Network pharmacology and molecular docking-based investigations of Kochiae Fructus's active phytomolecules, molecular targets, and pathways in treating COVID-19.

COVID-19 disease is caused by SARS-CoV-2. Hyper-inflammation mediated by proinflammatory cytokines is humans' primary etiology of SARS-CoV-2 infection. Kochiae Fructus is widely used in China as traditional Chinese medicine (TCM) to treat inflammatory diseases. Due to its anti-inflammatory properties, we hypothesized that Kochiae Fructus would be a promising therapeutic agent for COVID-19. The active phytomolecules, targets, and molecular pathways of Kochiae Fructus in treating COVID-19 have not been explored yet. Network pharmacology analysis was performed to determine the active phytomolecules, molecular targets, and pathways of Kochiae Fructus. The phytomolecules in Kochiae Fructus were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and their potential targets were predicted with the SwissTargetPrediction webserver. COVID-19-related targets were recovered from the GeneCards database. Intersecting targets were determined with the VENNY tool. The Protein-protein interaction (PPI) and Molecular Complex Detection (MCODE) network analyses were constructed using the Cytoscape software. Using the DAVID tool, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the intersecting targets. AutoDock Vina (version 1.2.0.) was used for molecular docking analysis. Six active phytomolecules and 165 their potential targets, 1,745 COVID-19-related targets, and 34 intersecting targets were identified. Network analysis determined 13 anti-COVID-19 core targets and three key active phytomolecules (Oleanolic acid, 9E,12Z-octadecadienoic acid, and 11,14-eicosadienoic acid). Three key pathways (pathways in cancer, the TNF signaling pathway, and lipid and atherosclerosis) and the top six anti-COVID-19 core targets (IL-6, PPARG, MAPK3, PTGS2, ICAM1, and MAPK1) were determined to be involved in the treatment of COVID-19 with active phytomolecules of Kochiae Fructus. Molecular docking analysis revealed that three key active phytomolecules of Kochiae Fructus had a regulatory effect on the identified anti-COVID-19 core targets. Hence, these findings offer a foundation for developing anti-COVID-19 drugs based on phytomolecules of Kochiae Fructus.

Homocysteine metabolism as the target for predictive medical approach, disease prevention, prognosis, and treatments tailored to the person.

Homocysteine (Hcy) metabolism is crucial for regulating methionine availability, protein homeostasis, and DNA-methylation presenting, therefore, key pathways in post-genomic and epigenetic regulation mechanisms. Consequently, impaired Hcy metabolism leading to elevated concentrations of Hcy in the blood plasma (hyperhomocysteinemia) is linked to the overproduction of free radicals, induced oxidative stress, mitochondrial impairments, systemic inflammation and increased risks of eye disorders, coronary artery diseases, atherosclerosis, myocardial infarction, ischemic stroke, thrombotic events, cancer development and progression, osteoporosis, neurodegenerative disorders, pregnancy complications, delayed healing processes, and poor COVID-19 outcomes, among others. This review focuses on the homocysteine metabolism impairments relevant for various pathological conditions. Innovative strategies in the framework of 3P medicine consider Hcy metabolic pathways as the specific target for in vitro diagnostics, predictive medical approaches, cost-effective preventive measures, and optimized treatments tailored to the individualized patient profiles in primary, secondary, and tertiary care.

COVID-19-associated inhibition of energy accumulation pathways in human semen samples.

OBJECTIVE: To investigate transcriptional alterations in human semen samples associated with COVID-19 infection. DESIGN: Retrospective observational cohort study. SETTING: City hospital. PATIENTS: Ten patients who had recovered from mild COVID-19 infection. Eight of these patients had different sperm abnormalities that were diagnosed before infection. The control group consisted of 5 healthy donors without known abnormalities and no history of COVID-19 infection. INTERVENTIONS: We used RNA sequencing to determine gene expression profiles in all studied biosamples. Original standard bioinformatic instruments were used to analyze activation of intracellular molecular pathways. MAIN OUTCOME MEASURES: Routine semen analysis, gene expression levels, and molecular pathway activation levels in semen samples. RESULTS: We found statistically significant inhibition of genes associated with energy production pathways in the mitochondria, including genes involved in the electron transfer chain and genes involved in toll-like receptor signaling. All protein-coding genes encoded by the mitochondrial genome were significantly down-regulated in semen samples collected from patients after recovery from COVID-19. CONCLUSIONS: Our results may provide a molecular basis for the previously observed phenomenon of decreased sperm motility associated with COVID-19 infection. Moreover, the data will be beneficial for the optimization of preconception care for men who have recently recovered from COVID-19 infection.

Integrated multi-omics approach identified molecular mechanism and pathogenetic processes of COVID-19 that affect patient with Parkinson's disorder.

The novel coronavirus named SARS-CoV-2 has emerged at the end of 2019, which causes coronavirus disease (COVID-2019). Recent case reports of COVID-19 patients have revealed the onset of Parkinson's disease (PD) symptoms in patients who do not have a family history of the PD. However, till recently, no genetic impact or mechanisms that may induce Parkinsonism in COVID-19 patients or after COVID-19 have been found.. This study aimed to detect the commonly dysregulated genes, transcriptional regulators, and pathways between PD and COVID-19. We integrated genome-wide transcriptomic datasets from peripheral blood mononuclear cells (PBMC) samples from COVID-19 and PD and associated pathways. Our study revealed 81 upregulated and 48 downregulated differentially expressed genes (DEGs) shared between PD and COVID-19. These dysregulated genes were involved in key pathways "mitochondrion structure organization", "cell activation in immune response", and "signalling by interleukins". Our analysis showed RELA, TP53 and SP1 TFs that may regulate the upregulated DEGs. We have discovered key dysregulated genes and characterized the biological processes of commonly dysregulated in COVID-19 and PD, which could be used for the design of personalized treatment of PD following COVID-19.

Discovering common pathogenetic processes between COVID-19 and diabetes mellitus by differential gene expression pattern analysis.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the newly discovered coronavirus, SARS-CoV-2. Increased severity of COVID-19 has been observed in patients with diabetes mellitus (DM). This study aimed to identify common transcriptional signatures, regulators and pathways between COVID-19 and DM. We have integrated human whole-genome transcriptomic datasets from COVID-19 and DM, followed by functional assessment with gene ontology (GO) and pathway analyses. In peripheral blood mononuclear cells (PBMCs), among the upregulated differentially expressed genes (DEGs), 32 were found to be commonly modulated in COVID-19 and type 2 diabetes (T2D), while 10 DEGs were commonly downregulated. As regards type 1 diabetes (T1D), 21 DEGs were commonly upregulated, and 29 DEGs were commonly downregulated in COVID-19 and T1D. Moreover, 35 DEGs were commonly upregulated in SARS-CoV-2 infected pancreas organoids and T2D islets, while 14 were commonly downregulated. Several GO terms were found in common between COVID-19 and DM. Prediction of the putative transcription factors involved in the upregulation of genes in COVID-19 and DM identified RELA to be implicated in both PBMCs and pancreas. Here, for the first time, we have characterized the biological processes and pathways commonly dysregulated in COVID-19 and DM, which could be in the next future used for the design of personalized treatment of COVID-19 patients suffering from DM as comorbidity.

Positive influence of gut microbiota on the effects of Korean red ginseng in metabolic syndrome: a randomized, double-blind, placebo-controlled clinical trial.

BACKGROUND: Ginseng, a traditional herbal medicine, has been used for thousands of years to treat various diseases including metabolic syndrome (MS). However, the underlying mechanism(s) of such beneficial actions of ginseng against MS is poorly understood. Emerging evidence indicates a close association of the host gut microbiota with MS. The present study was conducted to examine, whether the beneficial effects of Korean red ginseng (KRG) against MS could be influenced by gut microbial population and whether gut microbial profile could be considered a valuable biomarker for targeted treatment strategy for MS in compliance with the predictive, preventive, and personalized medicine (PPPM / 3PM). METHODS: This clinical study was a randomized, double-blind, placebo-controlled trial evaluating the effects of KRG treatment for 8 weeks on patients with MS. The anthropometric parameters, vital signs, metabolic biomarkers, and gut microbial composition through 16S rRNA gene sequencing were assessed at the baseline and endpoint. The impact of KRG was also evaluated after categorizing the subjects into responders and non-responders, as well as enterotypes 1 and 2 based on their gut microbial profile at the baseline. RESULTS: Fifty out of 60 subjects who meet the MS criteria completed the trial without showing adverse reactions. The KRG treatment caused a significant decrease in systolic blood pressure (SBP). Microbial analysis revealed a decrease in Firmicutes, Proteobacteria, and an increase in Bacteroidetes in response to KRG. In patient stratification analysis, the responders showing marked improvement in the serum levels of lipid metabolic biomarkers TC and LDL due to the KRG treatment exhibited higher population of both the family Lachnospiraceae and order Clostridiales compared to the non-responders. The homeostasis model assessment-insulin resistance (HOMA-IR) and insulin level were decreased in enterotype 1 (Bacteroides-abundant group) and increased in enterotype 2 (prevotella-abundant group) following the KRG treatment. CONCLUSION: In this study, the effects of KRG on the glucose metabolism in MS patients were influenced by the relative abundances of gut microbial population and differed according to the individual enterotype. Therefore, the analysis of enterotype categories is considered to be helpful in predicting the effectiveness of KRG on glucose homeostasis of MS patients individually. This will further help to decide on the appropriate treatment strategy for MS, in compliance with the perspective of PPPM.

Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach.

COVID-19 has emerged as global health threats. Chronic kidney disease (CKD) patients are immune-compromised and may have a high risk of infection by the SARS-CoV-2. We aimed to detect common transcriptomic signatures and pathways between COVID-19 and CKD by systems biology analysis. We analyzed transcriptomic data obtained from peripheral blood mononuclear cells (PBMC) infected with SARS-CoV-2 and PBMC of CKD patients. We identified 49 differentially expressed genes (DEGs) which were common between COVID-19 and CKD. The gene ontology and pathways analysis showed the DEGs were associated with "platelet degranulation", "regulation of wound healing", "platelet activation", "focal adhesion", "regulation of actin cytoskeleton" and "PI3K-Akt signalling pathway". The protein-protein interaction (PPI) network encoded by the common DEGs showed ten hub proteins (EPHB2, PRKAR2B, CAV1, ARHGEF12, HSP90B1, ITGA2B, BCL2L1, E2F1, TUBB1, and C3). Besides, we identified significant transcription factors and microRNAs that may regulate the common DEGs. We investigated protein-drug interaction analysis and identified potential drugs namely, aspirin, estradiol, rapamycin, and nebivolol. The identified common gene signature and pathways between COVID-19 and CKD may be therapeutic targets in COVID-19 patients with CKD comorbidity.

Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential.

The pestilential pathogen SARS-CoV-2 has led to a seemingly ceaseless pandemic of COVID-19. The healthcare sector is under a tremendous burden, thus necessitating the prognosis of COVID-19 severity. This in-depth study of plasma proteome alteration provides insights into the host physiological response towards the infection and also reveals the potential prognostic markers of the disease. Using label-free quantitative proteomics, we performed deep plasma proteome analysis in a cohort of 71 patients (20 COVID-19 negative, 18 COVID-19 non-severe, and 33 severe) to understand the disease dynamics. Of the 1200 proteins detected in the patient plasma, 38 proteins were identified to be differentially expressed between non-severe and severe groups. The altered plasma proteome revealed significant dysregulation in the pathways related to peptidase activity, regulated exocytosis, blood coagulation, complement activation, leukocyte activation involved in immune response, and response to glucocorticoid biological processes in severe cases of SARS-CoV-2 infection. Furthermore, we employed supervised machine learning (ML) approaches using a linear support vector machine model to identify the classifiers of patients with non-severe and severe COVID-19. The model used a selected panel of 20 proteins and classified the samples based on the severity with a classification accuracy of 0.84. Putative biomarkers such as angiotensinogen and SERPING1 and ML-derived classifiers including the apolipoprotein B, SERPINA3, and fibrinogen gamma chain were validated by targeted mass spectrometry-based multiple reaction monitoring (MRM) assays. We also employed an in silico screening approach against the identified target proteins for the therapeutic management of COVID-19. We shortlisted two FDA-approved drugs, namely, selinexor and ponatinib, which showed the potential of being repurposed for COVID-19 therapeutics. Overall, this is the first most comprehensive plasma proteome investigation of COVID-19 patients from the Indian population, and provides a set of potential biomarkers for the disease severity progression and targets for therapeutic interventions.