Objectives To clarify the work done by using AI for identifying the genomic sequences, development of drugs and vaccines for COVID-19 and to recognize the advantages and challenges of using such technology. Methods A non-systematic review was done. All articles published on Pub-Med, Medline, Google, and Google Scholar on AI or digital health regarding genomic sequencing, drug development, and vaccines of COVID-19 were scrutinized and summarized. Results The sequence of SARS- CoV-2 was identified with the help of AI. It can help also in the prompt identification of variants of concern (VOC) as delta strains and Omicron. Furthermore, there are many drugs applied with the help of AI. These drugs included Atazanavir, Remdesivir, Efavirenz, Ritonavir, and Dolutegravir, PARP1 inhibitors (Olaparib and CVL218 which is Mefuparib hydrochloride), Abacavir, Roflumilast, Almitrine, and Mesylate. Many vaccines were developed utilizing the new technology of bioinformatics, databases, immune-informatics, machine learning, and reverse vaccinology to the whole SARS-CoV-2 proteomes or the structural proteins. Examples of these vaccines are the messenger RNA and viral vector vaccines. AI provides cost-saving and agility. However, the challenges of its usage are the difficulty of collecting data, the internal and external validation, ethical consideration, therapeutic effect, and the time needed for clinical trials after drug approval. Moreover, there is a common problem in the deep learning (DL) model which is the shortage of interpretability. Conclusion The growth of AI techniques in health care opened a broad gate for discovering the genomic sequences of the COVID-19 virus and the VOC. AI helps also in the development of vaccines and drugs (including drug repurposing) to obtain potential preventive and therapeutic agents) for controlling the COVID-19 pandemic.

Abnormal accumulation of misfolded proteins in the endoplasmic reticulum and their aggregation causes inflammation and endoplasmic reticulum stress. This promotes accumulation of toxic proteins in the body tissues especially brain leading to manifestation of neurodegenerative diseases. The studies suggest that deregulation of proteostasis, particularly aberrant unfolded protein response (UPR) signaling, may be a common morbific process in the development of neurodegeneration. Curcumin, the mixture of low molecular weight polyphenolic compounds from turmeric, Curcuma longa has shown promising response to prevents many diseases including current global severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and neurodegenerative disorders. The UPR which correlates positively with neurodegenerative disorders were found affected by curcumin. In this review, we examine the evidence from many model systems illustrating how curcumin interacts with UPR and slows down the development of various neurodegenerative disorders (ND), e.g., Alzheimer’s and Parkinson’s diseases. The recent global increase in ND patients indicates that researchers and practitioners will need to develop a new pharmacological drug or treatment to manage and cure these neurodegenerative diseases.

Lung cancer is one of the most invasive cancers affecting over a million of the population. Non-small cell lung cancer (NSCLC) constitutes up to 85% of all lung cancer cases, and therefore, it is essential to identify predictive biomarkers of NSCLC for therapeutic purposes. Here we use a network theoretical approach to investigate the complex behavior of the NSCLC gene-regulatory interactions. We have used eight NSCLC microarray datasets GSE19188, GSE118370, GSE10072, GSE101929, GSE7670, GSE33532, GSE31547, and GSE31210 and meta-analyzed them to find differentially expressed genes (DEGs) and further constructed a protein–protein interaction (PPI) network. We analyzed its topological properties and identified significant modules of the PPI network using cytoscape network analyzer and MCODE plug-in. From the PPI network, top ten genes of each of the six topological properties like closeness centrality, maximal clique centrality (MCC), Maximum Neighborhood Component (MNC), radiality, EPC (Edge Percolated Component) and bottleneck were considered for key regulator identification. We further compared them with top ten hub genes (those with the highest degrees) to find key regulator (KR) genes. We found that two genes, CDK1 and HSP90AA1, were common in the analysis suggesting a significant regulatory role of CDK1 and HSP90AA1 in non-small cell lung cancer. Our study using a network theoretical approach, as a summary, suggests CDK1 and HSP90AA1 as key regulator genes in complex NSCLC network.

Purpose: Plant-derived phytochemicals have shown epigenetic modulatory effect in different types of cancer by reversing the pattern of DNA methylation and chromatin modulation, thereby restoring the function of silenced tumor-suppressor genes. In the present study, attempts have been made to explore chrysin-mediated epigenetic alterations in HeLa cells.Methods: Colony formation and migration assays followed by methylation-specific PCR for examining the methylation status of CpG promoters of various tumor-suppressor genes (TSGs) and the expression of these TSGs at the transcript and protein levels were performed. Furthermore, global DNA methylation; biochemical activities of DNA methyltransferases (DNMTs), histone methyl transferases (HMTs), histone deacetylases (HDACs), and histone acetyl transferases (HATs) along with the expression analysis of chromatin-modifying enzymes; and H3 and H4 histone modification marks analyses were performed after chrysin treatment.Results: The experimental analyses revealed that chrysin treatment encourages cytostatic behavior as well as inhibits the migration capacity of HeLa cells in a time- and dose-dependent manner. Chrysin reduces the methylation of various tumor-suppressor genes, leading to their reactivation at mRNA and protein levels. The expression levels of various chromatin-modifying enzymes viz DNMTs, HMTs, HDACs, and HATS were found to be decreased, and H3 and H4 histone modification marks were modulated too. Also, reduced global DNA methylation was observed following the treatment of chrysin.Conclusion: This study concludes that chrysin can be used as a potential epigenetic modifier for cancer treatment and warrants for further experimental validation.

Cancer progression is linked to abnormal epigenetic alterations such as DNA methylation and histone modifications. Since epigenetic alterations, unlike genetic changes, are heritable and reversible, they have been considered as interesting targets for cancer prevention and therapy by dietary compounds such as luteolin. In this study, epigenetic modulatory behaviour of luteolin was analysed on HeLa cells. Various assays including colony forming and migration assays, followed by biochemical assays of epigenetic enzymes including DNA methyltransferase, histone methyl transferase, histone acetyl transferase, and histone deacetylases assays were performed. Furthermore, global DNA methylation and methylation-specific PCR for examining the methylation status of CpG promoters of various tumour suppressor genes (TSGs) and the expression of these TSGs at transcript and protein level were performed. It was observed that luteolin inhibited migration and colony formation in HeLa cells. It also modulated DNA methylation at promoters of TSGs and the enzymatic activity of DNMT, HDAC, HMT, and HAT and reduced the global DNA methylation. Decrease in methylation resulted in the reactivation of silenced tumour suppressor genes including FHIT, DAPK1, PTEN, CDH1, SOCS1, TIMPS, VHL, TP53, TP73, etc. Hence, luteolin-targeted epigenetic alterations provide a promising approach for cancer prevention and intervention.