Dataset Information

Analytical approaches for determination of COVID-19 candidate drugs in human biological matrices.

ABSTRACT: Since the outbreak of the COVID-19 pandemic, the use of antiviral and other available drugs has been considered to combat or reduce the clinical symptoms of patients. In this regard, it would be necessary to choose sensitive and selective analytical techniques for pharmacokinetic and pharmacodynamic studies, monitoring of drug concentration in biological fluids, and determination of the most appropriate dose to achieve the desired effect on the disease. In the present study, the analytical techniques based on spectroscopy and chromatography with different detectors for diagnosis and determination of candidate drugs in the treatment of COVID-19 in human biological fluids are reviewed during the period 2015-2022. Moreover, various sample preparation and extraction techniques, are being used for this purpose, such as protein precipitation (PP), solid-phase extraction (SPE), liquid-liquid extraction (LLE), and QuEChERS (quick, easy, cheap, effective, rugged, and safe) are investigated.

SUBMITTER: Mahdavi R

PROVIDER: S-EPMC9922681 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Analytical approaches for determination of COVID-19 candidate drugs in human biological matrices.

Mahdavi Rabee R Talebpour Zahra Z

Trends in analytical chemistry : TRAC 20230213

Since the outbreak of the COVID-19 pandemic, the use of antiviral and other available drugs has been considered to combat or reduce the clinical symptoms of patients. In this regard, it would be necessary to choose sensitive and selective analytical techniques for pharmacokinetic and pharmacodynamic studies, monitoring of drug concentration in biological fluids, and determination of the most appropriate dose to achieve the desired effect on the disease. In the present study, the analytical techn ...[more]

PMID: 36816451

Similar Datasets

Project description:Background: Coronavirus (CoV) is an emerging human pathogen causing severe acute respiratory syndrome (SARS) around the world. Earlier identification of biomarkers for SARS can facilitate detection and reduce the mortality rate of the disease. Thus, by integrated network analysis and structural modeling approach, we aimed to explore the potential drug targets and the candidate drugs for coronavirus medicated SARS. Methods: Differentially expression (DE) analysis of CoV infected host genes (HGs) expression profiles was conducted by using the Limma. Highly integrated DE-CoV-HGs were selected to construct the protein-protein interaction (PPI) network. Results: Using the Walktrap algorithm highly interconnected modules include module 1 (202 nodes); module 2 (126 nodes) and module 3 (121 nodes) modules were retrieved from the PPI network. MYC, HDAC9, NCOA3, CEBPB, VEGFA, BCL3, SMAD3, SMURF1, KLHL12, CBL, ERBB4, and CRKL were identified as potential drug targets (PDTs), which are highly expressed in the human respiratory system after CoV infection. Functional terms growth factor receptor binding, c-type lectin receptor signaling, interleukin-1 mediated signaling, TAP dependent antigen processing and presentation of peptide antigen via MHC class I, stimulatory T cell receptor signaling, and innate immune response signaling pathways, signal transduction and cytokine immune signaling pathways were enriched in the modules. Protein-protein docking results demonstrated the strong binding affinity (-314.57 kcal/mol) of the ERBB4-3cLpro complex which was selected as a drug target. In addition, molecular dynamics simulations indicated the structural stability and flexibility of the ERBB4-3cLpro complex. Further, Wortmannin was proposed as a candidate drug to ERBB4 to control SARS-CoV-2 pathogenesis through inhibit receptor tyrosine kinase-dependent macropinocytosis, MAPK signaling, and NF-kb singling pathways that regulate host cell entry, replication, and modulation of the host immune system. Conclusion: We conclude that CoV drug target "ERBB4" and candidate drug "Wortmannin" provide insights on the possible personalized therapeutics for emerging COVID-19.

Project description:BackgroundThe coronavirus disease 2019 (COVID-19) has become a worldwide public health crisis. At present, there are no effective antiviral drugs to treat COVID-19. Although some vaccines have been developed, late-stage clinical trials that allow licensure by regulatory agencies are still needed. Previous reports have indicated that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and SARS-CoV are highly homologous and both use angiotensin-converting enzyme 2 (ACE2) as the receptor to enter cells, and SARS-CoV infection reduces the ACE2 expression in the lung. Therefore, the analysis of genes co-expressed with ACE2 in the lung may uncover the underlying mechanism of COVID-19. Finally, we used the Connectivity map (Cmap) database to search for candidate drugs using transcriptome profiles of patients with COVID-19.MethodBased on the differentially expressed genes (DEGs), indicated by the expression of RNAs isolated from bronchoalveolar lavage fluid (BALF) cells of patients with COVID-19, we performed functional enrichment analysis and hub gene cluster analysis. Furthermore, we identified genes co-expressed with ACE2 in healthy lung samples and analyzed the significant genes. Additionally, to identify several candidate drugs for the treatment of COVID-19, we queried Cmap using DEGs and genes co-expressed with ACE2.Results and conclusionThe up-regulated genes in the BALF cells of patients with COVID-19 are related to viral mRNA translation. The down-regulated genes are related to immune response functions. Genes positively correlated with ACE2 are related to immune defense and those negatively correlated are enriched in synaptic transmission functions. The results reflected prosperous viral proliferation and immune dysfunction in patients. Furthermore, ACE2 may not only mediate viral entrance, but also play an important role in immune defense. By using Cmap with transcriptome profiles of patients with COVID-19, we identified candidate drugs for the treatment of COVID-19, such as amantadine and acyclovir.

Dataset Information

Analytical approaches for determination of COVID-19 candidate drugs in human biological matrices.

Publications

Analytical approaches for determination of COVID-19 candidate drugs in human biological matrices.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets