Transcriptional Profiling of SARS-CoV-2-Infected Calu-3 Cells Reveals Immune-Related Signaling Pathways.

The COVID-19 disease, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), emerged in late 2019 and rapidly spread worldwide, becoming a pandemic that infected millions of people and caused significant deaths. COVID-19 continues to be a major threat, and there is a need to deepen our understanding of the virus and its mechanisms of infection. To study the cellular responses to SARS-CoV-2 infection, we performed an RNA sequencing of infected vs. uninfected Calu-3 cells. Total RNA was extracted from infected (0.5 MOI) and control Calu-3 cells and converted to cDNA. Sequencing was performed, and the obtained reads were quality-analyzed and pre-processed. Differential expression was assessed with the EdgeR package, and functional enrichment was performed in EnrichR for Gene Ontology, KEGG pathways, and WikiPathways. A total of 1040 differentially expressed genes were found in infected vs. uninfected Calu-3 cells, of which 695 were up-regulated and 345 were down-regulated. Functional enrichment analyses revealed the predominant up-regulation of genes related to innate immune response, response to virus, inflammation, cell proliferation, and apoptosis. These transcriptional changes following SARS-CoV-2 infection may reflect a cellular response to the infection and help to elucidate COVID-19 pathogenesis, in addition to revealing potential biomarkers and drug targets.

Mechanism of molecular interaction of sitagliptin with human DPP4 enzyme - New Insights.

PURPOSE: Dipeptidyl peptidase 4 (DPP4) inactivates a range of bioactive peptides. The cleavage of insulinotropic peptides and glucagon-like peptide 1 (GLP1) by DPP4 directly influences glucose homeostasis. This study aimed to describe the mode of interaction between sitagliptin (an antidiabetic drug) and human DPP4 using in silico approaches. MATERIALS AND METHODS: Docking studies were conducted using AutoDock Vina, 2D and 3D schematic drawings were obtained using PoseView and PLIP servers, and the DPP4-sitagliptin complex was visualized with Pymol software. RESULTS: The best affinity energy to form the DPP4-sitagliptin complex was E-value â€‹= â€‹- 8.1 â€‹kcal â€‹mol-1, as indicated by docking simulations. This result suggests a strong interaction. According to our observations, hydrophobic interactions involving the amino acids residues Tyr663 and Val712, hydrogen bonds (Glu203, Glu204, Tyr663, and Tyr667), π-Stacking interactions (Phe355 and Tyr667), and halogenic bonds (Arg123, Glu204, and Arg356) were prevalent in the DPP4-sitagliptin complex. Root Mean Square Deviation prediction also demonstrated that the global structure of the human DPP4 did not have a significant change in its topology, even after the formation of the DPP4-sitagliptin complex. CONCLUSION: The stable interaction between the sitagliptin ligand and the DPP4 enzyme was demonstrated through molecular docking simulations. The findings presented in this work enhance the understanding of the physicochemical properties of the sitagliptin interaction site, supporting the design of more efficient gliptin-like iDPP4 inhibitors.

Evaluation of the anti-diabetic drug sitagliptin as a novel attenuate to SARS-CoV-2 evidence-based in silico: molecular docking and molecular dynamics.

The current outbreak of COVID-19 cases worldwide has been responsible for a significant number of deaths, especially in hospitalized patients suffering from comorbidities, such as obesity, diabetes, hypertension. The disease not only has prompted an interest in the pathophysiology, but also it has propelled a massive race to find new anti-SARS-CoV-2 drugs. In this scenario, known drugs commonly used to treat other diseases have been suggested as alternative or complementary therapeutics. Herein we propose the use of sitagliptin, an inhibitor of dipeptidyl peptidase-4 (DPP4) used to treat type-II diabetes, as an agent to block and inhibit the activity of two proteases, 3CLpro and PLpro, related to the processing of SARS-CoV-2 structural proteins. Inhibition of these proteases may possibly reduce the viral load and infection on the host by hampering the synthesis of new viruses, thus promoting a better outcome. In silico assays consisting in the modeling of the ligand sitagliptin and evaluation of its capacity to interact with 3CLpro and PLpro through the prediction of the ligand bioactivity, molecular docking, overlapping of crystal structures, and molecular dynamic simulations were conducted. The experiments indicate that sitagliptin can interact and bind to both targets. However, this interaction seems to be stronger and more stable to 3CLpro (ΔG = -7.8 kcal mol-1), when compared to PLpro (ΔG = -7.5 kcal mol-1). This study suggests that sitagliptin may be suitable to treat COVID-19 patients, beyond its common use as an anti-diabetic medication. In vivo studies may further support this hypothesis. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03406-w.