In silico identification of natural product inhibitors against Octamer-binding transcription factor 4 (Oct4) to impede the mechanism of glioma stem cells

In silico investigation of cholesterol-lowering drugs to find potential inhibitors of dehydrosqualene synthase in Staphylococcus aureus

Staphylococcus aureus is a lethal pathogen that can cause various bacterial infections. This study targets the CrtM enzyme of S. aureus, which is crucial for synthesizing golden carotenoid pigment: staphyloxanthin, which provides anti-oxidant activity to this bacterium for combating antimicrobial resistance inside the host cell. The present investigation quests for human SQS inhibitors against the CrtM enzyme by employing structure-based drug design approaches including induced fit docking (IFD), molecular dynamic (MD) simulations, and binding free energy calculations. Depending upon the docking scores, two compounds, lapaquistat acetate and squalestatin analog 20, were identified as the lead molecules exhibit higher affinity toward the CrtM enzyme. These docked complexes were further subjected to 100 ns MD simulation and several thermodynamics parameters were analyzed. Further, the binding free energies (ΔG) were calculated for each simulated protein-ligand complex to study the stability of molecular contacts using the MM-GBSA approach. Pre-ADMET analysis was conducted for systematic evaluation of physicochemical and medicinal chemistry properties of these compounds. The above study suggested that lapaquistat acetate and squalestatin analog 20 can be selected as potential lead candidates with promising binding affinity for the S. aureus CrtM enzyme. This study might provide insights into the discovery of potential drug candidates for S. aureus with a high therapeutic index.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03862-y.

Structural insights into the RNA interaction with Yam bean Mosaic virus (coat protein) from Pachyrhizus erosus using bioinformatics approach

Plants are constantly threatened by a virus infection, i.e., Potyviruses, the second largest genus of plant viruses which results in several million-dollar losses in various essential crops globally. Yam bean (Pachyrhizus erosus) is considered to be one of the essential tuberous legume crops holding a great potential source of starch. Yam Bean Mosaic Virus (YBMV) of Potyvirus group belonging to the family potyviridae affects Yam bean and several angiosperms both in the tropical and sub-tropical regions causing large economical losses in crops. In this study, we attempted to understand the sequence-structure relationship and mode of RNA binding mechanism in YBMV CP using in silico integrative modeling and all-atoms molecular dynamics (MD) simulations. The assembly of coat protein (CP) subunits from YBMV and the plausible mode of RNA binding were compared with the experimental structure of CP from Watermelon mosaic virus potyvirus (5ODV). The transmembrane helix region is present in the YBMV CP sequence ranging from 76 to 91 amino acids. Like the close structural-homolog, 24 CPs monomeric sub-units formed YBMV a conserved fold. Our computational study showed that ARG124, ARG155, and TYR151 orient towards the inner side of the virion, while, THR122, GLN125, SER92, ASP94 reside towards the outer side of the virion. Despite sharing very low sequence similarity with CPs from other plant viruses, the strongly conserved residues Ser, Arg, and Asp within the RNA binding pocket of YBMV CP indicate the presence of a highly conserved RNA binding site in CPs from different families. Using several bioinformatics tools and comprehensive analysis from MD simulation, our study has provided novel insights into the RNA binding mechanism in YBMV CP. Thus, we anticipate that our findings from this study will be useful for the development of new therapeutic agents against the pathogen, paving the way for researchers to better control this destructive plant virus.

Integrated Transcriptome Profiling Identifies Prognostic Hub Genes as Therapeutic Targets of Glioblastoma: Evidenced by Bioinformatics Analysis

Glioblastoma (GBM) is the most devastating and frequent type of primary brain tumor with high morbidity and mortality. Despite the use of surgical resection followed by radio- and chemotherapy as standard therapy, the progression of GBM remains dismal with a median overall survival of <15 months. GBM embodies a populace of cancer stem cells (GSCs) that is associated with tumor initiation, invasion, therapeutic resistance, and post-treatment reoccurrence. However, understanding the potential mechanisms of stemness and their candidate biomarkers remains limited. Hence in this investigation, we aimed to illuminate potential candidate hub genes and key pathways associated with the pathogenesis of GSC in the development of GBM. The integrated analysis discovered differentially expressed genes (DEGs) between the brain cancer tissues (GBM and GSC) and normal brain tissues. Multiple approaches, including gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were employed to functionally annotate the DEGs and visualize them through the R program. The significant hub genes were identified through the protein-protein interaction network, Venn diagram analysis, and survival analysis. We observed that the upregulated DEGs were prominently involved in the ECM-receptor interaction pathway. The downregulated genes were mainly associated with the axon guidance pathway. Five significant hub genes (CTNNB1, ITGB1, TNC, EGFR, and SHOX2) were screened out through multiple analyses. GO and KEGG analyses of hub genes uncovered that these genes were primarily enriched in disease-associated pathways such as the inhibition of apoptosis and the DNA damage repair mechanism, activation of the cell cycle, EMT (epithelial-mesenchymal transition), hormone AR (androgen receptor), hormone ER (estrogen receptor), PI3K/AKT (phosphatidylinositol 3-kinase and AKT), RTK (receptor tyrosine kinase), and TSC/mTOR (tuberous sclerosis complex and mammalian target of rapamycin). Consequently, the epigenetic regulatory network disclosed that hub genes played a vital role in the progression of GBM. Finally, candidate drugs were predicted that can be used as possible drugs to treat GBM patients. Overall, our investigation offered five hub genes (CTNNB1, ITGB1, TNC, EGFR, and SHOX2) that could be used as precise diagnostic and prognostic candidate biomarkers of GBM and might be used as personalized therapeutic targets to obstruct gliomagenesis.