J Biomol Struct Dyn. 2024 Mar 26:1-11. doi: 10.1080/07391102.2024.2331092. Online ahead of print.

ABSTRACT

Hematopoietic cell kinase (HCK) has emerged as a potential target for therapeutic intervention in cancer and HIV infection because of its critical role in critical signaling pathways. Repurposing FDA-approved drugs offers an efficient strategy to identify new treatment options. Here, we address the need for novel therapies in cancer and HIV by investigating the potential of repurposed drugs against HCK. Our goal was to identify promising drug candidates with high binding affinities and specific interactions within the HCK binding pocket. We employed an integrated computational approach combining molecular docking and extensive molecular dynamics (MD) simulations. Initially, we analyzed the binding affinities and interaction patterns of a library of FDA-approved drugs sourced from DrugBank. After careful analysis, we focused on two compounds, Nilotinib and Radotinib, which exhibit exceptional binding affinities and specificity to the HCK binding pocket, including the active site. Additionally, we assessed the pharmacological properties of Nilotinib and Radotinib, making them attractive candidates for further drug development. Extensive all-atom MD simulations spanning 200 nanoseconds (ns) elucidated the conformational dynamics and stability of the HCK-Nilotinib and HCK-Radotinib complexes. These simulations demonstrate the robustness of these complexes over extended timescales. Our findings highlighted the potential of Nilotinib and Radotinib as promising candidates against HCK that offer valuable insights into their binding mechanisms. This computational approach provides a comprehensive understanding of drug interactions with HCK and sets the stage for future experimental validation and drug development endeavors.Communicated by Ramaswamy H. Sarma.

PMID:38529911 | DOI:10.1080/07391102.2024.2331092

J Biomol Struct Dyn. 2024 Mar 26:1-11. doi: 10.1080/07391102.2024.2323699. Online ahead of print.

ABSTRACT

The serine/threonine kinase (STK) plays a central role as the primary kinase in poxviruses, directing phosphoryl transfer reactions. Such reactions are pivotal for the activation of certain proteins during viral replication, assembly, and maturation. Therefore, targeting this key protein is anticipated to impede virus replication. In this work, a structural bioinformatics approach was employed to evaluate the potential of drug-like kinase inhibitors in binding to the ATP-binding pocket on the STK of the Mpox virus. Virtual screening of known kinase inhibitors revealed that the top 10 inhibitors exhibited binding affinities ranging from -8.59 to -12.05 kcal/mol. The rescoring of compounds using the deep-learning default model in GNINA was performed to predict accurate binding poses. Subsequently, the top three inhibitors underwent unbiased molecular dynamics (MD) simulations for 100 ns. Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) analysis and Principal Component Analysis (PCA) suggested tepotinib as a competitive inhibitor for Mpox virus STK as evidenced by its binding free energy and the induction of similar conformational behavior of the enzyme. Nevertheless, it is sensible to experimentally test all top 10 compounds, as scoring functions and energy calculations may not consistently align with experimental findings. These insights are poised to provide an attempt to identify an effective inhibitor for the Mpox virus.Communicated by Ramaswamy H. Sarma.

PMID:38529847 | DOI:10.1080/07391102.2024.2323699

Alzheimers Dement (N Y). 2024 Jan 26;10(1):e12445. doi: 10.1002/trc2.12445. eCollection 2024 Jan-Mar.

ABSTRACT

INTRODUCTION: Janus kinase (JAK) inhibitors were recently identified as promising drug candidates for repurposing in Alzheimer's disease (AD) due to their capacity to suppress inflammation via modulation of JAK/STAT signaling pathways. Besides interaction with primary therapeutic targets, JAK inhibitor drugs frequently interact with unintended, often unknown, biological off-targets, leading to associated effects. Nevertheless, the relevance of JAK inhibitors' off-target interactions in the context of AD remains unclear.

METHODS: Putative off-targets of baricitinib and tofacitinib were predicted using a machine learning (ML) approach. After screening scientific literature, off-targets were filtered based on their relevance to AD. Targets that had not been previously identified as off-targets of baricitinib or tofacitinib were subsequently tested using biochemical or cell-based assays. From those, active concentrations were compared to bioavailable concentrations in the brain predicted by physiologically based pharmacokinetic (PBPK) modeling.

RESULTS: With the aid of ML and in vitro activity assays, we identified two enzymes previously unknown to be inhibited by baricitinib, namely casein kinase 2 subunit alpha 2 (CK2-α2) and dual leucine zipper kinase (MAP3K12), both with binding constant (K d) values of 5.8 μM. Predicted maximum concentrations of baricitinib in brain tissue using PBPK modeling range from 1.3 to 23 nM, which is two to three orders of magnitude below the corresponding binding constant.

CONCLUSION: In this study, we extended the list of baricitinib off-targets that are potentially relevant for AD progression and predicted drug distribution in the brain. The results suggest a low likelihood of successful repurposing in AD due to low brain permeability, even at the maximum recommended daily dose. While additional research is needed to evaluate the potential impact of the off-target interaction on AD, the combined approach of ML-based target prediction, in vitro confirmation, and PBPK modeling may help prioritize drugs with a high likelihood of being effectively repurposed for AD.

HIGHLIGHTS: This study explored JAK inhibitors' off-targets in AD using a multidisciplinary approach.We combined machine learning, in vitro tests, and PBPK modelling to predict and validate new off-target interactions of tofacitinib and baricitinib in AD.Previously unknown inhibition of two enzymes (CK2-a2 and MAP3K12) by baricitinib were confirmed using in vitro experiments.Our PBPK model indicates that baricitinib low brain permeability limits AD repurposing.The proposed multidisciplinary approach optimizes drug repurposing efforts in AD research.

PMID:38528988 | PMC:PMC10962475 | DOI:10.1002/trc2.12445

BMC Cancer. 2024 Mar 25;24(1):371. doi: 10.1186/s12885-024-12142-8.

ABSTRACT

BACKGROUND: The need for intelligent and effective treatment of diseases and the increase in drug design costs have raised drug repurposing as one of the effective strategies in biomedicine. There are various computational methods for drug repurposing, one of which is using transcription signatures, especially single-cell RNA sequencing (scRNA-seq) data, which show us a clear and comprehensive view of the inside of the cell to compare the state of disease and health.

METHODS: In this study, we used 91,103 scRNA-seq samples from 29 patients with colorectal cancer (GSE144735 and GSE132465). First, differential gene expression (DGE) analysis was done using the ASAP website. Then we reached a list of drugs that can reverse the gene signature pattern from cancer to normal using the iLINCS website. Further, by searching various databases and articles, we found 12 drugs that have FDA approval, and so far, no one has reported them as a drug in the treatment of any cancer. Then, to evaluate the cytotoxicity and performance of these drugs, the MTT assay and real-time PCR were performed on two colorectal cancer cell lines (HT29 and HCT116).

RESULTS: According to our approach, 12 drugs were suggested for the treatment of colorectal cancer. Four drugs were selected for biological evaluation. The results of the cytotoxicity analysis of these drugs are as follows: tezacaftor (IC10 = 19 µM for HCT-116 and IC10 = 2 µM for HT-29), fenticonazole (IC10 = 17 µM for HCT-116 and IC10 = 7 µM for HT-29), bempedoic acid (IC10 = 78 µM for HCT-116 and IC10 = 65 µM for HT-29), and famciclovir (IC10 = 422 µM for HCT-116 and IC10 = 959 µM for HT-29).

CONCLUSIONS: Cost, time, and effectiveness are the main challenges in finding new drugs for diseases. Computational approaches such as transcriptional signature-based drug repurposing methods open new horizons to solve these challenges. In this study, tezacaftor, fenticonazole, and bempedoic acid can be introduced as promising drug candidates for the treatment of colorectal cancer. These drugs were evaluated in silico and in vitro, but it is necessary to evaluate them in vivo.

PMID:38528462 | DOI:10.1186/s12885-024-12142-8

Eur J Med Chem. 2024 Mar 15;269:116325. doi: 10.1016/j.ejmech.2024.116325. Online ahead of print.

ABSTRACT

By virtue of the drug repurposing strategy, the anti-osteoporosis drug raloxifene was identified as a novel PPARγ ligand through structure-based virtual high throughput screening (SB-VHTS) of FDA-approved drugs and TR-FRET competitive binding assay. Subsequent structural refinement of raloxifene led to the synthesis of a benzothiophene derivative, YGL-12. This compound exhibited potent PPARγ modulation with partial agonism, uniquely promoting adiponectin expression and inhibiting PPARγ Ser273 phosphorylation by CDK5 without inducing the expression of adipongenesis associated genes, including PPARγ, aP2, CD36, FASN and C/EBPα. This specific activity profile resulted in effective hypoglycemic properties, avoiding major TZD-related adverse effects like weight gain and hepatomegaly, which were demonstrated in db/db mice. Molecular docking studies showed that YGL-12 established additional hydrogen bonds with Ile281 and enhanced hydrogen-bond interaction with Ser289 as well as PPARγ Ser273 phosphorylation-related residues Ser342 and Glu343. These findings suggested YGL-12 as a promising T2DM therapeutic candidate, thereby providing a molecular framework for the development of novel PPARγ modulators with an enhanced therapeutic index.

PMID:38527378 | DOI:10.1016/j.ejmech.2024.116325

J Med Chem. 2024 Mar 25. doi: 10.1021/acs.jmedchem.3c02453. Online ahead of print.

ABSTRACT

Neutrophil-mediated immunotherapy is a promising strategy for treating Candida albicans infection due to its potential in dealing with drug-resistant events. Our previous study found that ACT001 exhibited good antifungal immunotherapeutic activity by inhibiting PD-L1 expression in neutrophils, but its strong cytotoxicity and high BBB permeability hindered its antifungal application. To address these deficiencies, a series of novel sulfide derivatives were designed and synthesized based on a slow-release prodrug strategy. Among these derivatives, compound 16 exhibited stronger inhibition of PD-L1 expression, less cytotoxicity to neutrophils, and lower BBB permeability than ACT001. Compound 16 also significantly enhanced neutrophil-mediated antifungal immunity in C. albicans infected mice, with acceptable pharmacokinetic properties and good oral safety. Moreover, pharmacological mechanism studies demonstrated that ACT001 and compound 16 reduced PD-L1 expression in neutrophils by directly targeting STAT3. Briefly, this study provided a novel prototype compound 16 which exhibited great potential in neutrophil-mediated antifungal immunotherapy.

PMID:38526960 | DOI:10.1021/acs.jmedchem.3c02453

Adv Biomed Res. 2024 Jan 30;13:9. doi: 10.4103/abr.abr_170_23. eCollection 2024.

ABSTRACT

Artificial intelligence talks about modeling intelligent behavior through a computer with the least human involvement. Drug repositioning techniques based on artificial intelligence accelerate the research process and decrease the cost of experimental studies. Dysregulation of fibroblast growth factor (FGF) receptors as the tyrosine kinase family of receptors plays a vital role in a wide range of malignancies. Because of their functional significance, they were considered promising drug targets for the therapy of various cancers. This review has summarized small molecules capable of inhibiting FGF receptors that progressed using artificial intelligence and repositioning drugs examined in clinical trials associated with cancer therapy. This review is based on a literature search in PubMed, Web of Science, Scopus EMBASE, and Google Scholar databases to gather the necessary information in each chapter by employing keywords like artificial intelligence, computational drug design, drug repositioning, and FGF receptor inhibitors. To achieve this goal, a spacious literature review of human studies in these fields-published over the last 20 decades-was performed. According to published reports, nonselective FGF receptor inhibitors can be used for cancer management, and multitarget kinase inhibitors are the first drug class approved due to more advanced clinical studies. For example, AZD4547 and BGJ398 are gradually entering the consumption cycle and are good options as combined treatments. Artificial intelligence and drug repositioning methods can help preselect suitable drug targets more successfully for future inhibition of carcinogenicity.

PMID:38525398 | PMC:PMC10958741 | DOI:10.4103/abr.abr_170_23

Curr Comput Aided Drug Des. 2024 Mar 20. doi: 10.2174/0115734099297360240312043642. Online ahead of print.

ABSTRACT

BACKGROUND: Drug-resistant Staphylococcus aureus represents a substantial healthcare challenge worldwide, and its range of available therapeutic options continues to diminish progressively. Thus, this study aimed to identify potential inhibitors against FemA, a crucial protein involved in the cell wall biosynthesis of S. aureus.

MATERIALS AND METHODS: The screening process involved a comprehensive structure-based virtual screening on the StreptomDB database to identify ligands with potential inhibitory effects on FemA using AutoDock Vina. The most desirable ligands with the highest binding affinity and pharmacokinetic properties were selected. Two ligands with the highest number of hydrogen bonds and hydrophobic interactions were further analyzed by molecular dynamics (MD) using the GROMACS version 2018 simulation package.

RESULTS: Six H-donor conserved residues were selected as protein active sites, including Arg- 220, Tyr-38, Gln-154, Asn-73, Arg-74, and Thr-24. Through virtual screening, a total of nine compounds with the highest binding affinity to the FemA protein were identified. Frigocyclinone and C21H21N3O4 exhibited the highest binding affinity and demonstrated favorable pharmacokinetic properties. Molecular dynamics analysis of the FemA-ligand complexes further indicated desirable stability and reliability of complexes, reinforcing the potential efficacy of these ligands as inhibitors of FemA protein.

CONCLUSION: Our findings suggest that Frigocyclinone and C21H21N3O4 are promising inhibitors of FemA in S. aureus. To further validate these computational results, experimental studies are planned to confirm the inhibitory effects of these compounds on various S. aureus strains. Combining computational screening with experimental validation contributes valuable insights to the field of drug discovery in comparison to the classical drug discovery approaches.

PMID:38523540 | DOI:10.2174/0115734099297360240312043642

Arch Microbiol. 2024 Mar 23;206(4):190. doi: 10.1007/s00203-024-03917-5.

ABSTRACT

Owing to the extensive prevalence of resistant bacteria to numerous antibiotic classes, antimicrobial resistance (AMR) poses a well-known hazard to world health. As an alternate approach in the field of antimicrobial drug discovery, repurposing the available medications which are also called antibiotic resistance breakers has been pursued for the treatment of infections with antimicrobial resistance pathogens. In this study, we used Haloperidol, Metformin and Hydroxychloroquine as repurposing drugs in in vitro (Antibacterial Antibiotic Sensitivity Test and Minimum Inhibitory Concentration-MIC) and in vivo (Shigellosis in Swiss albino mice) tests in combination with traditional antibiotics (Oxytetracycline, Erythromycin, Doxycycline, Gentamicin, Ampicillin, Chloramphenicol, and Penicillin) against a group of AMR resistance bacteria (Bacillus cereus, Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Shigella boydii). After observing the results of the conducted in vitro experiments we studied the effects of the above non antibiotic drugs in combination with the said antibiotics. As an repurposing adjuvant antibiotic drug, Metformin exhibited noteworthy activity in almost all in vitro, in vivo and in silico tests (Zone of inhibition for 30 to 43 mm for E.coli in combination with Doxycycline; MIC value decreased 50 µM to 0.781 µM with Doxycycline on S. boydii).In rodents Doxycycline and Metformin showed prominent against Shigellosis in White blood cell count (6.47 ± 0.152 thousand/mm3) and Erythrocyte sedimentation rate (10.5 ± 1.73 mm/hr). Our findings indicated that Metformin and Doxycycline combination has a crucial impact on Shigellosis. The molecular docking study was performed targeting the Acriflavine resistance protein B (AcrB) (PDB ID: 4CDI) and MexA protein (PDB ID: 6IOK) protein with Metformin (met8) drug which showed the highest binding energy with - 6.4 kcal/mol and - 5.5 kcal/mol respectively. Further, molecular dynamics simulation revealed that the docked complexes were relatively stable during the 100 ns simulation period. This study suggest Metformin and other experimented drugs can be used as adjuvants boost up antibiosis but further study is needed to find out the safety and efficacy of this non-antibiotic drug as potent antibiotic adjuvant.

PMID:38519821 | DOI:10.1007/s00203-024-03917-5

Biomed Pharmacother. 2024 Mar 21;174:116459. doi: 10.1016/j.biopha.2024.116459. Online ahead of print.

ABSTRACT

Ubiquitin-specific protease (USP), an enzyme catalyzing protein deubiquitination, is involved in biological processes related to metabolic disorders and cancer proliferation. We focused on constructing predictive models tailored to unveil compounds boasting USP21 inhibitory attributes. Six models, Extra Trees Classifier, Random Forest Classifier, LightGBM Classifier, XGBoost Classifier, Bagging Classifier, and a convolutional neural network harnessed from empirical data were selected for the screening process. These models guided our selection of 26 compounds from the FDA-approved drug library for further evaluation. Notably, nifuroxazide emerged as the most potent inhibitor, with a half-maximal inhibitory concentration of 14.9 ± 1.63 μM. The stability of protein-ligand complexes was confirmed using molecular modeling. Furthermore, nifuroxazide treatment of HepG2 cells not only inhibited USP21 and its established substrate ACLY but also elevated p-AMPKα, a downstream functional target of USP21. Intriguingly, we unveiled the previously unknown capacity of nifuroxazide to increase the levels of miR-4458, which was identified as downregulating USP21. This discovery was substantiated by manipulating miR-4458 levels in HepG2 cells, resulting in corresponding changes in USP21 protein levels in line with its predicted interaction with ACLY. Lastly, we confirmed the in vivo efficacy of nifuroxazide in inhibiting USP21 in mice livers, observing concurrent alterations in ACLY and p-AMPKα levels. Collectively, our study establishes nifuroxazide as a promising USP21 inhibitor with potential implications for addressing metabolic disorders and cancer proliferation. This multidimensional investigation sheds light on the intricate regulatory mechanisms involving USP21 and its downstream effects, paving the way for further exploration and therapeutic development.

PMID:38518599 | DOI:10.1016/j.biopha.2024.116459

PLoS One. 2024 Mar 22;19(3):e0300708. doi: 10.1371/journal.pone.0300708. eCollection 2024.

ABSTRACT

Researchers are increasingly using insights derived from large-scale, electronic healthcare data to inform drug development and provide human validation of novel treatment pathways and aid in drug repurposing/repositioning. The objective of this study was to determine whether treatment of patients with multiple sclerosis with dimethyl fumarate, an activator of the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway, results in a change in incidence of type 2 diabetes and its complications. This retrospective cohort study used administrative claims data to derive four cohorts of adults with multiple sclerosis initiating dimethyl fumarate, teriflunomide, glatiramer acetate or fingolimod between January 2013 and December 2018. A causal inference frequentist model averaging framework based on machine learning was used to compare the time to first occurrence of a composite endpoint of type 2 diabetes, cardiovascular disease or chronic kidney disease, as well as each individual outcome, across the four treatment cohorts. There was a statistically significantly lower risk of incidence for dimethyl fumarate versus teriflunomide for the composite endpoint (restricted hazard ratio [95% confidence interval] 0.70 [0.55, 0.90]) and type 2 diabetes (0.65 [0.49, 0.98]), myocardial infarction (0.59 [0.35, 0.97]) and chronic kidney disease (0.52 [0.28, 0.86]). No differences for other individual outcomes or for dimethyl fumarate versus the other two cohorts were observed. This study effectively demonstrated the use of an innovative statistical methodology to test a clinical hypothesis using real-world data to perform early target validation for drug discovery. Although there was a trend among patients treated with dimethyl fumarate towards a decreased incidence of type 2 diabetes, cardiovascular disease and chronic kidney disease relative to other disease-modifying therapies-which was statistically significant for the comparison with teriflunomide-this study did not definitively support the hypothesis that Nrf2 activation provided additional metabolic disease benefit in patients with multiple sclerosis.

PMID:38517926 | DOI:10.1371/journal.pone.0300708

IEEE Int Conf Healthc Inform. 2023 Jun;2023:738-745. doi: 10.1109/ichi57859.2023.00135. Epub 2023 Dec 11.

ABSTRACT

Our study aims to address the challenges in drug development for glioblastoma, a highly aggressive brain cancer with poor prognosis. We propose a computational framework that utilizes machine learning-based propensity score matching to estimate counterfactual treatment effects and predict synergistic effects of drug combinations. Through our in-silico analysis, we identified promising drug candidates and drug combinations that warrant further investigation. To validate these computational findings, we conducted in-vitro experiments on two GBM cell lines, U87 and T98G. The experimental results demonstrated that some of the identified drugs and drug combinations indeed exhibit strong suppressive effects on GBM cell growth. Our end-to-end pipeline showcases the feasibility of integrating computational models with biological experiments to expedite drug repurposing and discovery efforts. By bridging the gap between in-silico analysis and in-vitro validation, we demonstrate the potential of this approach to accelerate the development of novel and effective treatments for glioblastoma.

PMID:38516034 | PMC:PMC10956733 | DOI:10.1109/ichi57859.2023.00135

J Exp Clin Cancer Res. 2024 Mar 22;43(1):88. doi: 10.1186/s13046-024-03012-z.

ABSTRACT

BACKGROUND: This study explores the repurposing of Auranofin (AF), an anti-rheumatic drug, for treating non-small cell lung cancer (NSCLC) adenocarcinoma and pancreatic ductal adenocarcinoma (PDAC). Drug repurposing in oncology offers a cost-effective and time-efficient approach to developing new cancer therapies. Our research focuses on evaluating AF's selective cytotoxicity against cancer cells, identifying RNAseq-based biomarkers to predict AF response, and finding the most effective co-therapeutic agents for combination with AF.

METHODS: Our investigation employed a comprehensive drug screening of AF in combination with eleven anticancer agents in cancerous PDAC and NSCLC patient-derived organoids (n = 7), and non-cancerous pulmonary organoids (n = 2). Additionally, we conducted RNA sequencing to identify potential biomarkers for AF sensitivity and experimented with various drug combinations to optimize AF's therapeutic efficacy.

RESULTS: The results revealed that AF demonstrates a preferential cytotoxic effect on NSCLC and PDAC cancer cells at clinically relevant concentrations below 1 µM, sparing normal epithelial cells. We identified Carbonic Anhydrase 12 (CA12) as a significant RNAseq-based biomarker, closely associated with the NF-κB survival signaling pathway, which is crucial in cancer cell response to oxidative stress. Our findings suggest that cancer cells with low CA12 expression are more susceptible to AF treatment. Furthermore, the combination of AF with the AKT inhibitor MK2206 was found to be particularly effective, exhibiting potent and selective cytotoxic synergy, especially in tumor organoid models classified as intermediate responders to AF, without adverse effects on healthy organoids.

CONCLUSION: Our research offers valuable insights into the use of AF for treating NSCLC and PDAC. It highlights AF's cancer cell selectivity, establishes CA12 as a predictive biomarker for AF sensitivity, and underscores the enhanced efficacy of AF when combined with MK2206 and other therapeutics. These findings pave the way for further exploration of AF in cancer treatment, particularly in identifying patient populations most likely to benefit from its use and in optimizing combination therapies for improved patient outcomes.

PMID:38515178 | DOI:10.1186/s13046-024-03012-z

Biomed Pharmacother. 2024 Mar 20;174:116442. doi: 10.1016/j.biopha.2024.116442. Online ahead of print.

ABSTRACT

Parkinson's disease (PD) is a complex neurodegenerative disorder with an unclear etiology. Despite significant research efforts, developing disease-modifying treatments for PD remains a major unmet medical need. Notably, drug repositioning is becoming an increasingly attractive direction in drug discovery, and computational approaches offer a relatively quick and resource-saving method for identifying testable hypotheses that promote drug repositioning. We used an artificial intelligence (AI)-based drug repositioning strategy to screen an extensive compound library and identify potential therapeutic agents for PD. Our AI-driven analysis revealed that efavirenz and nevirapine, approved for treating human immunodeficiency virus infection, had distinct profiles, suggesting their potential effects on PD pathophysiology. Among these, efavirenz attenuated α-synuclein (α-syn) propagation and associated neuroinflammation in the brain of preformed α-syn fibrils-injected A53T α-syn Tg mice and α-syn propagation and associated behavioral changes in the C. elegans BiFC model. Through in-depth molecular investigations, we found that efavirenz can modulate cholesterol metabolism and mitigate α-syn propagation, a key pathological feature implicated in PD progression by regulating CYP46A1. This study opens new avenues for further investigation into the mechanisms underlying PD pathology and the exploration of additional drug candidates using advanced computational methodologies.

PMID:38513596 | DOI:10.1016/j.biopha.2024.116442

Biomed Pharmacother. 2024 Mar 20;174:116435. doi: 10.1016/j.biopha.2024.116435. Online ahead of print.

ABSTRACT

The global shortage of corneal endothelial graft tissue necessitates the exploration of alternative therapeutic strategies. Rho-associated protein kinase inhibitors (ROCKi), recognized for their regenerative potential in cardiology, oncology, and neurology, have shown promise in corneal endothelial regeneration. This study investigates the repurposing potential of additional ROCKi compounds. Through screening a self-assembled library of ROCKi on B4G12 corneal endothelial cells, we evaluated their dose-dependent effects on proliferation, migration, and toxicity using live-cell imaging. Nine ROCKi candidates significantly enhanced B4G12 proliferation compared to the basal growth rate. These candidates were further assessed for their potential to accelerate wound closure as another indicator for tissue regeneration capacity, with most demonstrating notable efficacy. To assess the potential impact of candidate ROCKi on key corneal endothelial cell markers related to cell proliferation, leaky tight junctions and ion efflux capacity, we analyzed the protein expression of cyclin E1, CDK2, p16, ZO-1 and Na+/K+-ATPase, respectively. Immunocytochemistry and western blot analysis confirmed the preservation of corneal endothelial markers post-treatment with ROCKi hits. However, notable cytoplasm enlargement and nuclear fragmentation were detected after the treatment with SR-3677 and Thiazovivin, indicating possible cellular stress. In compared parameters, Chroman-1 at a concentration of 10 nM outperformed other ROCKi, requiring significantly 1000-fold lower effective concentration than established ROCKi Y-27632 and Fasudil. Altogether, this study underscores the potential of repurposing ROCKi for treating corneal endothelial dysfunctions, offering a viable alternative to conventional grafting methods, and highlights Chroman-1 as a promising candidate structure for hit-to-lead development.

PMID:38513591 | DOI:10.1016/j.biopha.2024.116435

Comput Biol Med. 2024 Mar 13;173:108292. doi: 10.1016/j.compbiomed.2024.108292. Online ahead of print.

ABSTRACT

Lung cancer is one of the most common malignant tumors around the world, which has the highest mortality rate among all cancers. Traditional Chinese medicine (TCM) has attracted increased attention in the field of lung cancer treatment. However, the abundance of ingredients in Chinese medicines presents a challenge in identifying promising ingredient candidates and exploring their mechanisms for lung cancer treatment. In this work, two network-based algorithms were combined to calculate the network relationships between ingredient targets and lung cancer targets in the human interactome. Based on the enrichment analysis of the constructed disease module, key targets of lung cancer were identified. In addition, molecular docking and enrichment analysis of the overlapping targets between lung cancer and ingredients were performed to investigate the potential mechanisms of ingredient candidates against lung cancer. Ten potential ingredients against lung cancer were identified and they may have similar effect on the development of lung cancer. The results obtained from this study offered valuable insights and provided potential avenues for the development of novel drugs aimed at treating lung cancer.

PMID:38513387 | DOI:10.1016/j.compbiomed.2024.108292