The severe acute respiratory syndrome coronavirus 2, also known as SARS-CoV-2, is the causative agent of the COVID-19 global pandemic. SARS-CoV-2 has a highly conserved non-structural protein 12 (NSP-12) involved in RNA-dependent RNA polymerase (RdRp) activity. For the identification of potential inhibitors for NSP-12, computational approaches such as the identification of homologous proteins that have been previously targeted by FDA-approved antivirals can be employed. Herein, homologous proteins of NSP-12 were retrieved from Protein DataBank (PDB) and the evolutionary conserved sequence and structure similarity of the active site of the RdRp domain of NSP-12 was characterized. The identified homologous structures of NSP-12 belonged to four viral families: Coronaviridae, Flaviviridae, Picornaviridae, and Caliciviridae, and shared evolutionary conserved relationships. The multiple sequences and structural alignment of homologous structures showed highly conserved amino acid residues that were located at the active site of the RdRp domain of NSP-12. The conserved active site of the RdRp domain of NSP-12 was evaluated for binding affinity with the FDA-approved antivirals, i.e., Sofosbuvir and Dasabuvir in a molecular docking study. The molecular docking of Sofosbuvir and Dasabuvir with the active site that contains conserved motifs (motif A-G) of the RdRp domain of NSP-12 revealed significant binding affinity. Furthermore, MD simulation also inferred the potency of Sofosbuvir and Dasabuvir. In conclusion, targeting the active site of the RdRp domain of NSP-12 with Dasabuvir and Sofosbuvir might reduce viral replication and pathogenicity and could be further studied for the treatment of SARS-CoV-2.
This study aims to investigate the distribution of microbial taxa that are present in abundance in the oral cavity of patients diagnosed with Oral Squamous Cell Carcinoma (OSCC). We begin with a search for relevant literature on the OSCC microbiome in electronic databases (PubMed and Google Scholar). From the identified literature, studies were considered for data extraction based on an inclusion criteria according to PRISMA guidelines. From an initial 1217 published studies, a total of 15 relevant studies were identified that fulfilled the inclusion criteria. These studies were conducted for the detection of microbial taxa in the oral cavities of patients with OSCC by correlation with healthy controls for differential microbial abundance. The data from the selected studies provided evidence on microbial taxa in different anatomical sites of the oral cavity i.e. gingival region, tongue, buccal site and floor of the mouth. The most common method for the detection of microbial flora in the literature was 16s rRNA sequencing. Only those studies from the literature were considered for further analysis that showed the association of risk factors i.e. tobacco smoking and smokeless, betel quid, alcohol and periodontitis with OSCC. Risk factors in the resulting 6 studies showed a strong odds ratio (OR) with statistical significance (p-value <0.05). The calculated risk ratio (RR) of these risk factors also demonstrated substantial heterogeneity. These studies showed an increase in the abundance of periodontopathogens belonging to the genus Fusobacterium, Capnocytophaga, Prevotella, Parvimonas and Porphyromonas. The microbial taxa associated in abundance with risk factors of OSCC such as smoked or smokeless tobacco, betel quid and alcohol were quite similar to the microbial taxa that cause periodontitis. The detection for abundance of periodontopathogens in OSCC a class of putative biomarkers at early stages of tumor development in OSCC, in individuals exposed to these risk factors.
Oral squamous cell carcinoma (OSCC) is the most common malignant epithelial neoplasm and anatomical subtype of head and neck squamous cell carcinoma (HNSCC) with an average 5-year survival rate of less than 50%. To improve the survival rate of OSCC, the discovery of novel anti-cancer drugs is urgently needed. In the present study, we performed metanalysis of 5 gene expression datasets (GSE23558, GSE25099, GSE30784, GSE37991 and TCGA-OSCC) that resulted in 1851 statistically significant DEGs in OSCC. The DEGs were involved in key biological pathways that drive the progression of OSCC. A comprehensive protein-protein interaction (PPI) network was constructed from the DEGs and the top protein clusters (modules) were extracted in Cytoscape. The DEGs from the top modules were searched for antineoplastic agents using L1000CDS2 server. The search resulted in a total of 37 perturbing agents from which 12 well-characterized antineoplastic agents were selected. The selected 12 antineoplastic agents namely Teniposide, Palbociclib, Etoposide, Fedratinib, Tivozanib, Afatinib, Vemurafenib, Mitoxantrone, Idamycin, Canertinib, Dovitinib and Selumetinib. These drugs showed interactions with the over expressed hub genes that regulate cellular proliferation and growth in OSCC progression. These identified antineoplastic agents are candidates for their potential role in treating OSCC.
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