IEEE/ACM Trans Comput Biol Bioinform. 2022 Jan 21;PP. doi: 10.1109/TCBB.2022.3144429. Online ahead of print.

ABSTRACT

The matrix factorization model has become the cornerstone technique for computational drug repositioning due to its ease of implementation and excellent scalability. However, the matrix factorization model uses the inner product operation to represent the association between drugs and diseases, which is lacking in expressive ability. Moreover, the degree of similarity of drugs or diseases could not be implied on their respective latent factor vectors, which is not satisfy the common sense of drug discovery. Therefore, a neural metric factorization model for computational drug repositioning (NMFDR) is proposed in this work. We novelly consider the latent factor vector of drugs and diseases as a point in the high-dimensional coordinate system and propose a generalized Euclidean distance to represent the association between drugs and diseases to compensate for the shortcomings of the inner product operation. Furthermore, by embedding multiple drug (disease) metrics information into the encoding space of the latent factor vector, the information about the similarity between drugs (diseases) can be reflected in the distance between latent factor vectors. Finally, we conduct wide analysis experiments on three real datasets to demonstrate the effectiveness of the above improvement points and the superiority of the NMFDR model.

PMID:35061591 | DOI:10.1109/TCBB.2022.3144429

Parasitology. 2021 Nov;148(13):1680-1690. doi: 10.1017/S0031182021001402. Epub 2021 Aug 12.

ABSTRACT

Chagas disease is a potentially life-threatening protozoan infection affecting around 8 million people, for which only chemotherapies with limited efficacy and severe adverse secondary effects are available. The aetiological agent, Trypanosoma cruzi, displays varied cell invading tactics and triggers different host cell signals, including the Wnt/β-catenin pathway. Poly(ADP-ribose) (PAR) can be synthetized by certain members of the poly(ADP-ribose) polymerase (PARP) family: PARP-1/-2 and Tankyrases-1/2 (TNKS). PAR homoeostasis participates in the host cell response to T. cruzi infection and TNKS are involved in Wnt signalling, among other pathways. Therefore, we hypothesized that TNKS inhibitors (TNKSi) could hamper T. cruzi infection. We showed that five TNKSi (FLALL9, MN64, XAV939, G007LK and OULL9) diminished T. cruzi infection of Vero cells. As most TNKSi did not affect the viability of axenically cultivated parasites, our results suggested that TNKSi were interfering with parasite–host cell signalling. Infection by T. cruzi induced nuclear translocation of β-catenin, as well as upregulation of TNF-α expression and secretion. These changes were hampered by TNKSi. Further signals should be monitored in this model and in vivo. As a TNKSi has entered cancer clinical trials with promising results, our findings encourage further studies aiming at drug repurposing strategies.

PMID:35060470 | DOI:10.1017/S0031182021001402

J Chem Inf Model. 2022 Jan 20. doi: 10.1021/acs.jcim.1c00431. Online ahead of print.

ABSTRACT

In the event of an outbreak due to an emerging pathogen, time is of the essence to contain or to mitigate the spread of the disease. Drug repositioning is one of the strategies that has the potential to deliver therapeutics relatively quickly. The SARS-CoV-2 pandemic has shown that integrating critical data resources to drive drug-repositioning studies, involving host-host, host-pathogen, and drug-target interactions, remains a time-consuming effort that translates to a delay in the development and delivery of a life-saving therapy. Here, we describe a workflow we designed for a semiautomated integration of rapidly emerging data sets that can be generally adopted in a broad network pharmacology research setting. The workflow was used to construct a COVID-19 focused multimodal network that integrates 487 host-pathogen, 63 278 host-host protein, and 1221 drug-target interactions. The resultant Neo4j graph database named "Neo4COVID19" is made publicly accessible via a web interface and via API calls based on the Bolt protocol. Details for accessing the database are provided on a landing page (https://neo4covid19.ncats.io/). We believe that our Neo4COVID19 database will be a valuable asset to the research community and will catalyze the discovery of therapeutics to fight COVID-19.

PMID:35057621 | DOI:10.1021/acs.jcim.1c00431

Pharmaceutics. 2022 Jan 12;14(1):176. doi: 10.3390/pharmaceutics14010176.

ABSTRACT

Since 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been rapidly spreading worldwide, causing hundreds of millions of infections. Despite the development of vaccines, insufficient protection remains a concern. Therefore, the screening of drugs for the treatment of coronavirus disease 2019 (COVID-19) is reasonable and necessary. This study utilized bioinformatics for the selection of compounds approved by the U.S. Food and Drug Administration with therapeutic potential in this setting. In addition, the inhibitory effect of these compounds on the enzyme activity of transmembrane protease serine 2 (TMPRSS2), papain-like protease (PLpro), and 3C-like protease (3CLpro) was evaluated. Furthermore, the capability of compounds to attach to the spike-receptor-binding domain (RBD) was considered an important factor in the present assessment. Finally, the antiviral potency of compounds was validated using a plaque reduction assay. Our funnel strategy revealed that tamoxifen possesses an anti-SARS-CoV-2 property owing to its inhibitory performance in multiple assays. The proposed time-saving and feasible strategy may accelerate drug screening for COVID-19 and other diseases.

PMID:35057070 | DOI:10.3390/pharmaceutics14010176

Pharmaceutics. 2021 Dec 28;14(1):59. doi: 10.3390/pharmaceutics14010059.

ABSTRACT

The RAS-RAF-MEK-ERK pathway plays a key role in malevolent cell progression in many tumors. The high structural complexity in the upstream kinases limits the treatment progress. Thus, MEK inhibition is a promising strategy since it is easy to inhibit and is a gatekeeper for the many malignant effects of its downstream effector. Even though MEK inhibitors are under investigation in many cancers, drug resistance continues to be the principal limiting factor to achieving cures in patients with cancer. Hence, we accomplished a high-throughput virtual screening to overcome this bottleneck by the discovery of dual-targeting therapy in cancer treatment. Here, a total of 11,808 DrugBank molecules were assessed through high-throughput virtual screening for their activity against MEK. Further, the Glide docking, MLSF and prime-MM/GBSA methods were implemented to extract the potential lead compounds from the database. Two compounds, DB012661 and DB07642, were outperformed in all the screening analyses. Further, the study results reveal that the lead compounds also have a significant binding capability with the co-target PIM1. Finally, the SIE-based free energy calculation reveals that the binding of compounds was majorly affected by the van der Waals interactions with MEK receptor. Overall, the in silico binding efficacy of these lead compounds against both MEK and PIM1 could be of significant therapeutic interest to overcome drug resistance in the near future.

PMID:35056955 | DOI:10.3390/pharmaceutics14010059

Pharmaceutics. 2021 Dec 26;14(1):44. doi: 10.3390/pharmaceutics14010044.

ABSTRACT

Chronic inflammation and dysregulated epithelial differentiation, especially of hair follicle keratinocytes, have been suggested as the major pathogenetic pathways of hidradenitis suppurativa/acne inversa (HS). On the other hand, obesity and metabolic syndrome have additionally been considered as an important risk factor. With adalimumab, a drug has already been approved and numerous other compounds are in advanced-stage clinical studies. A systematic review was conducted to detect and corroborate HS pathogenetic mechanisms at the molecular level and identify HS molecular markers. The obtained data were used to confirm studied and off-label administered drugs and to identify additional compounds for drug repurposing. A robust, strongly associated group of HS biomarkers was detected. The triad of HS pathogenesis, namely upregulated inflammation, altered epithelial differentiation and dysregulated metabolism/hormone signaling was confirmed, the molecular association of HS with certain comorbid disorders, such as inflammatory bowel disease, arthritis, type I diabetes mellitus and lipids/atherosclerosis/adipogenesis was verified and common biomarkers were identified. The molecular suitability of compounds in clinical studies was confirmed and 31 potential HS repurposing drugs, among them 10 drugs already launched for other disorders, were detected. This systematic review provides evidence for the importance of molecular studies to advance the knowledge regarding pathogenesis, future treatment and biomarker-supported clinical course follow-up in HS.

PMID:35056940 | DOI:10.3390/pharmaceutics14010044

Pharmaceutics. 2021 Dec 21;14(1):3. doi: 10.3390/pharmaceutics14010003.

ABSTRACT

MicroRNAs (miRNAs) are short non-coding RNAs that play important roles in the body and affect various diseases, including cancers. Controlling miRNAs with small molecules is studied herein to provide new drug repurposing perspectives for miRNA-related diseases. Experimental methods are time- and effort-consuming, so computational techniques have been applied, relying mostly on biological feature similarities and a network-based scheme to infer new miRNA-small molecule associations. Collecting such features is time-consuming and may be impractical. Here we suggest an alternative method of similarity calculation, representing miRNAs and small molecules through continuous feature representation. This representation is learned by the proposed deep learning auto-encoder architecture. Our suggested representation was compared to previous works and achieved comparable results using 5-fold cross validation (92% identified within top 25% predictions), and better predictions for most of the case studies (avg. of 31% vs. 25% identified within the top 25% of predictions). The results proved the effectiveness of our proposed method to replace previous time- and effort-consuming methods.

PMID:35056899 | DOI:10.3390/pharmaceutics14010003

Molecules. 2022 Jan 14;27(2):505. doi: 10.3390/molecules27020505.

ABSTRACT

Amburana cearensis (Allemão) ACSm. belongs to the Fabaceae family and occurs in the Brazilian semiarid, Argentina, Paraguay, Bolivia, and Peru. Numerous studies that portray its ethnobotany, use in popular medicine, chemical composition, and biological activities exist in the literature. This review aimed to provide an overview of the chemical composition, ethnopharmacology, and biological activities associated with A. cearensis and its isolated constituents. Information was collected from internet searches in the Scopus, Medline, PubMed, Google Scholar, and ScienceDirect databases were performed covering publications from 1997-2020. An ethnopharmacological literature analysis revealed that A. cearensis is used to treat a wide range of respiratory disorders in addition to intestinal, circulatory, and inflammatory problems. Coumarins, flavonoids, phenolic glycosides, phenolic acids, phenylpropanoid derivatives, and triterpenoids, among others, have been reported as active compounds, with High-Performance Liquid Chromatography (HPLC) being the main analytical technique used. The A. cearensis extracts and compounds presented several biological activities, including antimicrobial, antinociceptive, anti-inflammatory, antioxidant, neuroprotective, and myorelaxant activities, among others. This review provides a useful bibliography for future investigations and A. cearensis applications; however, future studies should focus on its toxic effects and the mechanisms of action of its extracts and isolated constituents to guide clinical applications.

PMID:35056820 | DOI:10.3390/molecules27020505

Pharmaceuticals (Basel). 2022 Jan 14;15(1):94. doi: 10.3390/ph15010094.

ABSTRACT

Even if amyotrophic lateral sclerosis is still considered an orphan disease to date, its prevalence among the population is growing fast. Despite the efforts made by researchers and pharmaceutical companies, the cryptic information related to the biological and physiological onset mechanisms, as well as the complexity in identifying specific pharmacological targets, make it almost impossible to find effective treatments. Furthermore, because of complex ethical and economic aspects, it is usually hard to find all the necessary resources when searching for drugs for new orphan diseases. In this context, computational methods, based either on receptors or ligands, share the capability to improve the success rate when searching and selecting potential candidates for further experimentation and, consequently, reduce the number of resources and time taken when delivering a new drug to the market. In the present work, a computational strategy based on Molecular Topology, a mathematical paradigm capable of relating the chemical structure of a molecule to a specific biological or pharmacological property by means of numbers, is presented. The result was the creation of a reliable and accessible tool to help during the early in silico stages in the identification and repositioning of potential hits for ALS treatment, which can also apply to other orphan diseases. Considering that further computational and experimental results will be required for the final identification of viable hits, three linear discriminant equations combined with molecular docking simulations on specific proteins involved in ALS are reported, along with virtual screening of the Drugbank database as a practical example. In this particular case, as reported, a clinical trial has been already started for one of the drugs proposed in the present study.

PMID:35056151 | DOI:10.3390/ph15010094

Pharmaceuticals (Basel). 2021 Dec 28;15(1):38. doi: 10.3390/ph15010038.

ABSTRACT

Chronic pain determines a substantial burden on individuals, employers, healthcare systems, and society. Most of the affected patients report dissatisfaction with currently available treatments. There are only a few and poor therapeutic options-some therapeutic agents are an outgrowth of drugs targeting acute pain, while others have several serious side effects. One of the primary degradative enzymes for endocannabinoids, fatty acid amide hydrolase (FAAH) attracted attention as a significant molecular target for developing new therapies for neuropsychiatric and neurological diseases, including chronic pain. Using chemical graph mining, quantitative structure-activity relationship (QSAR) modeling, and molecular docking techniques we developed a multi-step screening protocol to identify repurposable drugs as FAAH inhibitors. After screening the DrugBank database using our protocol, 273 structures were selected, with five already approved drugs, montelukast, repaglinide, revefenacin, raloxifene, and buclizine emerging as the most promising repurposable agents for treating chronic pain. Molecular docking studies indicated that the selected compounds interact with the enzyme mostly non-covalently (except for revefenacin) through shape complementarity to the large substrate-binding pocket in the active site. A molecular dynamics simulation was employed for montelukast and revealed stable interactions with the enzyme. The biological activity of the selected compounds should be further confirmed by employing in vitro and in vivo studies.

PMID:35056095 | DOI:10.3390/ph15010038

Pharmaceuticals (Basel). 2021 Dec 25;15(1):31. doi: 10.3390/ph15010031.

ABSTRACT

Ischemic heart disease is a significant public health problem with high mortality and morbidity. Extensive scientific investigations from basic sciences to clinics revealed multilevel alterations from metabolic imbalance, altered electrophysiology, and defective Ca2+/Na+ homeostasis leading to lethal arrhythmias. Despite the recent identification of numerous molecular targets with potential therapeutic interest, a pragmatic observation on the current pharmacological R&D output confirms the lack of new therapeutic offers to patients. By contrast, from recent trials, molecules initially developed for other fields of application have shown cardiovascular benefits, as illustrated with some anti-diabetic agents, regardless of the presence or absence of diabetes, emphasizing the clear advantage of "old" drug repositioning. Ranolazine is approved as an antianginal agent and has a favorable overall safety profile. This drug, developed initially as a metabolic modulator, was also identified as an inhibitor of the cardiac late Na+ current, although it also blocks other ionic currents, including the hERG/Ikr K+ current. The latter actions have been involved in this drug's antiarrhythmic effects, both on supraventricular and ventricular arrhythmias (VA). However, despite initial enthusiasm and promising development in the cardiovascular field, ranolazine is only authorized as a second-line treatment in patients with chronic angina pectoris, notwithstanding its antiarrhythmic properties. A plausible reason for this is the apparent difficulty in linking the clinical benefits to the multiple molecular actions of this drug. Here, we review ranolazine's experimental and clinical knowledge on cardiac metabolism and arrhythmias. We also highlight advances in understanding novel effects on neurons, the vascular system, skeletal muscles, blood sugar control, and cancer, which may open the way to reposition this "old" drug alone or in combination with other medications.

PMID:35056088 | DOI:10.3390/ph15010031

ACS Biomater Sci Eng. 2022 Jan 20. doi: 10.1021/acsbiomaterials.1c01481. Online ahead of print.

ABSTRACT

Drug repurposing has been gaining increasing interest recently due to the reduction in development cost and reduced development timelines. Here, we report the antibacterial activity of the anticancer drug etoposide investigated in combination with the eggshell-derived hydroxyapatite (EHA). Hydroxyapatite (HA) is a well-known bioactive material with enhanced osteoconductivity and possesses superior drug delivery properties. In the present work, we have synthesized etoposide-loaded EHA by the wet precipitation method. The physicochemical characterization of the samples confirmed the composition and amount of drug encapsulation. Screening for antibacterial activity confirmed the antibacterial effect of etoposide against Staphylococcus aureus. Biofilm formation test on pristine and etoposide-loaded samples showed the inhibition of biofilm formation on etoposide loading, which was further studied by confocal laser scanning microscopy (CLSM) and colony forming units (CFUs). It has been found that etoposide-loaded HA exhibited a sustained release of the drug upto 168 h. Analysis of the inhibition mechanism of etoposide against S. aureus revealed damage to the cell membrane and has been quantified using flow cytometry by the uptake of propidium iodide. Etoposide-loaded eggshell-derived HA (EHA-ET) exhibited excellent bioactivity and cytocompatibility against mouse fibroblast cells (L929) and supressed the growth of osteosarcoma cells (MG-63). Our studies reveal that the EHA-ET has a great potential for treating osteosarcoma and osteomyelitis.

PMID:35050575 | DOI:10.1021/acsbiomaterials.1c01481

Autoimmunity. 2022 Jan 20:1-10. doi: 10.1080/08916934.2022.2027922. Online ahead of print.

ABSTRACT

Rheumatoid arthritis (RA) is an autoimmune disease that results in the destruction of tissue by attacks on the patient by his or her own immune system. Current treatment strategies are not sufficient to overcome RA. In the present study, various transcriptomic data from synovial fluids, synovial fluid-derived macrophages, and blood samples from patients with RA were analysed using bioinformatics approaches to identify tissue-specific repurposing drug candidates for RA. Differentially expressed genes (DEGs) were identified by integrating datasets for each tissue and comparing diseased to healthy samples. Tissue-specific protein-protein interaction (PPI) networks were generated and topologically prominent proteins were selected. Transcription-regulating biomolecules for each tissue type were determined from protein-DNA interaction data. Common DEGs and reporter biomolecules were used to identify drug candidates for repurposing using the hypergeometric test. As a result of bioinformatic analyses, 19 drugs were identified as repurposing candidates for RA, and text mining analyses supported our findings. We hypothesize that the FDA-approved drugs momelotinib, ibrutinib, and sodium butyrate may be promising candidates for RA. In addition, CHEMBL306380, Compound 19a (CHEMBL3116050), ME-344, XL-019, TG100801, JNJ-26483327, and NV-128 were identified as novel repurposing candidates for the treatment of RA. Preclinical and further validation of these drugs may provide new treatment options for RA.

PMID:35048767 | DOI:10.1080/08916934.2022.2027922

Front Pharmacol. 2022 Jan 3;12:790913. doi: 10.3389/fphar.2021.790913. eCollection 2021.

ABSTRACT

Cisplatin-induced acute kidney injury (CI-AKI) is a significant co-morbidity of chemotherapeutic regimens. While this condition is associated with substantially lower survival and increased economic burden, there is no pharmacological agent to effectively treat CI-AKI. The disease is hallmarked by acute tubular necrosis of the proximal tubular epithelial cells primarily due to increased oxidative stress. We investigated a drug delivery strategy to improve the pharmacokinetics of an approved therapy that does not normally demonstrate appreciable efficacy in CI-AKI, as a preventive intervention. In prior work, we developed a kidney-selective mesoscale nanoparticle (MNP) that targets the renal proximal tubular epithelium. Here, we found that the nanoparticles target the kidneys in a mouse model of CI-AKI with significant damage. We evaluated MNPs loaded with the reactive oxygen species scavenger edaravone, currently used to treat stroke and ALS. We found a marked and significant therapeutic benefit with edaravone-loaded MNPs, including improved renal function, which we demonstrated was likely due to a decrease in tubular epithelial cell damage and death imparted by the specific delivery of edaravone. The results suggest that renal-selective edaravone delivery holds potential for the prevention of acute kidney injury among patients undergoing cisplatin-based chemotherapy.

PMID:35046813 | PMC:PMC8762298 | DOI:10.3389/fphar.2021.790913

Brief Bioinform. 2022 Jan 18:bbab581. doi: 10.1093/bib/bbab581. Online ahead of print.

ABSTRACT

Drug repositioning is an efficient and promising strategy for traditional drug discovery and development. Many research efforts are focused on utilizing deep-learning approaches based on a heterogeneous network for modeling complex drug-disease associations. Similar to traditional latent factor models, which directly factorize drug-disease associations, they assume the neighbors are independent of each other in the network and thus tend to be ineffective to capture localized information. In this study, we propose a novel neighborhood and neighborhood interaction-based neural collaborative filtering approach (called DRWBNCF) to infer novel potential drugs for diseases. Specifically, we first construct three networks, including the known drug-disease association network, the drug-drug similarity and disease-disease similarity networks (using the nearest neighbors). To take the advantage of localized information in the three networks, we then design an integration component by proposing a new weighted bilinear graph convolution operation to integrate the information of the known drug-disease association, the drug's and disease's neighborhood and neighborhood interactions into a unified representation. Lastly, we introduce a prediction component, which utilizes the multi-layer perceptron optimized by the α-balanced focal loss function and graph regularization to model the complex drug-disease associations. Benchmarking comparisons on three datasets verified the effectiveness of DRWBNCF for drug repositioning. Importantly, the unknown drug-disease associations predicted by DRWBNCF were validated against clinical trials and three authoritative databases and we listed several new DRWBNCF-predicted potential drugs for breast cancer (e.g. valrubicin and teniposide) and small cell lung cancer (e.g. valrubicin and cytarabine).

PMID:35039838 | DOI:10.1093/bib/bbab581

Elife. 2022 Jan 17;11:e68832. doi: 10.7554/eLife.68832.

ABSTRACT

Insulin resistance (IR) contributes to the pathophysiology of diabetes, dementia, viral infection, and cardiovascular disease. Drug repurposing (DR) may identify treatments for IR; however, barriers include uncertainty whether in vitro transcriptomic assays yield quantitative pharmacological data, or how to optimise assay design to best reflect in vivo human disease. We developed a clinical-based human tissue IR signature by combining lifestyle-mediated treatment responses (>500 human adipose and muscle biopsies) with biomarkers of disease status (fasting IR from >1200 biopsies). The assay identified a chemically diverse set of >130 positively acting compounds, highly enriched in true positives, that targeted 73 proteins regulating IR pathways. Our multi-gene RNA assay score reflected the quantitative pharmacological properties of a set of epidermal growth factor receptor-related tyrosine kinase inhibitors, providing insight into drug target specificity; an observation supported by deep learning-based genome-wide predicted pharmacology. Several drugs identified are suitable for evaluation in patients, particularly those with either acute or severe chronic IR.

PMID:35037854 | DOI:10.7554/eLife.68832

ACS Pharmacol Transl Sci. 2022 Jan 3;5(1):8-19. doi: 10.1021/acsptsci.1c00182. eCollection 2022 Jan 14.

ABSTRACT

Drug development for specific antiviral agents against coronavirus disease 2019 (COVID-19) is still an unmet medical need as the pandemic continues to spread globally. Although huge efforts for drug repurposing and compound screens have been put forth, only a few compounds are in late-stage clinical trials. New approaches and assays are needed to accelerate COVID-19 drug discovery and development. Here, we report a time-resolved fluorescence resonance energy transfer-based assay that detects the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid protein (NP) produced in infected cells. It uses two specific anti-NP monoclonal antibodies conjugated to donor and acceptor fluorophores that produce a robust ratiometric signal for high throughput screening of large compound collections. Using this assay, we measured a half maximal inhibitory concentration (IC50) for remdesivir of 9.3 μM against infection with SARS-CoV-2 USA/WA1/2020 (WA-1). The assay also detected SARS-CoV-2 South African (Beta, β), Brazilian/Japanese P.1 (Gamma, γ), and Californian (Epsilon, ε) variants of concern (VoC). Therefore, this homogeneous SARS-CoV-2 NP detection assay can be used for accelerating lead compound discovery for drug development and for evaluating drug efficacy against emerging SARS-CoV-2 VoC.

PMID:35036857 | PMC:PMC8751018 | DOI:10.1021/acsptsci.1c00182

Front Pharmacol. 2021 Dec 31;12:828856. doi: 10.3389/fphar.2021.828856. eCollection 2021.

ABSTRACT

Cancer has become a global health problem, accounting for one out of six deaths. Despite the recent advances in cancer therapy, there is still an ever-growing need for readily accessible new therapies. The process of drug discovery and development is arduous and takes many years, and while it is ongoing, the time for the current lead compounds to reach clinical trial phase is very long. Drug repurposing has recently gained significant attention as it expedites the process of discovering new entities for anticancer therapy. One such potential candidate is the antimalarial drug, artemisinin that has shown anticancer activities in vitro and in vivo. In this review, major molecular and cellular mechanisms underlying the anticancer effect of artemisinin and its derivatives are summarised. Furthermore, major mechanisms of action and some key signaling pathways of this group of compounds have been reviewed to explore potential targets that contribute to the proliferation and metastasis of tumor cells. Despite its established profile in malaria treatment, pharmacokinetic properties, anticancer potency, and current formulations that hinder the clinical translation of artemisinin as an anticancer agent, have been discussed. Finally, potential solutions or new strategies are identified to overcome the bottlenecks in repurposing artemisinin-type compounds as anticancer drugs.

PMID:35035355 | PMC:PMC8758560 | DOI:10.3389/fphar.2021.828856

Biochem Biophys Res Commun. 2022 Jan 7;592:87-92. doi: 10.1016/j.bbrc.2022.01.003. Online ahead of print.

ABSTRACT

We screened pre-approved drugs for the survival of the Hu5/KD3 human myogenic progenitors. We found that meclozine, an anti-histamine drug that has long been used for motion sickness, promoted the proliferation and survival of Hu5/KD3 cells. Meclozine increased expression of MyoD, but reduced expression of myosin heavy chain and suppressed myotube formation. Withdrawal of meclozine, however, resumed the ability of Hu5/KD3 cells to differentiate into myotubes. We examined the effects of meclozine on mdx mouse carrying a nonsense mutation in the dystrophin gene and modeling for Duchenne muscular dystrophy. Intragastric administration of meclozine in mdx mouse increased the body weight, the muscle mass in the lower limbs, the cross-sectional area of the paravertebral muscle, and improved exercise performances. Previous reports show that inhibition of phosphorylation of ERK1/2 improves muscle functions in mouse models for Emery-Dreifuss muscular dystrophy and cancer cachexia, as well as in mdx mice. We and others previously showed that meclozine blocks the phosphorylation of ERK1/2 in cultured cells. We currently showed that meclozine decreased phosphorylation of ERK1/2 in muscles in mdx mice but not in wild-type mice. This was likely to be one of the underlying mechanisms of the effects of meclozine on mdx mice.

PMID:35033871 | DOI:10.1016/j.bbrc.2022.01.003

Microb Pathog. 2022 Jan 12:105401. doi: 10.1016/j.micpath.2022.105401. Online ahead of print.

ABSTRACT

The nosocomial pathogen Enterococcus faecalis critically implicated in the hospital environment. Its major virulence attributes biofilm formation and antibiotic resistance. The novel therapeutics are required to inhibit E. faecalis biofilm formation and virulence. Thus combinatorial and drug repurposing has been promising approaches to tackling biofilm-associated infections. Here, we have used a bacterium that produced indole terpenoid Rhodethrin (Rdn) with a combination of known antibiotic chloramphenicol (Chpl) against E. faecalis (ATCC 19433). The fractional inhibitory concentration index (FICI) values showed between 0.25 and 0.33 synergistic activities. The exopolysaccharides (EPSs) production significant decrease with Rdn (34.6 ± 4.6%), Chpl (31.0 ± 5.2%), and combination (Rdn-Chpl) (76.0 ± 4.5%) (p > 0.05). However, the biofilm interruption can attenuate of total biofilm was shown with Rdn (39.7 ± 5.1%), Chpl (32.6 ± 4.7%), and Rdn-Chpl (69.0 ± 5.3%), (p > 0.05). The microscopic observations reveal that the gradually unstructured biofilm architecture in E. faecalis. Furthermore, in silico, studies on biofilm-associated proteins (GelE, LuxS), virulence regulating (SprE), and cell division (FtsZ) have resulted in high and reasonable binding affinity, respectively. Thus, our results suggested that the synergism of Rdn-Chpl has the potential to function as a combinatorial antibiotic accelerates in treating vancomycin-resistant Enterococcus faecalis infections.

PMID:35032606 | DOI:10.1016/j.micpath.2022.105401