The COVID-19 situation had escalated into an unprecedented global crisis in just a few weeks. On the 30 th of January 2020, World Health Organization officially declared the COVID-19 epidemic as a public health emergency of international concern. The confirmed cases were reported to exceed 105,856,046 globally, with the death toll of above 2,311,048, according to the dashboard from Johns Hopkins University on the 7 th of February, 2021, though the actual figures may be much higher. Conserved regions of the South Asian strains were used to construct a phylogenetic tree to find evolutionary relationships among the novel virus. Off target similarities were searched with other microorganisms that have been previously reported using Basic Local Alignment Search Tool (BLAST). The conserved regions did not match with any previously reported microorganisms or viruses, which confirmed the novelty of SARS-CoV-2. Currently there is no approved drug for the prevention and treatment of COVID-19, but researchers globally are attempting to come up with one or more soon. Therapeutic strategies need to be addressed urgently to combat COVID-19. Successful drug repurposing is a tool that uses old and safe drugs, is time effective and requires lower development costs, and was thus considered for the study. Molecular docking was used for repurposing drugs from our own comprehensive database of approximately 300 highly characterized, existing drugs with known safety profile, to identify compounds that will inhibit the chosen molecular targets -SARS-CoV-2, ACE2, and TMPRSS2. The study has identified and proposed twenty seven candidates for further in vitro and in vivo studies for the treatment of SARS-CoV-2 infection.

Cancer is the major burden of diseases around the world. The incidence and mortality rate of cancers is mounting up with the passage of days. Breast cancer is the most demoralizing cause of death, where both diseases interlocked with each other due to some genetic, biological and behavioral motives. The molecular mechanism of breast cancer through which they crop up and manifest together remains questionable. The genetic basis of protein-protein interactions and gene networks has elucidated a group of gene regulatory systems in Breast cancer. Thus, the extraction of all genomic and proteomic data has enabled unprecedented views of gene-protein co-expression, co-regulation, and interactions in the biological system. This study explored the biological system to develop a gene-disease interaction model by implementing the extracted genomic and proteomic data of Breast cancer. The disease-specific and correlated genes were pulled out and their cabling studied by PPI, disease pathway and drug-disease interaction data to articulate their role in disease development. By analyzing mined genes that are related to breast cancer, a network model is also proposed. Exploration of all the correlated genes, Hub and common genes have given some promising pieces of evidence surrounding the genetic networking models. The result of this prospective study disclosed breast cancer mediated crosslinking or possible metastatic relation on a genetic basis. Moreover, other diseases like prostate, colorectal and ovarian cancers are at the same risk and might count into consideration. The finding provides a narrative broad approach for understanding the genetic basis of these fatal diseases by the pathway analysis with gene regulatory network evaluation.

RNA binding proteins (RBPs) are central regulators of gene expression implicated in all facets of RNA metabolism. As such, they play key roles in cellular physiology and disease etiology. Since different steps of post-transcriptional gene expression tend to occur in specific regions of the cell, including nuclear or cytoplasmic locations, defining the subcellular distribution properties of RBPs is an important step in assessing their potential functions. Here, we present the RBP Image Database, a resource that details the subcellular localization features of 301 RBPs in the human HepG2 and HeLa cell lines, based on the results of systematic immuno-fluorescence studies conducted using a highly validated collection of RBP antibodies and a panel of 12 markers for specific organelles and subcellular structures. The unique features of the RBP Image Database include: (i) hosting of comprehensive representative images for each RBP-marker pair, with ∼250,000 microscopy images; (ii) a manually curated controlled vocabulary of annotation terms detailing the localization features of each factor; and (iii) a user-friendly interface allowing the rapid querying of the data by target or annotation. The RBP Image Database is freely available at https://rnabiology.ircm.qc.ca/RBPImage/.