Enumeration of olive derived lignan, pinoresinol for activity against recent Omicron variant spike protein for structure-based drug design, DFT, molecular dynamics simulations, and MMGBSA studies

The coronavirus disease 2019 (COVID-19) was first found in Wuhan, China, in December 2019. Because the virus spreads quickly, it quickly became a global worry. Coronaviridae is the family that contains both SARS-CoV-2 and the viruses that came before (i.e., MERS-CoV and SARS-CoV). Recent sources portray that the COVID-19 virus has affected 344,710,576 people worldwide and killed about 5,598,511 people in the last 2 years. The B.1.1.529 strain, later called "Omicron," was named a Variant of Concern on November 24, 2021. The SARS-CoV-2 virus has gone through a never-ending chain of changes that have never happened before. As a result, it has many different traits. Most of these changes have occurred in the spike protein, where antibodies bind. Because of these changes, the Omicron type is very contagious and easy to pass on. There have been a lot of studies done to try to figure out this new challenge in the COVID-19 strains race, but there is still a lot that needs to be explained. This study focuses on virtual screening, docking, and molecular dynamic analysis; we aimed to identify therapeutic candidates for the SARS-CoV-2 variant Omicron based on their ability to inhibit non-structural proteins. We investigate the prediction of the properties of a substantial database of drug molecules obtained from the OliveNet™ database. Compounds that did not exhibit adequate gastrointestinal absorption and failed the Lipinski test are not considered for further research. The filtered compounds were coupled with our primary target, SARS-CoV-2 Omicron spike protein. We focused on SARS-CoV-2 Omicron spike protein and filtering potent olive compounds. Pinoresinol, the most likely candidate, is bound best (- 8.5 kcal/mol). Pinoresinol's strong interaction with the active site made the complex's dynamic structure more resilient. MD simulations explain the protein-ligand complex's stability and function. Pinoresinol may be a promising SARS-CoV-2 Omicron spike protein receptor lead drug, and additional research may assist the scientific community.

Identification of potential biomarkers for melanoma cancer (black tumor) using bioinformatics strategy: a study based on GEO and SRA datasets

Melanoma, a highly invasive type of skin cancer that penetrates the entire dermis layer, is associated with increased mortality rates. Excessive exposure of the skin to sunlight, specifically ultraviolet radiation, is the underlying cause of this malignant condition. The appearance of unique skin moles represents a visible clue, referred to as the "ugly duckling" sign, indicating the presence of melanoma and its association with cellular DNA damage. This research aims to explore potential biomarkers derived from microarray data, employing bioinformatics techniques and methodologies, for a thorough investigation of melanoma skin cancer. The microarray dataset for melanoma skin cancer was obtained from the GEO database, and thorough data analysis and quality control measures were performed to identify differentially expressed genes (DEGs). The top 14 highly expressed DEGs were identified, and their gene information and protein sequences were retrieved from the NCBI gene and protein database. These proteins were further analyzed for domain identification and network analysis. Gene expression analysis was conducted to visualize the upregulated and downregulated genes. Additionally, gene metabolite network analysis was carried out to understand the interactions between highly interconnected genes and regulatory transcripts. Molecular docking was employed to investigate the ligand-binding sites and visualize the three-dimensional structure of proteins. Our research unveiled a collection of genes with varying expression levels, some elevated and others reduced, which could function as promising biomarkers closely linked to the development and advancement of melanoma skin cancer. Through molecular docking analysis of the GINS2 protein, we identified two natural compounds (PubChem-156021169 and PubChem-60700) with potential as inhibitors against melanoma. This research has implications for early detection, treatment, and understanding the molecular basis of melanoma.