Transl Oncol. 2021 Nov 22;15(1):101272. doi: 10.1016/j.tranon.2021.101272. Online ahead of print.

ABSTRACT

High-risk neuroblastoma (NB) represents a major clinical challenge in pediatric oncology due to relapse of metastatic, drug-resistant disease, and treatment-related toxicities. An analysis of 1235 primary NB patient dataset revealed significant increase in AKT1 and AKT2 gene expression with cancer stage progression. Additionally, Both AKT1 and AKT2 expression inversely correlate with poor overall survival of NB patients. AKT1 and AKT2 genes code for AKT that drive a major oncogenic cell signaling pathway known in many cancers, including NB. To inhibit AKT pathway, we repurposed an antiviral inhibitor BX-795 that inhibits PDK1, an upstream activator of AKT. BX-795 potently inhibits NB cell proliferation and colony growth in a dose-dependent manner. BX-795 significantly enhances apoptosis and blocks cell cycle progression at mitosis phase in NB. Additionally, BX-795 potently inhibits tumor formation and growth in a NB spheroid tumor model. We further tested dual therapeutic approaches by combining BX-795 with either doxorubicin or crizotinib and found synergistic and significant inhibition of NB growth, in contrast to either drug alone. Overall, our data demonstrate that BX-795 inhibits AKT pathway to inhibit NB growth, and combining BX-795 with current therapies is an effective and clinically tractable therapeutic approach for NB.

PMID:34823094 | DOI:10.1016/j.tranon.2021.101272

Mol Biol Rep. 2021 Nov 25. doi: 10.1007/s11033-021-06977-8. Online ahead of print.

ABSTRACT

Beta-hemoglobinopathies exhibit a heterogeneous clinical picture with varying degrees of clinical severity. Pertaining to the limited treatment options available, where blood transfusion still remains the commonest mode of treatment, pharmacological induction of fetal hemoglobin (HbF) has been a lucrative therapeutic intervention. Till now more than 70 different HbF inducers have been identified. The practical usage of many pharmacological drugs has been limited due to safety concerns. Natural compounds, like Resveratrol, Ripamycin and Bergaptene, with limited cytotoxicity and high efficacy have started capturing the attention of researchers. In this review, we have summarized pharmacological drugs and bioactive compounds isolated from natural sources that have been shown to increase HbF significantly. It primarily discusses recently identified synthetic and natural compounds, their mechanism of action, and their suitable screening platforms, including high throughput drug screening technology and biosensors. It also delves into the topic of combinatorial therapy and drug repurposing for HbF induction. Overall, we aim to provide insights into where we stand in HbF induction strategies for treating β-hemoglobinopathies.

PMID:34822068 | DOI:10.1007/s11033-021-06977-8

Expert Opin Drug Discov. 2021 Nov 24. doi: 10.1080/17460441.2022.2005025. Online ahead of print.

ABSTRACT

INTRODUCTION: SARS-CoV-2 is a highly infectious and deadly coronavirus whose study requires the use of a biosafety level 3 (BSL-3) containment facility to investigate viral biology and pathogenesis, which limits the study of live virus and slows progress towards finding suitable treatments for infection. While vaccines from several companies have proven very effective in combating the virus, few treatments exist for those who do succumb to the viral-induced systemic disease called COVID-19.

AREAS COVERED: This short review focuses on fluorescent quantum dot-based modeling of SARS-CoV-2. New BSL-2 viral models are essential to find small molecules and biologics that may be effective in stopping viral infection as well as treating already infected individuals. Nanoparticles are invaluable tools for biological research as they can be used to both modeling pathogens and serve as a platform for developing vaccines.

EXPERT OPINION: Visualizing viral activity with fluorescent quantum dots enables both biochemical and cell-based assays to detect virus-host receptor interactions, cellular activity after binding to cell plasma membrane, screening for interventions using small molecule drug repurposing, and testing of novel biologics. Quantum dots can also be used for diagnostic assays, vaccine development, and importantly, pan-antiviral drugs to address variants that may escape the immune response.

PMID:34817309 | DOI:10.1080/17460441.2022.2005025

Adv Sci (Weinh). 2021 Nov 23:e2104051. doi: 10.1002/advs.202104051. Online ahead of print.

ABSTRACT

Toll-like receptor (TLR) activation in macrophages plays a critical role in the pathogenesis of acute lung injury (ALI). While TLR inhibition is a promising strategy to control the overwhelming inflammation in ALI, there still lacks effective TLR inhibitors for clinical uses to date. A unique class of peptide-coated gold nanoparticles (GNPs) is previously discovered, which effectively inhibited TLR signaling and protected mice from lipopolysaccharide (LPS)-induced ALI. To fast translate such a discovery into potential clinical applicable nanotherapeutics, herein an elegant strategy of "nano-enabled drug repurposing" with "nano-targeting" is introduced to empower the existing drugs for new uses. Combining transcriptome sequencing with Connectivity Map analysis, it is identified that the proton pump inhibitors (PPIs) share similar mechanisms of action to the discovered GNP-based TLR inhibitor. It is confirmed that PPIs (including omeprazole) do inhibit endosomal TLR signaling and inflammatory responses in macrophages and human peripheral blood mononuclear cells, and exhibits anti-inflammatory activity in an LPS-induced ALI mouse model. The omeprazole is then formulated into a nanoform with liposomes to enhance its macrophage targeting ability and the therapeutic efficacy in vivo. This research provides a new translational strategy of nano-enabled drug repurposing to translate bioactive nanoparticles into clinically used drugs and targeted nano-therapeutics for ALI.

PMID:34816630 | DOI:10.1002/advs.202104051

J Mol Struct. 2021 Nov 19:131920. doi: 10.1016/j.molstruc.2021.131920. Online ahead of print.

ABSTRACT

A new coronavirus strain called as SARS-CoV-2 has emerged from Wuhan, China in late 2019 and it caused a worldwide pandemic in a few months. After the Second World War, it is the biggest calamity observed as there is no specific US Food and Drugs Administration (USFDA) approved drug or vaccine available globally for the treatment. Several clinical trials are ongoing for therapeutic alternatives, however with little success rate. Considering that the time is crucial, the drug repurposing and data obtained from in silico models are one of the most important approaches to identify possible lead inhibitors against SARS-CoV-2. More recently, the Direct Acting Antivirals (DAAs) are emerged as the most promising drugs to control viral infection. The Main Protease (Mpro), a key enzyme in the SARS-CoV-2 replication cycle, is found close homolog to the Hepatitis C Virus (HCV) protease and could be susceptible of blocking its activity by DAAs. In the current study, the DAAs were investigated as antivirals using structure based computational approach against Mpro of SARS-CoV-2 to propose them as new therapeutics. In total, 20 DAAs of HCV, including a reference compound O6K were docked against Mpro. The docked structures were examined and resulted in the identification of six highly promising DAAs i.e. beclabuvir, elbasvir, paritaprevir, grazoprevir, simeprevir, and asunapevir exhibiting high theoretical binding affinity to Mpro from SARS-CoV-2 in comparison to other DAAs. Furthermore, the post docking analysis revealed that Cys145, Glu166, His163, Thr26, His41, and Met165 played potential role for the binding of these DAAs inside binding site of Mpro. Furthermore, the correlation between binding energies were found in accord with the results from the reported IC50s for some DAAs. Overall, the current study provides insight to combat COVID-19 using FDA-approved DAAs as repurposed drugs.

PMID:34815586 | PMC:PMC8602124 | DOI:10.1016/j.molstruc.2021.131920

Biomed Pharmacother. 2021 Nov 20;145:112436. doi: 10.1016/j.biopha.2021.112436. Online ahead of print.

ABSTRACT

Disruption or loss of oligodendrocytes (OLs) and myelin has devastating effects on CNS function and integrity, which occur in diverse neurological disorders, including Multiple Sclerosis (MS), Alzheimer's disease and neuropsychiatric disorders. Hence, there is a need to develop new therapies that promote oligodendrocyte regeneration and myelin repair. A promising approach is drug repurposing, but most agents have potentially contrasting biological actions depending on the cellular context and their dose-dependent effects on intracellular pathways. Here, we have used a combined systems biology and neurobiological approach to identify compounds that exert positive and negative effects on oligodendroglia, depending on concentration. Notably, next generation pharmacogenomic analysis identified the PI3K/Akt modulator LY294002 as the most highly ranked small molecule with both pro- and anti-oligodendroglial concentration-dependent effects. We validated these in silico findings using multidisciplinary approaches to reveal a profoundly bipartite effect of LY294002 on the generation of OPCs and their differentiation into myelinating oligodendrocytes in both postnatal and adult contexts. Finally, we employed transcriptional profiling and signalling pathway activity assays to determine cell-specific mechanisms of action of LY294002 on oligodendrocytes and resolve optimal in vivo conditions required to promote myelin repair. These results demonstrate the power of multidisciplinary strategies in determining the therapeutic potential of small molecules in neurodegenerative disorders.

PMID:34813998 | DOI:10.1016/j.biopha.2021.112436

J Med Chem. 2021 Nov 23. doi: 10.1021/acs.jmedchem.1c01547. Online ahead of print.

ABSTRACT

To fight COVID-19, much effort has been directed toward in vitro drug repurposing. Here, we investigate the impact of colloidal aggregation, a common screening artifact, in these repurposing campaigns. We tested 56 drugs reported as active in biochemical assays for aggregation by dynamic light scattering and by detergent-based enzyme counter screening; 19 formed colloids at concentrations similar to their literature IC50's, and another 14 were problematic. From a common repurposing library, we further selected another 15 drugs that had physical properties resembling known aggregators, finding that six aggregated at micromolar concentrations. This study suggests not only that many of the drugs repurposed for SARS-CoV-2 in biochemical assays are artifacts but that, more generally, at screening-relevant concentrations, even drugs can act artifactually via colloidal aggregation. Rapid detection of these artifacts will allow the community to focus on those molecules that genuinely have potential for treating COVID-19.

PMID:34812616 | DOI:10.1021/acs.jmedchem.1c01547

Mol Inform. 2021 Nov 23:e2100190. doi: 10.1002/minf.202100190. Online ahead of print.

ABSTRACT

Current pandemics propelled research efforts in unprecedented fashion, primarily triggering computational efforts towards new vaccine and drug development as well as drug repurposing. There is an urgent need to design novel drugs with targeted biological activity and minimum adverse reactions that may be useful to manage viral outbreaks. Hence an attempt has been made to develop Machine Learning based predictive models that can be used to assess whether a compound has the potency to be antiviral or not. To this end, a set of 2358 antiviral compounds were compiled from the CAS COVID-19 antiviral SAR dataset whose activity was reported based on IC50 value. A total 1157 two-dimensional molecular descriptors were computed among which, the most highly correlated descriptors were selected using Tree-based, Correlation-based and Mutual information-based feature selection methods. Seven Machine Learning algorithms i. e., Random Forest, XGBoost, Support Vector Machine, KNN, Decision Tree, MLP Classifier and Logistic Regression were benchmarked. The best performance was achieved by the models developed using Random Forest and XGBoost algorithms in all the feature selection methods. The maximum predictive accuracy of both these models was 88 % with internal validation. Whereas, with an external dataset, a maximum accuracy of 93.10 % for XGBoost and 100 % for Random Forest based model was achievable. Furthermore, the study demonstrated scaffold analysis of the molecules as a pragmatic approach to explore the importance of structurally diverse compounds in data driven studies.

PMID:34811938 | DOI:10.1002/minf.202100190

Nat Commun. 2021 Nov 22;12(1):6775. doi: 10.1038/s41467-021-27137-3.

ABSTRACT

Prediction of drug-target interactions (DTI) plays a vital role in drug development in various areas, such as virtual screening, drug repurposing and identification of potential drug side effects. Despite extensive efforts have been invested in perfecting DTI prediction, existing methods still suffer from the high sparsity of DTI datasets and the cold start problem. Here, we develop KGE_NFM, a unified framework for DTI prediction by combining knowledge graph (KG) and recommendation system. This framework firstly learns a low-dimensional representation for various entities in the KG, and then integrates the multimodal information via neural factorization machine (NFM). KGE_NFM is evaluated under three realistic scenarios, and achieves accurate and robust predictions on four benchmark datasets, especially in the scenario of the cold start for proteins. Our results indicate that KGE_NFM provides valuable insight to integrate KG and recommendation system-based techniques into a unified framework for novel DTI discovery.

PMID:34811351 | DOI:10.1038/s41467-021-27137-3

Drug Discov Today. 2021 Nov 19:S1359-6446(21)00494-3. doi: 10.1016/j.drudis.2021.11.013. Online ahead of print.

ABSTRACT

Autophagy is a multistep degradation pathway involving the lysosome, which supports nutrient reuse and metabolic balance, and has been implicated as a process that regulates cancer genesis and development. Targeting tumors by regulating autophagy has become a therapeutic strategy of interest. Drugs with other indications can have antitumor activity by modulating autophagy, providing a shortcut to developing novel antitumor drugs (i.e., drug repurposing/repositioning), as successfully performed for chloroquine (CQ); an increasing number of repurposed drugs have since advanced into clinical trials. In this review, we describe the application of different drug-repurposing approaches in autophagy for the treatment of cancer and focus on repurposing drugs that target autophagy to treat malignant neoplasms.

PMID:34808390 | DOI:10.1016/j.drudis.2021.11.013

ACS Chem Neurosci. 2021 Nov 22. doi: 10.1021/acschemneuro.1c00521. Online ahead of print.

ABSTRACT

Tyrosine kinase inhibitors (TKIs) are antitumor compounds that prevent the phosphorylation of proteins in a biological environment. However, the multitarget performance of TKIs promotes them as possible candidates for drug repositioning. In this work, interaction and inhibition studies through spectroscopic and computational techniques to evaluate the binding effectiveness of lapatinib and pazopanib TKIs to acetylcholinesterase (AChE) are reported. The results indicated potent inhibition at the μM level. The types of inhibition were identified, with pazopanib acting through non-competitive inhibition and lapatinib through acompetitive inhibition. The fluorescence suppression studies indicate a static mechanism for lapatinib-AChE and pazopanib-AChE systems, with a binding constant in the order of 105 M-1. The obtained thermodynamic parameters reveal interactions driven by van der Waals forces and hydrogen bonds in the lapatinib-AChE system (ΔH° and ΔS° < 0). In contrast, the pazopanib-AChE system shows positive ΔH° and ΔS°, characteristic of hydrophobic interactions. The Foster resonance energy transfer study supports the fluorescence studies performed. The 3D fluorescence studies suggest changes in the microenvironment of the tryptophan and tyrosine residues of the protein in contact with lapatinib and pazopanib. The results suggest effective inhibition and moderate interaction of the drugs with AChE, making them interesting for conducting more in-depth repositioning studies as AChE inhibitors.

PMID:34808043 | DOI:10.1021/acschemneuro.1c00521

Infect Dis Ther. 2021 Nov 22. doi: 10.1007/s40121-021-00559-8. Online ahead of print.

ABSTRACT

Antimicrobials are essential for combating infectious diseases. However, an increase in resistance to them is a major cause of concern. The empirical use of drugs in managing COVID-19 and the associated secondary infections have further exacerbated the problem of antimicrobial resistance. Hence, the situation mandates exploring and developing efficient alternatives for the treatment of bacterial and fungal infections in patients suffering from COVID-19 or other viral infections. In this review, we have described the alternatives to conventional antimicrobials that have shown promising results and are at various stages of development. An acceleration of efforts to investigate their potential as therapeutics can provide more treatment options for clinical management of drug-resistant secondary bacterial and fungal infections in the current pandemic and similar potential outbreaks in the future. The alternatives include bacteriophages and their lytic enzymes, anti-fungal enzymes, antimicrobial peptides, nanoparticles and small molecule inhibitors among others. What is required at this stage is to critically examine the challenges in developing the listed compounds and biomolecules as therapeutics and to establish guidelines for their safe and effective application within a suitable time frame. In this review, we have attempted to highlight the importance of rational use of antimicrobials in patients suffering from COVID-19 and boost the deployment of alternative therapeutics.

PMID:34807451 | DOI:10.1007/s40121-021-00559-8

Inform Med Unlocked. 2021;27:100787. doi: 10.1016/j.imu.2021.100787. Epub 2021 Nov 15.

ABSTRACT

Search for new antiviral medications has surged in the past two years due to the COVID-19 crisis. Toll-like receptor 7 (TLR7) is among one of the most important TLR proteins of innate immunity that is responsible for broad antiviral response and immune system control. TLR7 agonists, as both vaccine adjuvants and immune response modulators, are among the top drug candidates for not only our contemporary viral pandemic but also other diseases. The agonists of TLR7 have been utilized as vaccine adjuvants and antiviral agents. In this study, we hybridized a statistical learning-based QSAR model with molecular docking and molecular dynamics simulation to extract new antiviral drugs by drug repurposing of the DrugBank database. First, we manually curated a dataset consisting of TLR7 agonists. The molecular descriptors of these compounds were extracted, and feature engineering was done to restrict the number of features to 45. We applied a statistically inspired modification of the partial least squares (SIMPLS) method to build our QSAR model. In the next stage, the DrugBank database was virtually screened structurally using molecular docking, and the top compounds for the guanosine binding site of TLR were identified. The result of molecular docking was again screened by the ligand-based approach of QSAR to eliminate compounds that do not display strong EC50 values by the previously trained model. We then subjected the final results to molecular dynamics simulation and compared our compounds with imiquimod (an FDA-approved TLR7 agonist) and compound 1 (the most active compound against TLR7 in vitro, EC50 = 0.2 nM). Our results evidently demonstrate that cephalosporins and nucleotide analogues (especially acyclic nucleotide analogues such as adefovir and cidofovir) are computationally potent agonists of TLR7. We finally reviewed some publications about cephalosporins that, just like pieces of a puzzle, completed our conclusion.

PMID:34805481 | PMC:PMC8591993 | DOI:10.1016/j.imu.2021.100787

Turk J Biol. 2021 Aug 30;45(4):459-468. doi: 10.3906/biy-2106-61. eCollection 2021.

ABSTRACT

With the emergence of the new SARS-CoV-2 virus, drug repurposing studies have gained substantial importance. Combined with the efficacy of recent improvements in ligand- and target-based virtual screening approaches, virtual screening has become faster and more productive than ever. In the current study, an FDA library of approved drugs and compounds under clinical investigation were screened for their antiviral activity using the antiviral therapeutic activity binary QSAR model of the MetaCore/MetaDrug platform. Among 6733-compound collection, we found 370 compounds with a normalized therapeutic activity value greater than a cutoff of 0.75. Only these selected compounds were used for molecular docking studies against the SARS-CoV-2 main protease (Mpro). After initial short (10 ns) molecular dynamics (MD) simulations with the top-50 docking scored compounds and following molecular mechanics generalized born surface area (MM/GBSA) calculations, top-10 compounds were subjected to longer (100 ns) MD simulations and end-point MM/GBSA estimations. Our virtual screening protocol yielded Cefuroxime pivoxetil, an ester prodrug of second-generation cephalosporin antibiotic Cefuroxime, as being a considerable molecule for drug repurposing against the SARS-CoV-2 Mpro.

PMID:34803447 | PMC:PMC8573836 | DOI:10.3906/biy-2106-61

Turk J Biol. 2021 Aug 30;45(4):442-458. doi: 10.3906/biy-2012-52. eCollection 2021.

ABSTRACT

Despite COVID-19 turned into a pandemic, no approved drug for the treatment or globally available vaccine is out yet. In such a global emergency, drug repurposing approach that bypasses a costly and long-time demanding drug discovery process is an effective way in search of finding drugs for the COVID-19 treatment. Recent studies showed that SARS-CoV-2 uses neuropilin-1 (NRP1) for host entry. Here we took advantage of structural information of the NRP1 in complex with C-terminal of spike (S) protein of SARS-CoV-2 to identify drugs that may inhibit NRP1 and S protein interaction. U.S. Food and Drug Administration (FDA) approved drugs were screened using docking simulations. Among top drugs, well-tolerated drugs were selected for further analysis. Molecular dynamics (MD) simulations of drugs-NRP1 complexes were run for 100 ns to assess the persistency of binding. MM/GBSA calculations from MD simulations showed that eltrombopag, glimepiride, sitagliptin, dutasteride, and ergotamine stably and strongly bind to NRP1. In silico Alanine scanning analysis revealed that Tyr297, Trp301, and Tyr353 amino acids of NRP1 are critical for drug binding. Validating the effect of drugs analyzed in this paper by experimental studies and clinical trials will expedite the drug discovery process for COVID-19.

PMID:34803446 | PMC:PMC8573850 | DOI:10.3906/biy-2012-52

J Ginseng Res. 2021 Sep;45(5):610-616. doi: 10.1016/j.jgr.2021.06.008. Epub 2021 Jun 24.

ABSTRACT

BACKGROUND: Thymic stromal lymphopoietin (TSLP) acts as a master switch for inflammatory responses. Ginsenoside Rg3 (Rg3) which is an active ingredient of Panax ginseng Meyer (Araliaceae) is known to possess various therapeutic effects. However, a modulatory effect of Rg3 on TSLP expression in the inflammatory responses remains poorly understood.

METHODS: We investigated antiinflammatory effects of Rg3 on an in vitro model using HMC-1 cells stimulated by PMA plus calcium ionophore (PMACI), as well as an in vivo model using PMA-induced mouse ear edema. TSLP and vascular endothelial growth factor (VEGF) levels were detected using enzyme-linked immunosorbent assay or real-time PCR analysis. Murine double minute 2 (MDM2) and hypoxia-inducible factor 1α (HIF1α) expression levels were detected using Western blot analysis.

RESULTS: Rg3 treatment restrained the production and mRNA expression levels of TSLP and VEGF in activated HMC-1 cells. Rg3 down-regulated the MDM2 expression level increased by PMACI stimulation. The HIF1α expression level was also reduced by Rg3 in activated HMC-1 cells. In addition, Rg3-administered mice showed the decreased redness and ear thickness in PMA-irritated ear edema. Rg3 inhibited the TSLP and VEGF levels in the serum and ear tissue homogenate. Moreover, the MDM2 and HIF1α expression levels in the ear tissue homogenate were suppressed by Rg3.

CONCLUSION: Taken together, the current study identifies new mechanistic evidence about MDM2/HIF1α pathway in the antiinflammatory effect of Rg3, providing a new effective therapeutic strategy for the treatment of skin inflammatory diseases.

PMID:34803431 | PMC:PMC8587510 | DOI:10.1016/j.jgr.2021.06.008

Philos Trans A Math Phys Eng Sci. 2022 Jan 10;380(2214):20210127. doi: 10.1098/rsta.2021.0127. Epub 2021 Nov 22.

ABSTRACT

During the COVID-19 pandemic, more than ever, data science has become a powerful weapon in combating an infectious disease epidemic and arguably any future infectious disease epidemic. Computer scientists, data scientists, physicists and mathematicians have joined public health professionals and virologists to confront the largest pandemic in the century by capitalizing on the large-scale 'big data' generated and harnessed for combating the COVID-19 pandemic. In this paper, we review the newly born data science approaches to confronting COVID-19, including the estimation of epidemiological parameters, digital contact tracing, diagnosis, policy-making, resource allocation, risk assessment, mental health surveillance, social media analytics, drug repurposing and drug development. We compare the new approaches with conventional epidemiological studies, discuss lessons we learned from the COVID-19 pandemic, and highlight opportunities and challenges of data science approaches to confronting future infectious disease epidemics. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.

PMID:34802267 | DOI:10.1098/rsta.2021.0127

Carbohydr Res. 2021 Nov 13;511:108478. doi: 10.1016/j.carres.2021.108478. Online ahead of print.

ABSTRACT

α-Glucosidase is a promising target for the treatment of diabetes. Drug repurposing can increase the chances of discovering an active inhibitor. Therefore, this study aimed to identify potential α-glucosidase inhibitor using drug repurposing and in silico strategies. We identified critical amino acid residues of the three α-glucosidase proteins. Based on cross molecular docking studies of three α-glucosidase proteins and drugs in the FDA database, we screened hits with the favorable binding affinities and modes targeting the three proteins. Subsequently, an in vitro activity assay showed that raloxifene was an excellent inhibitor of α-glucosidase. Moreover, molecular dynamics simulations of raloxifene and three proteins were performed to assess the stability of the protein-hit systems in physiological conditions and clarify protein-hit interactions. We also performed the binding free energy calculation, Hirshfeld surface and alanine scanning mutagenesis analyses. These results demonstrated that binding between raloxifene and the three proteins was stable, and the critical amino acid residues of the three proteins formed stable contacts with raloxifene. The molecular mechanisms agree well with its activity, reinforcing that raloxifene is a candidate α-glucosidase inhibitor. Our study smoothes the path for the development of novel a-glucosidase inhibitors with high efficacy and low toxicity for the treatment of diabetes.

PMID:34801925 | DOI:10.1016/j.carres.2021.108478

Arch Biochem Biophys. 2021 Nov 17:109085. doi: 10.1016/j.abb.2021.109085. Online ahead of print.

ABSTRACT

The identification of biomolecules associated with papillary thyroid cancer (PTC) has upmost importance for the elucidation of the disease mechanism and the development of effective diagnostic and treatment strategies. Despite particular findings in this regard, a holistic analysis encompassing molecular data from different biological levels has been lacking. In the present study, a meta-analysis of four transcriptome datasets was performed to identify gene expression signatures in PTC, and reporter molecules were determined by mapping gene expression data onto three major cellular networks, i.e., transcriptional regulatory, protein-protein interaction, and metabolic networks. We identified 282 common genes that were differentially expressed in all PTC datasets. In addition, six proteins (FYN, JUN, LYN, PML, SIN3A, and RARA), two Erb-B2 receptors (ERBB2 and ERBB4), two cyclin-dependent receptors (CDK1 and CDK2), and three histone deacetylase receptors (HDAC1, HDAC2, and HDAC3) came into prominence as proteomic signatures in addition to several metabolites including lactaldehyde and proline at the metabolome level. Significant associations with calcium and MAPK signaling pathways and transcriptional and post-transcriptional activities of 12 TFs and 110 miRNAs were also observed at the regulatory level. Among them, six miRNAs (miR-30b-3p, miR-15b-5p, let-7a-5p, miR-130b-3p, miR-424-5p, and miR-193b-3p) were associated with PTC for the first time in the literature, and the expression levels of miR-30b-3p, miR-15b-5p, and let-7a-5p were found to be predictive of disease prognosis. Drug repositioning and molecular docking simulations revealed that 5 drugs (prochlorperazine, meclizine, rottlerin, cephaeline, and tretinoin) may be useful in the treatment of PTC. Consequently, we report here biomolecule candidates that may be considered as prognostic biomarkers or potential therapeutic targets for further experimental and clinical trials for PTC.

PMID:34800440 | DOI:10.1016/j.abb.2021.109085

J Appl Microbiol. 2021 Nov 20. doi: 10.1111/jam.15377. Online ahead of print.

ABSTRACT

AIM: Antimicrobial resistance (AMR) has become a global concern. Developing novel antimicrobials is one of the most effective approaches in tackling AMR. Considering its relatively low cost and risk, drug repurposing has been proposed as a valuable approach for novel antimicrobial discovery. The aim of this study was to screen for antimicrobial compounds against Streptococcus suis, an important zoonotic bacterial pathogen, from an FDA-approved drug library.

METHODS AND RESULTS: In this study, we tested the antimicrobial activity of 1815 FDA-approved drugs against S. suis. 67 hits were obtained that showed a growth inhibition of more than 98%. After excluding already known antibiotics and antiseptics, twelve compounds were subjected to minimal inhibition concentration (MIC) assessment against S. suis. This showed that pralatrexate, daunorubicin (hydrochloride), teniposide, aclacinomycin A hydrochloride, and floxuridine gave a relatively low MIC, ranging from 0.85 to 5.25 μg/mL. Apart from pralatrexate, the remaining four drugs could also inhibit the growth of antimicrobial-resistant S. suis. It was also demonstrated that these four drugs had better efficacy against Gram-positive bacteria than Gram-negative bacteria. Cytotoxicity assays showed that floxuridine and teniposide had a relatively high 50% cytotoxic concentration (CC50 ). The in vivo efficacy of floxuridine was analyzed using a Galleria mellonella larvae infection model, and the results showed that floxuridine was effective in treating S. suis infection in vivo.

CONCLUSIONS: Five compounds from the FDA-approved drug library showed high antimicrobial activity against S. suis, among which floxuridine displayed potent in vivo efficacy that is worth further development.

SIGNIFICANCE AND IMPACT OF STUDY: Our study identified several antimicrobial compounds that are effective against S. suis, which provides a valuable starting point for further antimicrobial development.

PMID:34800069 | DOI:10.1111/jam.15377