Epilepsia. 2022 Jun 29. doi: 10.1111/epi.17352. Online ahead of print.

ABSTRACT

OBJECTIVE: Decades of genetic studies on people with many different epilepsies, and on many non-human species, using many different technologies, have generated a huge body of literature about the genes associated with seizures/epilepsy. Collating this data can help uncover epilepsy genes, pathways and treatments that would otherwise be overlooked. We aimed to collate and structure these data into a database, and use the database to identify novel epilepsy genes and pathways, and to prioritise promising treatments.

METHODS: We collated all the genes associated with all types of seizures/epilepsy in all species, and quantified the supporting evidence for each gene, by manually screening ~10,000 publications, and by extracting data from existing databases.

RESULTS: The largest published dataset of epilepsy genes includes only 977 genes, whereas our database (www.sagas.ac) includes 2876 genes, which demonstrates that the number of genes that can potentially contribute to seizures/epilepsy is much higher than previously envisaged. We use our database to identify 12 hitherto unreported polygenic epilepsy genes, and 479 high-confidence monogenic epilepsy genes, and 394 more biological pathways than identified using the previous largest epilepsy genes dataset. We use a unique feature of SAGAS-the number of citations for each gene-to demonstrate that a drug is more likely to affect seizures if there is more evidence that the genes it affects are associated with seizures, and we use these data to identify promising candidate antiseizure drugs.

SIGNIFICANCE: This database offers insights into the causes of epilepsy and its treatments, and can accelerate future epilepsy research.

PMID:35767389 | DOI:10.1111/epi.17352

Biotechnol Bioeng. 2022 Jun 28. doi: 10.1002/bit.28166. Online ahead of print.

ABSTRACT

In the current pandemic, scenario the world is facing a huge shortage of effective drugs and other prophylactic medicine to treat patients which created havoc in several countries with poor resources. With limited demand and supply of effective drugs, researchers rushed to repurpose the existing approved drugs for the treatment of COVID-19. The process of drug screening and testing is very costly and requires several steps for validation and treatment efficacy evaluation ranging from in-vitro to in-vivo setups. After these steps, a clinical trial is mandatory for the evaluation of treatment efficacy and side effects in humans. These processes enhance the overall cost and sometimes the lead molecule show adverse effects in humans and the trial ends up in the final stages. Recently with the advent of 3D organoid culture which mimics the human tissue exactly the process of drug screening and testing can be done in a faster and cost-effective manner. Further 3D organoids prepared from stems cells taken from individuals can be beneficial for personalized drug therapy which could save millions of lives. This review discussed approaches and techniques for the synthesis of 3D-printed human organoids for drug screening. The key findings of the usage of organoids for personalized medicine for the treatment of COVID-19 have been discussed. In the end, the key challenges for the wide applicability of human organoids for drug screening with prospects of future orientation have been included. This article is protected by copyright. All rights reserved.

PMID:35765706 | DOI:10.1002/bit.28166

Comput Struct Biotechnol J. 2022 Jun 1;20:2839-2847. doi: 10.1016/j.csbj.2022.05.057. eCollection 2022.

ABSTRACT

Repositioning or repurposing drugs account for a substantial part of entering approval pipeline drugs, which indicates that drug repositioning has huge market potential and value. Computational technologies such as machine learning methods have accelerated the process of drug repositioning in the last few decades years. The repositioning potential of type 2 diabetes mellitus (T2DM) drugs for various diseases such as cancer, neurodegenerative diseases, and cardiovascular diseases have been widely studied. Hence, the related summary about repurposing antidiabetic drugs is of great significance. In this review, we focus on the machine learning methods for the development of new T2DM drugs and give an overview of the repurposing potential of the existing antidiabetic agents.

PMID:35765655 | PMC:PMC9189996 | DOI:10.1016/j.csbj.2022.05.057

Sci Rep. 2022 Jun 28;12(1):10896. doi: 10.1038/s41598-022-14558-3.

ABSTRACT

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), a pneumonia-like disease with a pattern of acute respiratory symptoms, currently remains a significant public health concern causing tremendous human suffering. Although several approved vaccines exist, vaccine hesitancy, limited vaccine availability, high rate of viral mutation, and the absence of approved drugs account for the persistence of SARS-CoV-2 infections. The investigation of possibly repurposing of phytochemical compounds as therapeutic alternatives has gained momentum due to their reported affordability and minimal toxicity. This study investigated anti-viral phytochemical compounds from ethanolic leaf extracts of Spondias mombin L as potential inhibitor candidates against SARS-CoV-2. We identified Geraniin and 2-O-Caffeoyl-(+)-allohydroxycitric acid as potential SARS-CoV-2 inhibitor candidates targeting the SARS-CoV-2 RNA-dependent polymerase receptor-binding domain (RBD) of SARS-CoV-2 viral S-protein and the 3C-like main protease (3CLpro). Geraniin exhibited binding free energy (ΔGbind) of - 25.87 kcal/mol and - 21.74 kcal/mol towards SARS-CoV-2 RNA-dependent polymerase and receptor-binding domain (RBD) of SARS-CoV-2 viral S-protein respectively, whereas 2-O-Caffeoyl-(+)-allohydroxycitric acid exhibited a ΔGbind of - 32 kcal/mol towards 3CLpro. Molecular Dynamics simulations indicated a possible interference to the functioning of SARS-CoV-2 targets by the two identified inhibitors. However, further in vitro and in vivo evaluation of these potential SARS-CoV-2 therapeutic inhibitor candidates is needed.

PMID:35764663 | DOI:10.1038/s41598-022-14558-3

Cell Mol Life Sci. 2022 Jun 28;79(7):387. doi: 10.1007/s00018-022-04416-w.

ABSTRACT

Ferroptosis, a type of iron-dependent programmed cell death distinct from apoptosis, necroptosis, and other types of cell death, is characterized by lipid peroxidation, reactive oxygen species production, and mitochondrial dysfunction. Accumulating evidence has highlighted vital roles for ferroptosis in multiple diseases, including acute kidney injury. Therefore, ferroptosis has become a major focus for translational research. However, despite its involvement in pathological conditions, there are no pharmacologic inhibitors of ferroptosis in clinical use. In the context of drug repurposing, a strategy for identifying new uses for approved drugs outside the original medical application, we discovered that vitamin K1 is an efficient inhibitor of ferroptosis. Our findings are strengthened by the fact that the vitamin K antagonist phenprocoumon significantly exacerbated ferroptotic cell death in vitro and also massively worsened the course of acute kidney injury in vivo, which is of utmost clinical importance. We therefore assign vitamin K1 a novel role in preventing ferroptotic cell death in acute tubular necrosis during acute kidney injury. Since the safety, tolerability, pharmacokinetics, and pharmacodynamics of vitamin K1 formulations are well documented, this drug is primed for clinical application, and provides a new strategy for pharmacological control of ferroptosis and diseases associated with this mode of cell death.

PMID:35763128 | DOI:10.1007/s00018-022-04416-w

Curr Med Chem. 2022 Jun 27. doi: 10.2174/0929867329666220627121416. Online ahead of print.

ABSTRACT

The COVID-19 outbreak caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to have high incidence and mortality rate globally. To meet the increasingly growing demand for new therapeutic drugs and vaccines, researchers are developing different diagnostic techniques focused on screening new drugs in clinical use, developing an antibody targeting a SARS-CoV-2 receptor, or interrupting infection/replication mechanisms of SARS-CoV-2. Although many prestigious research publications are addressing this subject, there is no open access platform where all experimental techniques for COVID-19 research can be seen as a whole. Many researchers have accelerated the development of in silico methods, high-throughput screening techniques, and in vitro assays. This development has played an important role in the emergence of improved innovative strategies including different antiviral drug development, new drug discovery protocols, combinations of approved drugs, and setting up new drug classes during the COVID 19 outbreak. Hence, the present review discusses the current literature on these modalities, including virtual in silico methods for instant ligand- and target-driven based techniques, nucleic acid amplification tests, and in vitro models based on sensitive cell cultures, tissue equivalents, organoids, and SARS-CoV-2 neutralization systems (lentiviral pseudotype, viral isolates, etc.). This pack of complementary tests inform researchers about the accurate, and most relevant emerging techniques available, and in vitro assays allowing them to understand their strengths and limitations. This review could be a pioneer reference guide for the development of logical algorithmic approaches for new drugs and vaccine strategies against COVID-19.

PMID:35761502 | DOI:10.2174/0929867329666220627121416

OMICS. 2022 Jun 28. doi: 10.1089/omi.2022.0068. Online ahead of print.

ABSTRACT

Drug repurposing is of interest for therapeutics innovation in many human diseases including coronavirus disease 2019 (COVID-19). Methodological innovations in drug repurposing are currently being empowered by convergence of omics systems science and digital transformation of life sciences. This expert review article offers a systematic summary of the application of artificial intelligence (AI), particularly machine learning (ML), to drug repurposing and classifies and introduces the common clustering, dimensionality reduction, and other methods. We highlight, as a present-day high-profile example, the involvement of AI/ML-based drug discovery in the COVID-19 pandemic and discuss the collection and sharing of diverse data types, and the possible futures awaiting drug repurposing in an era of AI/ML and digital technologies. The article provides new insights on convergence of multi-omics and AI-based drug repurposing. We conclude with reflections on the various pathways to expedite innovation in drug development through drug repurposing for prompt responses to the current COVID-19 pandemic and future ecological crises in the 21st century.

PMID:35759424 | DOI:10.1089/omi.2022.0068

Bioinformatics. 2022 Jun 24;38(Supplement_1):i68-i76. doi: 10.1093/bioinformatics/btac240.

ABSTRACT

MOTIVATION: A critical element of drug development is the identification of therapeutic targets for diseases. However, the depletion of therapeutic targets is a serious problem.

RESULTS: In this study, we propose the novel concept of target repositioning, an extension of the concept of drug repositioning, to predict new therapeutic targets for various diseases. Predictions were performed by a trans-disease analysis which integrated genetically perturbed transcriptomic signatures (knockdown of 4345 genes and overexpression of 3114 genes) and disease-specific gene transcriptomic signatures of 79 diseases. The trans-disease method, which takes into account similarities among diseases, enabled us to distinguish the inhibitory from activatory targets and to predict the therapeutic targetability of not only proteins with known target-disease associations but also orphan proteins without known associations. Our proposed method is expected to be useful for understanding the commonality of mechanisms among diseases and for therapeutic target identification in drug discovery.

AVAILABILITY AND IMPLEMENTATION: Supplemental information and software are available at the following website [http://labo.bio.kyutech.ac.jp/~yamani/target_repositioning/].

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:35758779 | DOI:10.1093/bioinformatics/btac240

J Enzyme Inhib Med Chem. 2022 Dec;37(1):1838-1844. doi: 10.1080/14756366.2022.2092729.

ABSTRACT

Vancomycin-resistant enterococci (VRE), consisting of pathogenic Enterococcus faecalis and E. faecium, is a leading cause of hospital-acquired infections (HAIs). We recently repurposed the FDA-approved human carbonic anhydrase (CA) inhibitor acetazolamide (AZM) against VRE agent with the likely mechanism of action for the molecules being inhibition of one, or both, of the bacterial CA isoforms expressed in VRE. To elucidate how inhibitor binding to the enzymes relates to MIC, we further characterised the inhibition constants (Ki) against the E. faecium α-CA (Efα-CA) and γ-CA (Efγ-CA), as well as against human CA I (hCAI) and human CA II (hCAII) to assess selectivity. We have also utilised homology modelling and molecular dynamics (MD) simulations to gain a better understanding of the potential interactions the molecules are making with the targets. In this paper, we elaborate on the SAR for the AZM analogs as it pertains to MIC and Ki for each CA.

PMID:35758212 | DOI:10.1080/14756366.2022.2092729

Patterns (N Y). 2022 Jun 10;3(6):100496. doi: 10.1016/j.patter.2022.100496. eCollection 2022 Jun 10.

ABSTRACT

Indication extension or repositioning of drugs can, if done well, provide a faster, cheaper, and derisked route to the approval of new therapies, creating new options to address pockets of unmet medical need for patients and offering the potential for significant commercial and clinical benefits. We look at the promises and challenges of different repositioning strategies and the disease insights and scalability that new high-resolution patient stratification methodologies can bring. This is exemplified by a systematic analysis of all development candidates and on-market drugs, which identified 477 indication extension opportunities across 30 chronic disease areas, each supported by patient stratification biomarkers. This illustrates the potential that new artificial intelligence (AI) and combinatorial analytics methods have to enhance the rate and cost of innovation across the drug discovery industry.

PMID:35755863 | PMC:PMC9214305 | DOI:10.1016/j.patter.2022.100496

Brief Bioinform. 2022 Jun 27:bbac247. doi: 10.1093/bib/bbac247. Online ahead of print.

ABSTRACT

As the development of new drugs reaches its physical and financial limits, drug repurposing has become more important than ever. For mechanistically grounded drug repurposing, it is crucial to uncover the disease mechanisms and to detect clusters of mechanistically related diseases. Various methods for computing candidate disease mechanisms and disease clusters exist. However, in the absence of ground truth, in silico validation is challenging. This constitutes a major hurdle toward the adoption of in silico prediction tools by experimentalists who are often hesitant to carry out wet-lab validations for predicted candidate mechanisms without clearly quantified initial plausibility. To address this problem, we present DIGEST (in silico validation of disease and gene sets, clusterings or subnetworks), a Python-based validation tool available as a web interface (https://digest-validation.net), as a stand-alone package or over a REST API. DIGEST greatly facilitates in silico validation of gene and disease sets, clusterings or subnetworks via fully automated pipelines comprising disease and gene ID mapping, enrichment analysis, comparisons of shared genes and variants and background distribution estimation. Moreover, functionality is provided to automatically update the external databases used by the pipelines. DIGEST hence allows the user to assess the statistical significance of candidate mechanisms with regard to functional and genetic coherence and enables the computation of empirical $P$-values with just a few mouse clicks.

PMID:35753693 | DOI:10.1093/bib/bbac247

J Affect Disord. 2022 Jun 23:S0165-0327(22)00700-5. doi: 10.1016/j.jad.2022.06.040. Online ahead of print.

ABSTRACT

BACKGROUND: Improved treatments for bipolar disorder (BD) are needed. Drug repurposing aims to find novel targets for drugs that have been used for other indications. This study investigated the risk of psychiatric hospitalization associated with use of calcium-channel blockers (CCBs; dihydropyridines, diltiazem, verapamil) and adenosine modulators (allopurinol, dipyridamole) in BD in within-individual design.

METHODS: Individuals diagnosed with BD (ICD-10: F30-F31) were identified from the inpatient, specialized outpatient, sickness absence, and disability pension registers during 1996-2018 in Finland (N = 60,045). The main outcome was hospitalization due to affective symptoms (ICD-10: F30-F39). Within-individual models in stratified Cox regression were used and adjusted hazard ratios (aHR) with 95 % confidence intervals (CIs) reported.

RESULTS: Use of CCBs was associated with a decreased risk of hospitalization due to affective symptoms (aHR 0.83, 95 % CI 0.78-0.88) when all CCBs were analyzed together. Of specific CCBs, use of diltiazem (0.71, 0.55-0.91) and dihydropyridines (0.83, 0.78-0.89) were associated with a decreased risk but verapamil was not (0.93, 0.73-1.19). Use of adenosine modulators in general was associated with a decreased risk of hospitalizations due to affective symptoms (0.87, 0.79-0.96). Both allopurinol (0.85, 0.74-0.97) and dipyridamole (0.89, 0.78-1.00) were associated with a marginally decreased risk. Thiazide diuretic use as a negative control was not associated with the risk of hospitalization due to affective symptoms (0.97, 0.83-1.13).

LIMITATIONS: Due to the observational nature of this study, causation cannot be confirmed.

CONCLUSIONS: Dihydropyridines and diltiazem were associated with a decreased risk of psychiatric hospitalization in bipolar disorder. Results for allopurinol and dipyridamole were inconclusive.

PMID:35753501 | DOI:10.1016/j.jad.2022.06.040

Eur J Med Chem. 2022 Jun 17;239:114542. doi: 10.1016/j.ejmech.2022.114542. Online ahead of print.

ABSTRACT

Chemotherapy is one of the most common treatments for cancer that uses one or more anti-cancer drugs as a part of the standardized chemotherapy regimen. Cytotoxic chemicals delay and prevent cancer cells from multiplying, invading, and metastasizing. However, the significant drawbacks of cancer chemotherapy are the lack of selectivity of the cytotoxic drugs to tumour cells and normal cells and the development of resistance by cells for the particular drug or the combination of drugs. Multidrug resistance (MDR) is the low sensitivity of specific cells against drugs associated with cancer chemotherapy. The most common mechanisms of anticancer drug resistance are: (a) drug-dependent MDR (b) target-dependent MDR, and (c) drug target-independent MDR. In all the factors, the overexpression of multidrug efflux systems contributes significantly to the increased resistance in the cancer cells. Multidrug resistance due to efflux of anticancer drugs by membrane ABC transporters includes ABCB1, ABCC1, and ABCG2. ABCB1 inhibition can restore the sensitivity of the cancerous cells toward chemotherapeutic drugs. In this review, we discussed ABCB1 inhibitors under clinical studies with their mode of action, potency and selectivity. Also, we have highlighted the contribution of repurposing drugs, biologics and nano formulation strategies to combat multidrug resistance by modulating the ABCB1 activity.

PMID:35751979 | DOI:10.1016/j.ejmech.2022.114542

J Biomol Struct Dyn. 2022 Jun 24:1-14. doi: 10.1080/07391102.2022.2091659. Online ahead of print.

ABSTRACT

High-risk (HR) Human papillomavirus (e.g. HPV16 and HPV18) causes approximately two-thirds of all cervical cancers in women. Although the first and second-generation vaccines confer some protection against individuals, there are no approved drugs to treat HR-HPV infections to-date. The HPV E1 protein is an attractive drug target because the protein is highly conserved across all HPV types and is crucial for the regulation of viral DNA replication. Hence, we used the Random Forest algorithm to construct a Quantitative-Structure Activity Relationship (QSAR) model to predict the potential inhibitors against the HPV E1 protein. Our QSAR classification model achieved an accuracy of 87.5%, area under the receiver operating characteristic curve of 1.00, and F-measure of 0.87 when evaluated using an external test set. We conducted a drug repurposing campaign by deploying the model to screen the Drugbank database. The top three compounds, namely Cinalukast, Lobeglitazone, and Efatutazone were analyzed for their cell membrane permeability, toxicity, and carcinogenicity. Finally, these three compounds were subjected to molecular docking and 200 ns-long Molecular Dynamics (MD) simulations. The predicted binding free energies for the candidates were calculated using the MM-GBSA method. The binding free energies for Cinalukast, Lobeglitazone, and Efatutazone were -37.84 kcal/mol, -25.30 kcal/mol, and -29.89 kcal/mol respectively. Therefore, we propose their chemical scaffolds for future rational design of E1 inhibitors.Communicated by Ramaswamy H. Sarma.

PMID:35751129 | DOI:10.1080/07391102.2022.2091659

J Antimicrob Chemother. 2022 Jun 24:dkac201. doi: 10.1093/jac/dkac201. Online ahead of print.

ABSTRACT

BACKGROUND: Antimicrobial resistance is a growing menace, claiming millions of lives all over the world. In this context, drug repurposing is one approach gaining interest as a suitable alternative to conventional drug discovery and development.

METHODS: Whole-cell assays were used to screen FDA-approved drugs to identify novel antimicrobial agents active against bacterial pathogens. Following identification of nitazoxanide, its various characteristics, such as antimicrobial activity against MDR isolates, time-kill kinetics, ability to synergize with approved drugs, antibiofilm activity and ability to generate resistance in Staphylococcus aureus, were determined, followed by determination of its in vivo potential against MDR S. aureus.

RESULTS: Nitazoxanide demonstrated a potent in vitro antistaphylococcal profile, including equipotent activity against clinical drug-resistant S. aureus and Enterococcus spp. Nitazoxanide exhibited concentration-dependent killing, significantly eradicated preformed S. aureus biofilm and S. aureus did not generate resistance to it. Nitazoxanide strongly synergized with linezolid both in vitro and in vivo against linezolid-susceptible and -resistant S. aureus, displaying superior activity to untreated control and drug-alone treatment groups.

CONCLUSIONS: Nitazoxanide can be utilized in combination with linezolid against infections caused by linezolid-resistant S. aureus as it exhibits strong synergism in vitro and in vivo.

PMID:35748613 | DOI:10.1093/jac/dkac201

FEBS Open Bio. 2022 Jun 24. doi: 10.1002/2211-5463.13459. Online ahead of print.

ABSTRACT

Renal cyst development and expansion in autosomal dominant polycystic kidney disease (ADPKD) involves over-proliferation of cyst-lining epithelial cells and excessive cystic fluid secretion. While metformin effectively inhibits renal cyst growth in mouse models of ADPKD it exhibits low potency, and thus an AMPK activator with higher potency is required. Herein, we adopted a drug repurposing strategy to explore the potential of PF-06409577, an adenosine monophosphate-activated protein kinase (AMPK) activator for diabetic nephropathy, in cellular, ex vivo and in vivo models of ADPKD. Our results demonstrated that PF-06409577 effectively down-regulated mammalian target of rapamycin (mTOR) pathway-mediated proliferation of cyst-lining epithelial cells and reduced cystic fibrosis transmembrane conductance regulator (CFTR)-regulated cystic fluid secretion. Overall, our data suggest that PF-06409577 holds therapeutic potential for ADPKD treatment.

PMID:35748097 | DOI:10.1002/2211-5463.13459

Front Oncol. 2022 Jun 7;12:922418. doi: 10.3389/fonc.2022.922418. eCollection 2022.

ABSTRACT

BACKGROUND: Cachexia is an inflammatory and metabolic syndrome of unintentional weight loss through depletion of muscle and adipose tissue. There is limited knowledge of how chronic use of non-steroidal anti-inflammatory drugs (NSAIDs) and glucocorticoids affect cachexia development. The purpose of this study was to investigate associations between prior long-term use of NSAIDs or glucocorticoids with cachexia incidence and post-diagnosis weight loss progression in a retrospective cancer patient cohort.

METHODS: Of 3,802 lung or gastrointestinal cancer patient records, 3,180 comprised our final cohort. Patient demographic information, tumor qualities, medication histories, and comorbidities were assessed. Cachexia was defined as having developed prior to oncologic treatment. Statistical evaluations included categorical, multivariate logistic regression, and log-rank survival analyses. Development of substantial post-diagnosis weight loss was calculated and interpreted for patients without cachexia at diagnosis.

RESULTS: Chronic prior use of any NSAID or glucocorticoid medication was associated with approximate absolute and relative reductions in cachexia incidence at diagnosis of 10 and 25 percent (P<0.0001). In multivariate analyses, NSAID medications demonstrated a 23 percent reduction in cachexia incidence likelihood (OR=0.770; 95% CI=0.594, 0.998; P=0.0481). Patients without cachexia at diagnosis were significantly more likely to develop substantial post-diagnosis weight loss from pre-diagnosis use groups of glucocorticoids (OR= 1.452; 95% CI=1.065, 1.979; P=0.0183) or NSAIDs (OR=1.411; 95% CI=1.082, 1.840; P=0.011).

CONCLUSIONS: Our findings suggest a protective effect of prior anti-inflammatory medications, primarily NSAIDs, against manifestations of the cachexia phenotype at cancer diagnosis. These observations support further exploration of potential therapeutic benefits from anti-inflammatory medications early in cancer management.

PMID:35747801 | PMC:PMC9210667 | DOI:10.3389/fonc.2022.922418

Viruses. 2022 May 24;14(6):1129. doi: 10.3390/v14061129.

ABSTRACT

The COVID-19 pandemic began in 2019, but it is still active. The development of an effective vaccine reduced the number of deaths; however, a treatment is still needed. Here, we aimed to inhibit viral entry to the host cell by inhibiting spike (S) protein cleavage by several proteases. We developed a computational pipeline to repurpose FDA-approved drugs to inhibit protease activity and thus prevent S protein cleavage. We tested some of our drug candidates and demonstrated a decrease in protease activity. We believe our pipeline will be beneficial in identifying a drug regimen for COVID-19 patients.

PMID:35746605 | DOI:10.3390/v14061129

Pharmaceutics. 2022 Jun 8;14(6):1219. doi: 10.3390/pharmaceutics14061219.

ABSTRACT

We aimed to develop nafamostat mesylate immediate-release tablets for the treatment of COVID-19 through drug repositioning studies of nafamostat mesylate injection. Nafamostat mesylate is a serine protease inhibitor known to inhibit the activity of the transmembrane protease, serine 2 enzyme that affects the penetration of the COVID-19 virus, thereby preventing the binding of the angiotensin-converting enzyme 2 receptor in vivo and the spike protein of the COVID-19 virus. The formulation was selected through a stability study after manufacturing by a wet granulation process and a direct tableting process to develop a stable nafamostat mesylate immediate-release tablet. Formulation issues for the selected processes were addressed using the design of experiments and quality-by-design approaches. The dissolution rate of the developed tablet was confirmed to be &gt;90% within 30 min in the four major dissolutions, except in the pH 6.8 dissolution medium. Additionally, an in vivo pharmacokinetic study was performed in monkeys, and the pharmacokinetic profiles of nafamostat injections, oral solutions, and tablets were compared. The half-life during oral administration was confirmed to be significantly longer than the reported literature value of 8 min, and the bioavailability of the tablet was approximately 25% higher than that of the oral solution.

PMID:35745792 | DOI:10.3390/pharmaceutics14061219

Pharmaceuticals (Basel). 2022 Jun 8;15(6):726. doi: 10.3390/ph15060726.

ABSTRACT

Although oxaliplatin is a well-known anti-cancer agent used for the treatment of colorectal cancer, treated patients often experience acute cold and mechanical allodynia as side effects. Unfortunately, no optimal treatment has been developed yet. In this study, [6]-shogaol (10 mg/kg, i.p.), which is one of the major bioactive components of Zingiber officinale roscoe (Z. officinale), significantly alleviated allodynia induced by oxaliplatin (6 mg/kg, i.p.) injection. Cold and mechanical allodynia were assessed by acetone drop and von Frey filament tests, respectively. The analgesic effect of [6]-shogaol was blocked by the intrathecal injection of 5-HT1A, 5-HT3, and GABAB receptor antagonists, NAN-190 (1 μg), MDL-72222 (15 μg), and CGP 55845 (10 μg), respectively. Furthermore, oxaliplatin injection lowered the GABA concentration in the superficial laminae of the spinal dorsal horn, whereas [6]-shogaol injection significantly elevated it. The GAD (glutamic acid decarboxylase) 65 concentration also increased after [6]-shogaol administration. However, pre-treatment of NAN-190 completely inhibited the increased GABA induced by [6]-shogaol in the spinal dorsal horn, whereas MDL-72222 partially blocked the effect. Altogether, these results suggest that [6]-shogaol could attenuate oxaliplatin-induced cold and mechanical allodynia through 5-HT1A and 5-HT3 receptor antagonists located in the GABAergic neurons in the spinal dorsal horn in mice.

PMID:35745645 | DOI:10.3390/ph15060726