Curr Med Chem. 2021 Dec 21. doi: 10.2174/0929867329666211221153719. Online ahead of print.

ABSTRACT

Fyn kinase is a member of the Src non-receptor tyrosine kinase family. Fyn is involved in multiple signaling pathways extending from cell proliferation and differentiation to cell adhesion and cell motility, and it has been found to be overexpressed in various types of cancers. In the central nervous system, Fyn exerts several different functions such as axon-glial signal transduction, oligodendrocyte maturation and myelination, and it is implicated in neuroinflammatory processes. Based on these premises, Fyn emerges as an attractive target in cancer and neurodegenerative disease therapy, particularly Alzheimer disease (AD), based on its activation by Aβ via cellular prion protein and its interaction with tau protein. However, Fyn is also a challenging target since the Fyn inhibitors discovered so far, due to the relevant homology of Fyn with other kinases, suffer from off-target effects. This review covers the efforts performed in the last decade to identify and optimize small molecules that effectively inhibit Fyn, both in enzymatic and in cell assays, including drug repositioning practices, as an opportunity of therapeutic intervention in neurodegeneration.

PMID:34939537 | DOI:10.2174/0929867329666211221153719

Assay Drug Dev Technol. 2021 Dec 21. doi: 10.1089/adt.2021.126. Online ahead of print.

NO ABSTRACT

PMID:34936476 | DOI:10.1089/adt.2021.126

Sci Rep. 2021 Dec 21;11(1):24367. doi: 10.1038/s41598-021-03000-9.

ABSTRACT

Persistent infection with high-risk types Human Papillomavirus could cause diseases including cervical cancers and oropharyngeal cancers. Nonetheless, so far there is no effective pharmacotherapy for treating the infection from high-risk HPV types, and hence it remains to be a severe threat to the health of female. Based on drug repositioning strategy, we trained and benchmarked multiple machine learning models so as to predict potential effective antiviral drugs for HPV infection in this work. Through optimizing models, measuring models' predictive performance using 182 pairs of antiviral-target interaction dataset which were all approved by the United States Food and Drug Administration, and benchmarking different models' predictive performance, we identified the optimized Support Vector Machine and K-Nearest Neighbor classifier with high precision score were the best two predictors (0.80 and 0.85 respectively) amongst classifiers of Support Vector Machine, Random forest, Adaboost, Naïve Bayes, K-Nearest Neighbors, and Logistic regression classifier. We applied these two predictors together and successfully predicted 57 pairs of antiviral-HPV protein interactions from 864 pairs of antiviral-HPV protein associations. Our work provided good drug candidates for anti-HPV drug discovery. So far as we know, we are the first one to conduct such HPV-oriented computational drug repositioning study.

PMID:34934067 | DOI:10.1038/s41598-021-03000-9

Nat Commun. 2021 Dec 20;12(1):7342. doi: 10.1038/s41467-021-26280-1.

ABSTRACT

Parkinson's disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson's disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson's disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson's disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson's disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson's disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson's disease drug development.

PMID:34930919 | DOI:10.1038/s41467-021-26280-1

Mol Med. 2021 Dec 20;27(1):161. doi: 10.1186/s10020-021-00424-x.

ABSTRACT

BACKGROUND: Similarities in the hijacking mechanisms used by SARS-CoV-2 and several types of cancer, suggest the repurposing of cancer drugs to treat Covid-19. CK2 kinase antagonists have been proposed for cancer treatment. A recent study in cells infected with SARS-CoV-2 found a significant CK2 kinase activity, and the use of a CK2 inhibitor showed antiviral responses. CIGB-300, originally designed as an anticancer peptide, is an antagonist of CK2 kinase activity that binds to the CK2 phospho-acceptor sites. Recent preliminary results show the antiviral activity of CIGB-300 using a surrogate model of coronavirus. Here we present a computational biology study that provides evidence, at the molecular level, of how CIGB-300 may interfere with the SARS-CoV-2 life cycle within infected human cells.

METHODS: Sequence analyses and data from phosphorylation studies were combined to predict infection-induced molecular mechanisms that can be interfered by CIGB-300. Next, we integrated data from multi-omics studies and data focusing on the antagonistic effect on the CK2 kinase activity of CIGB-300. A combination of network and functional enrichment analyses was used.

RESULTS: Firstly, from the SARS-CoV studies, we inferred the potential incidence of CIGB-300 in SARS-CoV-2 interference on the immune response. Afterwards, from the analysis of multiple omics data, we proposed the action of CIGB-300 from the early stages of viral infections perturbing the virus hijacking of RNA splicing machinery. We also predicted the interference of CIGB-300 in virus-host interactions that are responsible for the high infectivity and the particular immune response to SARS-CoV-2 infection. Furthermore, we provided evidence of how CIGB-300 may participate in the attenuation of phenotypes related to muscle, bleeding, coagulation and respiratory disorders.

CONCLUSIONS: Our computational analysis proposes putative molecular mechanisms that support the antiviral activity of CIGB-300.

PMID:34930105 | DOI:10.1186/s10020-021-00424-x

Saudi J Biol Sci. 2021 Dec 13. doi: 10.1016/j.sjbs.2021.12.018. Online ahead of print.

ABSTRACT

In view of the potential of traditional plant-based remedies (or phytomedicines) in the management of COVID-19, the present investigation was aimed at finding novel anti-SARS-CoV-2 molecules by in silico screening of bioactive phytochemicals (database) using computational methods and drug repurposing approach. A total of 160 compounds belonging to various phytochemical classes (flavonoids, limonoids, saponins, triterpenoids, steroids etc.) were selected (as initial hits) and screened against three specific therapeutic targets (Mpro/ 3CLpro, PLpro and RdRp) of SARS-CoV-2 by docking, molecular dynamics simulation and drug-likeness/ADMET studies. From our studies, six phytochemicals were identified as notable ant-SARS-CoV-2 agents (best hit molecules) with promising inhibitory effects effective against protease (Mpro and PLpro) and polymerase (RdRp) enzymes. These compounds are namely, ginsenoside Rg2, saikosaponin A, somniferine, betulinic acid, soyasapogenol C and azadirachtin A. On the basis of binding modes and dynamics studies of protein-ligand intercations, ginsenoside Rg2, saikosaponin A, somniferine were found to be the most potent (in silico) inhibitors potentially active against Mpro, PLpro and RdRp, respectively. The present investigation can be directed towards further experimental studies in order to confirm the anti-SARS-CoV-2 efficacy along with toxicities of identified phytomolecules.

PMID:34924801 | PMC:PMC8667520 | DOI:10.1016/j.sjbs.2021.12.018

J Invest Dermatol. 2021 Dec 16:S0022-202X(21)02521-5. doi: 10.1016/j.jid.2021.11.012. Online ahead of print.

ABSTRACT

Drug repurposing has the potential to discover new treatments for diseases with high unmet medical needs. Lee et al. (2021) combined transcriptomics and computational analysis of drug-target databases to identify novel therapies for epidermolysis bullosa simplex. Differential gene expression analysis of blister epidermis identified the phosphoinositide 3-kinase/protein kinase B/mTOR signaling pathway as central. A pilot study using a topical mTOR inhibitor showed marked improvement.

PMID:34924185 | DOI:10.1016/j.jid.2021.11.012

Biomed Pharmacother. 2021 Dec 16;146:112549. doi: 10.1016/j.biopha.2021.112549. Online ahead of print.

ABSTRACT

MAP/microtubule affinity-regulating kinases (MARKs) were recently identified as potential drug targets for Alzheimer's disease (AD) due to their role in pathological hyperphosphorylation of tau protein. Hyperphosphorylated tau has decreased affinity for microtubule binding, impairing their stability and associated functions. Destabilization of microtubules in neuronal cells leads to neurodegeneration, and microtubule-unbound tau forms neurofibrillary tangles, one of the primary hallmarks of AD. Many phosphorylation sites of tau protein have been identified, but phosphorylation at Ser262, which occurs in early stages of AD, plays a vital role in the pathological hyperphosphorylation of tau. It has been found that Ser262 is phosphorylated by MARK4, which is currently an intensively studied target for treating Alzheimer's disease and other neurodegenerative diseases. Our present study aimed to develop a high throughput compatible assay to directly detect MARK enzymatic activity using echoacoustic transfer and MALDI-TOF mass spectrometer. We optimized the assay for all four isoforms of MARK and validated its use for identifying potential inhibitors by the screening of 1280 compounds from the LOPAC®1280 International (Library Of Pharmacologically Active Compounds). Six MARK4 inhibitors with IC50 < 1 µM were identified. To demonstrate their therapeutic potential, active compounds were further tested for MARK4 selectivity and ability to cross the blood-brain barrier. Lastly, the molecular docking with the most active inhibitors to predict their interaction with MARK4 was performed.

PMID:34923338 | DOI:10.1016/j.biopha.2021.112549

Cancer Lett. 2021 Dec 16:S0304-3835(21)00627-3. doi: 10.1016/j.canlet.2021.12.014. Online ahead of print.

ABSTRACT

Psychotropic drugs can penetrate the blood-brain barrier and regulate the levels of neurotransmitters and neuromodulators such as γ-aminobutyric acid, glutamate, serotonin, dopamine, and norepinephrine in the brain, and thus influence neuronal activity. Neuronal activity in the tumor microenvironment can promote the growth and expansion of glioma. There is increasing evidence that in addition to their use in the treatment of mental disorders, antipsychotic, antidepressant, and mood-stabilizing drugs have clinical potential for cancer therapy. These drugs have been shown to inhibit the malignant progression of glioma by targeting signaling pathways related to cell proliferation, apoptosis, or invasion/migration or by increasing the sensitivity of glioma cells to conventional chemotherapy or radiotherapy. In this review, we summarize findings from preclinical and clinical studies investigating the use of antipsychotics, antidepressants, and mood stabilizers in the treatment of various types of cancer, with a focus on glioma; and discuss their presumed antitumor mechanisms. The existing evidence indicates that psychotropic drugs with established pharmacologic and safety profiles can be repurposed as anticancer agents, thus providing new options for the treatment of glioma.

PMID:34923043 | DOI:10.1016/j.canlet.2021.12.014

IUBMB Life. 2021 Dec 18. doi: 10.1002/iub.2590. Online ahead of print.

ABSTRACT

Cancer accounted for nearly 10 million deaths in 2020 and is the second leading cause of death worldwide. The chemotherapeutic agents that are in clinical practice possess a broad range of severe adverse effects towards vital organs which emphasizes the importance of the discovery of new therapeutic agents or repurposing of existing drugs for the treatment of human cancers. Pyrimethamine is an antiparasitic drug used for the treatment of malaria and toxoplasmosis with a well-documented excellent safety profile. In the last five years, numerous efforts have been made to explore the anticancer potential of pyrimethamine in in vitro and in vivo preclinical models and to repurpose it as an anticancer agent. The studies have demonstrated that pyrimethamine inhibits oncogenic proteins such as STAT3, NF-κB, DX2, MAPK, DHFR, thymidine phosphorylase, telomerase, and many more in a different types of cancer models. Moreover, pyrimethamine has been reported to work in synergy with other anticancer agents, such as temozolomide, to induce apoptosis of tumor cells. Recently, the results of phase-1/2 clinical trials demonstrated that pyrimethamine administration reduces the expression of STAT3 signature genes in tumor tissues of chronic lymphocytic leukemia patients with a good therapeutic response. In the present article, we have reviewed most of the published papers related to the antitumor effects of pyrimethamine in malignancies of breast, liver, lung, skin, ovary, prostate, pituitary, and leukemia in in vitro and in vivo settings. We have also discussed the pharmacokinetic profile and results of clinical trials obtained after pyrimethamine treatment. From these studies, we believe that pyrimethamine has the potential to be repurposed as an anticancer drug. This article is protected by copyright. All rights reserved.

PMID:34921584 | DOI:10.1002/iub.2590

Eur Rev Med Pharmacol Sci. 2021 Dec;25(23):7565-7584. doi: 10.26355/eurrev_202112_27456.

ABSTRACT

OBJECTIVE: With the recent direction in drug repurposing, many approved drugs have been evaluated to assess their effect on the coronavirus or SARS-CoV-2 infection (COVID-19). Driving this path, chloroquine (CQ) has been used in the treatment of malaria and hydroxychloroquine (HCQ) in immunomodulatory and anti-thrombotic action, playing a leading role in initial management of the viral infection.

MATERIALS AND METHODS: Literature search was done using Google Scholar, PubMed and Scopus database using keywords "chloroquine" "SARS-CoV-2" "COVID-19" "mechanism of action" and articles of interest were selected providing evidence of the possible role of CQ in viral infection.

RESULTS: In a bid to understand how and if CQ and HCQ would exert their anti-viral property, mechanistic exegesis was done to review various proposed mechanisms of action. This revealed the inhibition of viral attachment and entry, inhibition of enveloped glycoprotein, inhibition of the development and proliferation of new viral particles as the way they perform their action. There is an interplay between iron metabolism and homeostasis with COVID-19 infection and viral reproduction.

CONCLUSIONS: This study aims to show the functional role of CQ and HCQ, as well as to provide possible mechanistic insight on the role of iron on viral infection, iron starvation and its downstream cellular pathways involving hepcidin and proinflammatory cytokines. The overall aim of providing possible mode of action of CQ and HCQ in the management of COVID-19 infection is exhibited via its anti-viral, anti-inflammatory and anti-thrombotic activities.

PMID:34919258 | DOI:10.26355/eurrev_202112_27456

Front Pharmacol. 2021 Nov 30;12:763649. doi: 10.3389/fphar.2021.763649. eCollection 2021.

ABSTRACT

Background: Previous studies suggested an association of sleep disorders with inflammatory bowel disease (IBD) and indicated that using pharmacological treatments for the modulation of circadian rhythms might prevent IBD pathogenesis or aggravation, but whether the effect of sleep traits on IBD was causal is inconclusive and, therefore, prevents drug repurposing based on the previous studies. We aimed to examine the causal effect of different sleep traits on the pathogenesis of IBD. Methods: Genetic instruments for sleep traits were selected from the largest GWAS studies available in the UK Biobank (n = 449,734) and the 23andMe Research (n = 541,333). A two-sample Mendelian randomization (MR) study was conducted to examine the association of the genetic instruments with IBD (12,882 cases and 21,770 controls), ulcerative colitis (6,968 cases, 20,464 controls), and Crohn's disease (5,956 cases and 14,927 controls). We applied the inverse-variance weighted (IVW) method to estimate causal effects, and we used the weighted median and MR-Egger method for sensitivity analyses. Results: We found that sleep duration (OR, 1.00, 95% CI 1.00-1.01), short sleep duration (OR, 1.07, 95% CI 0.41-2.83), morningness (OR, 1.05, 95% CI 0.87-1.27), daytime napping (OR, 1.64, 95% CI 0.62-4.4), frequent insomnia (OR, 1.17, 95% CI 0.8-1.72), any insomnia (OR, 1.17, 95% CI 0.69-1.97), and snoring (OR, 0.31, 95% CI 0.06-1.54) had no causal effect on IBD, and these sleep traits had no causal effect on ulcerative colitis and Crohn's disease either. Most of the sensitivity analyses showed consistent results with those of the IVW method. Conclusion: Our MR study did not support the causal effect of sleep traits on IBD. Pharmacological modulation of circadian rhythms for the prevention of IBD pathogenesis was unwarranted.

PMID:34916940 | PMC:PMC8669049 | DOI:10.3389/fphar.2021.763649

Nat Commun. 2021 Dec 16;12(1):7327. doi: 10.1038/s41467-021-27547-3.

ABSTRACT

The global disruption caused by the 2020 coronavirus pandemic stressed the supply chain of many products, including pharmaceuticals. Multiple drug repurposing studies for COVID-19 are now underway. If a winning therapeutic emerges, it is unlikely that the existing inventory of the medicine, or even the chemical raw materials needed to synthesize it, will be available in the quantities required. Here, we utilize retrosynthetic software to arrive at alternate chemical supply chains for the antiviral drug umifenovir, as well as eleven other antiviral and anti-inflammatory drugs. We have experimentally validated four routes to umifenovir and one route to bromhexine. In one route to umifenovir the software invokes conversion of six C-H bonds into C-C bonds or functional groups. The strategy we apply of excluding known starting materials from search results can be used to identify distinct starting materials, for instance to relieve stress on existing supply chains.

PMID:34916512 | DOI:10.1038/s41467-021-27547-3

Genome Med. 2021 Dec 16;13(1):189. doi: 10.1186/s13073-021-01000-y.

ABSTRACT

While understanding molecular heterogeneity across patients underpins precision oncology, there is increasing appreciation for taking intra-tumor heterogeneity into account. Based on large-scale analysis of cancer omics datasets, we highlight the importance of intra-tumor transcriptomic heterogeneity (ITTH) for predicting clinical outcomes. Leveraging single-cell RNA-seq (scRNA-seq) with a recommender system (CaDRReS-Sc), we show that heterogeneous gene-expression signatures can predict drug response with high accuracy (80%). Using patient-proximal cell lines, we established the validity of CaDRReS-Sc's monotherapy (Pearson r>0.6) and combinatorial predictions targeting clone-specific vulnerabilities (>10% improvement). Applying CaDRReS-Sc to rapidly expanding scRNA-seq compendiums can serve as in silico screen to accelerate drug-repurposing studies. Availability: https://github.com/CSB5/CaDRReS-Sc .

PMID:34915921 | DOI:10.1186/s13073-021-01000-y

Curr Opin Pharmacol. 2021 Nov 18;62:43-59. doi: 10.1016/j.coph.2021.11.002. Online ahead of print.

ABSTRACT

To face the COVID-19 pandemic, prophylactic vaccines have been developed in record time, but vaccine coverage is still limited, accessibility is not equitable worldwide, and the vaccines are not fully effective against emerging variants. Therefore, therapeutic treatments are urgently needed to control the pandemic and treat vulnerable populations, but despite all efforts made, options remain scarce. However, the knowledge gained during 2020 constitutes an invaluable platform from which to build future therapies. In this review, we highlight the main drug repurposing strategies and achievements made over the first 18 months of the pandemic, but also discuss the antivirals, immunomodulators and drug combinations that could be used in the near future to cure COVID-19.

PMID:34915400 | DOI:10.1016/j.coph.2021.11.002

Front Genet. 2021 Nov 29;12:744170. doi: 10.3389/fgene.2021.744170. eCollection 2021.

ABSTRACT

Drug discovery and repurposing against COVID-19 is a highly relevant topic with huge efforts dedicated to delivering novel therapeutics targeting SARS-CoV-2. In this context, computer-aided drug discovery is of interest in orienting the early high throughput screenings and in optimizing the hit identification rate. We herein propose a pipeline for Ligand-Based Drug Discovery (LBDD) against SARS-CoV-2. Through an extensive search of the literature and multiple steps of filtering, we integrated information on 2,610 molecules having a validated effect against SARS-CoV and/or SARS-CoV-2. The chemical structures of these molecules were encoded through multiple systems to be readily useful as input to conventional machine learning (ML) algorithms or deep learning (DL) architectures. We assessed the performances of seven ML algorithms and four DL algorithms in achieving molecule classification into two classes: active and inactive. The Random Forests (RF), Graph Convolutional Network (GCN), and Directed Acyclic Graph (DAG) models achieved the best performances. These models were further optimized through hyperparameter tuning and achieved ROC-AUC scores through cross-validation of 85, 83, and 79% for RF, GCN, and DAG models, respectively. An external validation step on the FDA-approved drugs collection revealed a superior potential of DL algorithms to achieve drug repurposing against SARS-CoV-2 based on the dataset herein presented. Namely, GCN and DAG achieved more than 50% of the true positive rate assessed on the confirmed hits of a PubChem bioassay.

PMID:34912370 | PMC:PMC8667578 | DOI:10.3389/fgene.2021.744170

Genome Med. 2021 Dec 16;13(1):187. doi: 10.1186/s13073-021-01001-x.

ABSTRACT

We present Beyondcell, a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq data and proposing cancer-specific treatments. Our method calculates an enrichment score in a collection of drug signatures, delineating therapeutic clusters (TCs) within cellular populations. Additionally, Beyondcell determines the therapeutic differences among cell populations and generates a prioritised sensitivity-based ranking in order to guide drug selection. We performed Beyondcell analysis in five single-cell datasets and demonstrated that TCs can be exploited to target malignant cells both in cancer cell lines and tumour patients. Beyondcell is available at: https://gitlab.com/bu_cnio/beyondcell .

PMID:34911571 | DOI:10.1186/s13073-021-01001-x

Transl Oncol. 2021 Dec 12;16:101303. doi: 10.1016/j.tranon.2021.101303. Online ahead of print.

ABSTRACT

Sertraline hydrochloride is a first-line antidepressant with potential antineoplastic properties because of its structural similarity with other drugs capable to inhibit the translation-controlled tumor protein (TCTP), a biomolecule involved in cell proliferation. Recent studies suggest it could be repositioned for cancer treatment. In this review, we systematically map the findings that repurpose sertraline as an antitumoral agent, including the mechanisms of action that support this hypotesis. From experimental in vivo and in vitro tumor models of thirteen different types of neoplasms, three mechanisms of action are proposed: apoptosis, autophagy, and drug synergism. The antidepressant is able to inhibit TCTP, modulate chemotherapeutical resistance and exhibit proper cytotoxicity, resulting in reduced cell counting (in vitro) and shrunken tumor masses (in vivo). A mathematical equation determined possible doses to be used in human beings, supporting that sertraline could be explored in clinical trials as a TCTP-inhibitor.

PMID:34911014 | DOI:10.1016/j.tranon.2021.101303

OMICS. 2021 Dec 15. doi: 10.1089/omi.2021.0195. Online ahead of print.

ABSTRACT

Gastric cancer (GC) is a prevalent disease worldwide with high mortality and poor treatment success. Early diagnosis of GC and forecasting of its prognosis with the use of biomarkers are directly relevant to achieve both personalized/precision medicine and innovation in cancer therapeutics. Gene expression signatures offer one of the promising avenues of research in this regard, as well as guiding drug repurposing analyses in cancers. Using publicly accessible gene expression datasets from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA), we report here original findings on co-expressed gene modules that are differentially expressed between 133 GC samples and 46 normal tissues, and thus hold potential for novel diagnostic candidates for GC. Furthermore, we found two co-expressed gene modules were significantly associated with poor survival outcomes revealed by survival analysis of the RNA-Seq TCGA datasets. We identified STAT6 (signal transducer and activator of transcription 6) as a key regulator of the identified gene modules. Finally, potential therapeutic drugs that may target and reverse the expression of the identified altered gene modules examined for drug repurposing analyses and the unraveled compounds were further investigated in the literature by the text mining method. Accordingly, we found several repurposed drug candidates, including Trichostatin A, Vorinostat, Parthenolide, Panobinostat, Brefeldin A, Belinostat, and Danusertib. Through text mining analysis and literature search validation, Belinostat and Danusertib were suggested as possible novel drug candidates for GC treatment. These findings collectively inform multiple aspects of GC medical management, including its precision diagnosis, forecasting of possible outcomes, and drug repurposing for innovation in GC medicines in the future.

PMID:34910889 | DOI:10.1089/omi.2021.0195

Curr Res Pharmacol Drug Discov. 2021 Jun 9;2:100041. doi: 10.1016/j.crphar.2021.100041. eCollection 2021.

ABSTRACT

Psoriasis is a chronic inflammatory autoimmune condition manifested by the hyperproliferation of keratinocytes with buildup of inflammatory red patches and scales on skin surfaces. The available treatment options for the management of psoriasis have various drawbacks, and the clinical need for effective therapeutics for this disease remain unmet; therefore, the approaches of drug repurposing or drug repositioning could potentially be used for treating indications of psoriasis. The undiscovered potential of drug repurposing or repositioning compensates for the limitations and hurdles in drug discovery and drug development processes. Drugs initially approved for other indications, including anticancer, antidiabetic, antihypertensive, and anti-arthritic activities, are being investigated for their potential in psoriasis management as a new therapeutic indication by using repurposing strategies. This article envisages the potential of various therapeutics for the management of psoriasis.

PMID:34909670 | PMC:PMC8663928 | DOI:10.1016/j.crphar.2021.100041