Epigallocatechin Gallate: A Multifaceted Molecule for Neurological Disorders and Neurotropic Viral Infections.

Epigallocatechin-3-gallate (EGCG), a polyphenolic moiety found in green tea extracts, exhibits pleiotropic bioactivities to combat many diseases including neurological ailments. These neurological diseases include Alzheimer's disease, multiple sclerosis, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. For instance, in the case of Alzheimer's disease, the formation of a ß-sheet in the region of the 10th-21st amino acids was significantly reduced in EGCG-induced oligomeric samples of Aß40. Its interference induces the formation of Aß structures with an increase in intercenter-of-mass distances, reduction in interchain/intrachain contacts, reduction in ß-sheet propensity, and increase in α-helix. Besides, numerous neurotropic viruses are known to instigate or aggravate neurological ailments. It exerts an effect on the oxidative damage caused in neurodegenerative disorders by acting on GSK3-ß, PI3K/Akt, and downstream signaling pathways via caspase-3 and cytochrome-c. EGCG also diminishes these viral-mediated effects, such as EGCG delayed HSV-1 infection by blocking the entry for virions, inhibitory effects on NS3/4A protease or NS5B polymerase of HCV and potent inhibitor of ZIKV NS2B-NS3pro/NS3 serine protease (NS3-SP). It showed a reduction in the neurotoxic properties of HIV-gp120 and Tat in the presence of IFN-γ. EGCG also involves numerous viral-mediated inflammatory cascades, such as JAK/STAT. Nonetheless, it also inhibits the Epstein-Barr virus replication protein (Zta and Rta). Moreover, it also impedes certain viruses (influenza A and B strains) by hijacking the endosomal and lysosomal compartments. Therefore, the current article aims to describe the importance of EGCG in numerous neurological diseases and its inhibitory effect against neurotropic viruses.

Genome-wide screening and identification of potential kinases involved in endoplasmic reticulum stress responses.

AIM: This study aims to identify endoplasmic reticulum stress response elements (ERSE) in the human genome to explore potentially regulated genes, including kinases and transcription factors, involved in the endoplasmic reticulum (ER) stress and its related diseases. MATERIALS AND METHODS: Python-based whole genome screening of ERSE was performed using the Amazon Web Services elastic computing system. The Kinome database was used to filter out the kinases from the extracted list of ERSE-related genes. Additionally, network analysis and genome enrichment were achieved using NDEx, the Network and Data Exchange software, and web-based computational tools. To validate the gene expression, quantitative RT-PCR was performed for selected kinases from the list by exposing the HeLa cells to tunicamycin and brefeldin, ER stress inducers, for various time points. KEY FINDINGS: The overall number of ERSE-associated genes follows a similar pattern in humans, mice, and rats, demonstrating the ERSE's conservation in mammals. A total of 2705 ERSE sequences were discovered in the human genome (GRCh38.p14), from which we identified 36 kinases encoding genes. Gene expression analysis has shown a significant change in the expression of selected genes under ER stress conditions in HeLa cells, supporting our finding. SIGNIFICANCE: In this study, we have introduced a rapid method using Amazon cloud-based services for genome-wide screening of ERSE sequences from both positive and negative strands, which covers the entire genome reference sequences. Approximately 10 % of human protein-protein interactomes were found to be associated with ERSE-related genes. Our study also provides a rich resource of human ER stress-response-based protein networks and transcription factor interactions and a reference point for future research aiming at targeted therapeutics.