Molecular modeling and simulation approaches to characterize potential molecular targets for burdock inulin to instigate protection against autoimmune diseases.

In the current study, we utilized molecular modeling and simulation approaches to define putative potential molecular targets for Burdock Inulin, including inflammatory proteins such as iNOS, COX-2, TNF-alpha, IL-6, and IL-1ß. Molecular docking results revealed potential interactions and good binding affinity for these targets; however, IL-1ß, COX-2, and iNOS were identified as the best targets for Inulin. Molecular simulation-based stability assessment demonstrated that inulin could primarily target iNOS and may also supplementarily target COX-2 and IL-1ß during DSS-induced colitis to reduce the role of these inflammatory mechanisms. Furthermore, residual flexibility, hydrogen bonding, and structural packing were reported with uniform trajectories, showing no significant perturbation throughout the simulation. The protein motions within the simulation trajectories were clustered using principal component analysis (PCA). The IL-1ß-Inulin complex, approximately 70% of the total motion was attributed to the first three eigenvectors, while the remaining motion was contributed by the remaining eigenvectors. In contrast, for the COX2-Inulin complex, 75% of the total motion was attributed to the eigenvectors. Furthermore, in the iNOS-Inulin complex, the first three eigenvectors contributed to 60% of the total motion. Furthermore, the iNOS-Inulin complex contributed 60% to the total motion through the first three eigenvectors. To explore thermodynamically favorable changes upon mutation, motion mode analysis was carried out. The Free Energy Landscape (FEL) results demonstrated that the IL-1ß-Inulin achieved a single conformation with the lowest energy, while COX2-Inulin and iNOS-Inulin exhibited two lowest-energy conformations each. IL-1ß-Inulin and COX2-Inulin displayed total binding free energies of - 27.76 kcal/mol and - 37.78 kcal/mol, respectively, while iNOS-Inulin demonstrated the best binding free energy results at - 45.89 kcal/mol. This indicates a stronger pharmacological potential of iNOS than the other two complexes. Thus, further experiments are needed to use inulin to target iNOS and reduce DSS-induced colitis and other autoimmune diseases.

Development of multi-epitope subunit vaccine for protection against the norovirus' infections based on computational vaccinology.

Human Norovirus belongs to a family Calciviridae, and was identified in the outbreak of gastroenteritis in Norwalk, due to its seasonal prevalence known as "winter vomiting disease." Treatment of Norovirus infection is still mysterious because there is no effective antiviral drugs or vaccine developed to protect against the infection, to eradicate the infection an effective vaccine should be developed. In this study, capsid protein (A7YK10), small protein (A7YK11), and polyprotein (A7YK09) were utilized. These proteins were subjected to B and T cell epitopes prediction by using reliable immunoinformatics tools. The antigenic and non-allergenic epitopes were selected for the subunit vaccine, which can activate cellular and humoral immune responses. Linkers joined these epitopes together. The vaccine structure was modelled and validated by using Errat, ProSA, and rampage servers. The modelled vaccine was docked with TLR-7. The stability of the docked complex was evaluated by MD simulation. To apply the concept in a wet lab, the reverse translated vaccine sequence was cloned in pET28a (+). The vaccine developed in this study requires experimental validation to ensure its effectiveness against the disease.Communicated by Ramaswamy H. Sarma.

Drug similarity and structure-based screening of medicinal compounds to target macrodomain-I from SARS-CoV-2 to rescue the host immune system: a molecular dynamics study.

The outbreak of the recent coronavirus (SARS-CoV-2), which causes a severe pneumonia infection, first identified in Wuhan, China, imposes significant risks to public health. Around the world, researchers are continuously trying to identify small molecule inhibitors or vaccine candidates by targeting different drug targets. The SARs-CoV-2 macrodomain-I, which helps in viral replication and hijacking the host immune system, is also a potential drug target. Hence, this study targeted viral macrodomain-I by using drug similarity, virtual screening, docking and re-docking approaches. A total of 64,043 compounds were screened, and potential hits were identified based on the docking score and interactions with the key residues. The top six hits were subjected to molecular dynamics simulation and Free energy calculations and repeated three times each. The per-residue energy decomposition analysis reported that these compounds significantly interact with Asp22, Ala38, Asn40, Val44, Phe144, Gly46, Gly47, Leu127, Ser128, Gly130, Ile131, Phe132 and Ala155 which are the critical active site residues. Here, we also used ADPr as a positive control to compare our results. Our results suggest that our identified hits by using such a complicated computational pipeline could inhibit the SARs-CoV-2 by targeting the macrodomain-1. We strongly recommend the experimental testing of these compounds, which could rescue the host immune system and could help to contain the disease caused by SARs-CoV-2.Communicated by Ramaswamy H. Sarma.

Structural and Biophysical Investigation of the Key Hotspots on the Surface of Epstein-Barr Nuclear Antigen 1 Essential for DNA Recognition and Pathogenesis.

Epstein-Barr Virus (EBV) is considered the most important human pathogen due to its role in infections and cellular malignancies. It has been reported that this Oncolytic virus infects 90% world's population. EBNA1 is required for DNA binding and survival of the virus and is considered an essential drug target. The biochemical and structural properties of this protein are known, but it is still unclear which residues impart a critical role in the recognition of dsDNA. Intending to disclose only the essential residues in recognition of dsDNA, this study used a computational pipeline to generate an alanine mutant of each interacting residue and determine the impact on the binding. Our analysis revealed that R469A, K514A, Y518A, R521A and R522A are the key hotspots for the recognition of dsDNA by the EBNA1. The dynamics properties, i.e. stability, flexibility, structural compactness, hydrogen bonding frequency, binding affinity, are altered by disrupting the protein-DNA contacts, thereby decreases the binding affinity. In particular, the two arginine substitution, R521A and R522A, significantly affected the total binding energy. Thus, we hypothesize that these residues impart a critical role in the dsDNA recognition and pathogenesis. This study would help to design structure-based drugs against the EBV infections.

An Integrated Systems Biology and Network-Based Approaches to Identify Novel Biomarkers in Breast Cancer Cell Lines Using Gene Expression Data.

Breast cancer is the most common cause of death in women worldwide. Approximately 5%-10% of instances are attributed to mutations acquired from the parents. Therefore, it is highly recommended to design more potential drugs and drug targets to eradicate such complex diseases. Network-based gene expression profiling is a suggested tool for discovering drug targets by incorporating various factors such as disease states, intensities based on gene expression as well as protein-protein interactions. To find prospective biomarkers in breast cancer, we first identified differentially expressed genes (DEGs) statistical methods p-value and false discovery rate were initially used. Of the total 82 DEGs, 67 were upregulated while the remaining 17 were downregulated. Sub-modules and hub genes include VEGFA with the highest degree, followed by 15 CCND1 and CXCL8 with 12-degree score was found. The survival analysis revealed that all the hub genes have important role in the development and progression of breast cancer. Enrichment analysis revealed that most of these genes are involved in signaling pathways and in the extracellular spaces. We also identified transcription factors and kinases, which regulate proteins in the DEGs PPI. Finally, drugs for each hub genes were identified. These results further expanded the knowledge regarding important biomarkers in breast cancer.