In silico identification of available drugs targeting cell surface BiP to disrupt SARS-CoV-2 binding and replication: Drug repurposing approach

Discovering common pathogenetic processes between COVID-19 and tuberculosis by bioinformatics and system biology approach

Introduction

The coronavirus disease 2019 (COVID-19) pandemic, stemming from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has persistently threatened the global health system. Meanwhile, tuberculosis (TB) caused by Mycobacterium tuberculosis (M. tuberculosis) still continues to be endemic in various regions of the world. There is a certain degree of similarity between the clinical features of COVID-19 and TB, but the underlying common pathogenetic processes between COVID-19 and TB are not well understood.

Methods

To elucidate the common pathogenetic processes between COVID-19 and TB, we implemented bioinformatics and systematic research to obtain shared pathways and molecular biomarkers. Here, the RNA-seq datasets (GSE196822 and GSE126614) are used to extract shared differentially expressed genes (DEGs) of COVID-19 and TB. The common DEGs were used to identify common pathways, hub genes, transcriptional regulatory networks, and potential drugs.

Results

A total of 96 common DEGs were selected for subsequent analyses. Functional enrichment analyses showed that viral genome replication and immune-related pathways collectively contributed to the development and progression of TB and COVID-19. Based on the protein-protein interaction (PPI) network analysis, we identified 10 hub genes, including IFI44L, ISG15, MX1, IFI44, OASL, RSAD2, GBP1, OAS1, IFI6, and HERC5. Subsequently, the transcription factor (TF)-gene interaction and microRNA (miRNA)-gene coregulatory network identified 61 TFs and 29 miRNAs. Notably, we identified 10 potential drugs to treat TB and COVID-19, namely suloctidil, prenylamine, acetohexamide, terfenadine, prochlorperazine, 3'-azido-3'-deoxythymidine, chlorophyllin, etoposide, clioquinol, and propofol.

Conclusion

This research provides novel strategies and valuable references for the treatment of tuberculosis and COVID-19.

Functions of MAP3Ks in antiviral immunity

Immune signal transduction is crucial to the body's defense against viral infection. Recognition of pathogen-associated molecular patterns by pattern recognition receptors (PRRs) activates the transcription of interferon regulators and nuclear factor-κB (NF-κB); this promotes the release of interferons and inflammatory factors. Efficient regulation of type I interferon and NF-κB signaling by members of the mitogen-activated protein (MAP) kinase kinase kinase (MAP3K) family plays an important role in antiviral immunity. Elucidating the specific roles of MAP3K activation during viral infection is essential to develop effective antiviral therapies. In this review, we outline the specific regulatory mechanisms of MAP3Ks in antiviral immunity and discuss the feasibility of targeting MAP3Ks for the treatment of virus-induced diseases.

Type I Interferon Pathway-Related Hub Genes as a Potential Therapeutic Target for SARS-CoV-2 Omicron Variant-Induced Symptoms

BACKGROUND

The global pandemic of COVID-19 is caused by the rapidly evolving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The clinical presentation of SARS-CoV-2 Omicron variant infection varies from asymptomatic to severe disease with diverse symptoms. However, the underlying mechanisms responsible for these symptoms remain incompletely understood.

METHODS

Transcriptome datasets from peripheral blood mononuclear cells (PBMCs) of COVID-19 patients infected with the Omicron variant and healthy volunteers were obtained from public databases. A comprehensive bioinformatics analysis was performed to identify hub genes associated with the Omicron variant. Hub genes were validated using quantitative RT-qPCR and clinical data. DSigDB database predicted potential therapeutic agents.

RESULTS

Seven hub genes (IFI44, IFI44L, MX1, OAS3, USP18, IFI27, and ISG15) were potential biomarkers for Omicron infection's symptomatic diagnosis and treatment. Type I interferon-related hub genes regulated Omicron-induced symptoms, which is supported by independent datasets and RT-qPCR validation. Immune cell analysis showed elevated monocytes and reduced lymphocytes in COVID-19 patients, which is consistent with retrospective clinical data. Additionally, ten potential therapeutic agents were screened for COVID-19 treatment, targeting the hub genes.

CONCLUSIONS

This study provides insights into the mechanisms underlying type I interferon-related pathways in the development and recovery of COVID-19 symptoms during Omicron infection. Seven hub genes were identified as promising biological biomarkers for diagnosing and treating Omicron infection. The identified biomarkers and potential therapeutic agent offer valuable implications for Omicron's clinical manifestations and treatment strategies.

Peptides as Pharmacological Carriers to the Brain: Promises, Shortcomings and Challenges

Central nervous system (CNS) diseases are among the most difficult to treat, mainly because the vast majority of the drugs fail to cross the blood-brain barrier (BBB) or to reach the brain at concentrations adequate to exert a pharmacological activity. The obstacle posed by the BBB has led to the in-depth study of strategies allowing the brain delivery of CNS-active drugs. Among the most promising strategies is the use of peptides addressed to the BBB. Peptides are versatile molecules that can be used to decorate nanoparticles or can be conjugated to drugs, with either a stable link or as pro-drugs. They have been used to deliver to the brain both small molecules and proteins, with applications in diverse therapeutic areas such as brain cancers, neurodegenerative diseases and imaging. Peptides can be generally classified as receptor-targeted, recognizing membrane proteins expressed by the BBB microvessels (e.g., Angiopep2, CDX, and iRGD), "cell-penetrating peptides" (CPPs; e.g. TAT_47-57, SynB1/3, and Penetratin), undergoing transcytosis through unspecific mechanisms, or those exploiting a mixed approach. The advantages of peptides have been extensively pointed out, but so far few studies have focused on the potential negative aspects. Indeed, despite having a generally good safety profile, some peptide conjugates may display toxicological characteristics distinct from those of the peptide itself, causing for instance antigenicity, cardiovascular alterations or hemolysis. Other shortcomings are the often brief lifetime in vivo, caused by the presence of peptidases, the vulnerability to endosomal/lysosomal degradation, and the frequently still insufficient attainable increase of brain drug levels, which remain below the therapeutically useful concentrations. The aim of this review is to analyze not only the successful and promising aspects of the use of peptides in brain targeting but also the problems posed by this strategy for drug delivery.

Bioinformatics and systems-biology analysis to determine the effects of Coronavirus disease 2019 on patients with allergic asthma

Background

The coronavirus disease (COVID-19) pandemic has posed a significant challenge for global health systems. Increasing evidence shows that asthma phenotypes and comorbidities are major risk factors for COVID-19 symptom severity. However, the molecular mechanisms underlying the association between COVID-19 and asthma are poorly understood. Therefore, we conducted bioinformatics and systems biology analysis to identify common pathways and molecular biomarkers in patients with COVID-19 and asthma, as well as potential molecular mechanisms and candidate drugs for treating patients with both COVID-19 and asthma.

Methods

Two sets of differentially expressed genes (DEGs) from the GSE171110 and GSE143192 datasets were intersected to identify common hub genes, shared pathways, and candidate drugs. In addition, murine models were utilized to explore the expression levels and associations of the hub genes in asthma and lung inflammation/injury.

Results

We discovered 157 common DEGs between the asthma and COVID-19 datasets. A protein–protein-interaction network was built using various combinatorial statistical approaches and bioinformatics tools, which revealed several hub genes and critical modules. Six of the hub genes were markedly elevated in murine asthmatic lungs and were positively associated with IL-5, IL-13 and MUC5AC, which are the key mediators of allergic asthma. Gene Ontology and pathway analysis revealed common associations between asthma and COVID-19 progression. Finally, we identified transcription factor–gene interactions, DEG–microRNA coregulatory networks, and potential drug and chemical-compound interactions using the hub genes.

Conclusion

We identified the top 15 hub genes that can be used as novel biomarkers of COVID-19 and asthma and discovered several promising candidate drugs that might be helpful for treating patients with COVID-19 and asthma.

Target and drug predictions for SARS-CoV-2 infection in hepatocellular carcinoma patients

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the coronavirus disease (COVID-19), which poses a major threat to humans worldwide. With the continuous progress of the pandemic, a growing number of people are infected with SARS-CoV-2, including hepatocellular carcinoma (HCC) patients. However, the relationship between COVID-19 and HCC has not been fully elucidated. In order to provide better treatment for HCC patients infected with SARS-CoV-2, it’s urgently needed to identify common targets and find effective drugs for both. In our study, transcriptomic analysis was performed on both selected lung epithelial cell datasets of COVID-19 patients and the datasets of HCC patients to identify the synergistic effect of COVID-19 in HCC patients. What’s more, common differentially expressed genes were identified, and a protein-protein interactions network was designed. Then, hub genes and basic modules were detected based on the protein-protein interactions network. Next, functional analysis was performed using gene ontology terminology and the Kyoto Encyclopedia of Genes and Genomes pathway. Finally, protein-protein interactions revealed COVID-19 interaction with key proteins associated with HCC and further identified transcription factor (TF) genes and microRNAs (miRNA) with differentially expressed gene interactions and transcription factor activity. This study reveals that COVID-19 and HCC are closely linked at the molecular level and proposes drugs that may play an important role in HCC patients with COVID-19. More importantly, according to the results of our research, two critical drugs, Ilomastat and Palmatine, may be effective for HCC patients with COVID-19, which provides clinicians with a novel therapeutic idea when facing possible complications in HCC patients with COVID-19.

High predictive QSAR models for predicting the SARS coronavirus main protease inhibition activity of ketone-based covalent inhibitors

In this research, a dataset including 29 ketone-based covalent inhibitors with SARS-CoV-1 3CL^pro inhibition activity was used to develop high predictive QSAR models. Twenty-two molecules were put in train set and seven molecules in test set. By using stepwise MLR method for molecules in train set, four molecular descriptors including Mor26p, Hy, GATS7p and Mor04v were selected to build QSAR models. MLR and ANN methods were used to create QSAR models for predicting the activity of molecules in both train and test sets. Both QSAR models were validated by calculating several statistical parameters. R² values for the test set of MLR and ANN models were 0.93 and 0.95, respectively, and RMSE values for their test sets were 0.24 and 0.17, respectively. Other calculated statistical parameters (especially \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$Q_{F3}^{2}$$\end{document}QF32 parameter) show that created ANN model has more predictive power with respect to developed MLR model (with four descriptor). Calculated leverages for all molecules show that predicted pIC₅₀ (by both QSAR models) for all molecules is acceptable, and drawn residuals plots show that there is no systematic error in building both QSAR modes. Also, based on developed MLR model, used molecular descriptors were interpreted.

Thyroid Cancer and COVID-19: Prospects for Therapeutic Approaches and Drug Development

Thyroid cancer is the most prevalent endocrine malignancy and the reported incidence of thyroid cancer has continued to increase in recent years. Since 2019, coronavirus disease 2019 (COVID-19) has been spreading worldwide in a global pandemic. COVID-19 aggravates primary illnesses and affects disease management; relevant changes include delayed diagnosis and treatment. The thyroid is an endocrine organ that is susceptible to autoimmune attack; thus, thyroid cancer after COVID-19 has gradually attracted attention. Whether COVID-19 affects the diagnosis and treatment of thyroid cancer has also attracted the attention of many researchers. This review examines the literature regarding the influence of COVID-19 on the pathogenesis, diagnosis, and treatment of thyroid cancer; it also focuses on drug therapies to promote research into strategies for improving therapy and management in thyroid cancer patients with COVID-19.

Nonsteroidal anti-inflammatory drugs and glucocorticoids in COVID-19

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is characterized by a wide spectrum of symptom severity, which is manifested at different phases of infection and demands different levels of care. Viral load, host innate-immune response to SARS-CoV-2, and comorbidities have a direct impact on the clinical outcomes of COVID-19 patients and determine the diverse disease trajectories. The initial SARS-CoV-2 penetrance and replication in the host causes death of infected cells, determining the viral response. SARS-CoV-2 replication in the host triggers the activation of host antiviral immune mechanisms, determining the inflammatory response. While a healthy immune response is essential to eliminate infected cells and prevent spread of the virus, a dysfunctional immune response can result in a cytokine storm and hyperinflammation, contributing to disease progression.

Current therapies for COVID-19 target the virus and/or the host immune system and may be complicated in their efficacy by comorbidities. Here we review the evidence for use of two classes of anti-inflammatory drugs, glucocorticoids and nonsteroidal anti-inflammatory drugs (NSAIDs) for the treatment of COVID-19. We consider the clinical evidence regarding the timing and efficacy of their use, their potential limitations, current recommendations and the prospect of future studies by these and related therapies.

A Repurposed Drug Screen Identifies Compounds That Inhibit the Binding of the COVID-19 Spike Protein to ACE2

Repurposed drugs that block the interaction between the SARS-CoV-2 spike protein and its receptor ACE2 could offer a rapid route to novel COVID-19 treatments or prophylactics. Here, we screened 2,701 compounds from a commercial library of drugs approved by international regulatory agencies for their ability to inhibit the binding of recombinant, trimeric SARS-CoV-2 spike protein to recombinant human ACE2. We identified 56 compounds that inhibited binding in a concentration-dependent manner, measured the IC50 of binding inhibition, and computationally modeled the docking of the best inhibitors to the Spike-ACE2 binding interface. The best candidates were Thiostrepton, Oxytocin, Nilotinib, and Hydroxycamptothecin with IC50's in the 4-9 μM range. These results highlight an effective screening approach to identify compounds capable of disrupting the Spike-ACE2 interaction, as well as identify several potential inhibitors of the Spike-ACE2 interaction.