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Molecular docking and dynamic simulation of approved drugs targeting against spike protein (6VXX) of 2019-nCoV (novel coronavirus)

ABSTRACT: The 2019-nCoV has triggered a global public health emergency due to its rapid spread, resulting in a pandemic situation. Because of its ability to bind with the host cell receptor ACE-2, the spike protein of the 2019-nCoV is a critical factor in viral infection. The current study aims to investigate the molecular-docking of the spike protein (6VXX) using PyRx for FDA-approved drugs available for the treatment of SARS-1 and MERS, with the hypothesis that these drugs could be suggested for the treatment of 2019-nCoV or not. A phylogenetic analysis of 2019-nCoV in relation to SARS-1 and MERS confirmed the validation. The positive result urged the Multiple Sequence Alignment analysis of the top five affected countries, with China serving as a control, using WHO available reference data to determine the rate of mutant variation. The docking results revealed that the top ten drugs with the highest binding affinity rate are also used for Hepatitis-C virus treatment, and the Molecular Dynamic Simulation was carried out for the drug Paritaprevir, which had the highest binding affinity rate, using Gromacs. The results indicated that the drug Paritaprevir could be used as a potential target against the 2019-nCoV Spike protein. Graphical abstract Image 1

SUBMITTER: Thakur A

PROVIDER: S-EPMC9197568 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundMedicines for the treatment of 2019-novel coronavirus (2019-nCoV) infections are urgently needed. However, drug screening using live 2019-nCoV requires high-level biosafety facilities, which imposes an obstacle for those institutions without such facilities or 2019-nCoV. This study aims to repurpose the clinically approved drugs for the treatment of coronavirus disease 2019 (COVID-19) in a 2019-nCoV-related coronavirus model.MethodsA 2019-nCoV-related pangolin coronavirus GX_P2V/pangolin/2017/Guangxi was described. Whether GX_P2V uses angiotensin-converting enzyme 2 (ACE2) as the cell receptor was investigated by using small interfering RNA (siRNA)-mediated silencing of ACE2. The pangolin coronavirus model was used to identify drug candidates for treating 2019-nCoV infection. Two libraries of 2406 clinically approved drugs were screened for their ability to inhibit cytopathic effects on Vero E6 cells by GX_P2V infection. The anti-viral activities and anti-viral mechanisms of potential drugs were further investigated. Viral yields of RNAs and infectious particles were quantified by quantitative real-time polymerase chain reaction (qRT-PCR) and plaque assay, respectively.ResultsThe spike protein of coronavirus GX_P2V shares 92.2% amino acid identity with that of 2019-nCoV isolate Wuhan-hu-1, and uses ACE2 as the receptor for infection just like 2019-nCoV. Three drugs, including cepharanthine (CEP), selamectin, and mefloquine hydrochloride, exhibited complete inhibition of cytopathic effects in cell culture at 10 μmol/L. CEP demonstrated the most potent inhibition of GX_P2V infection, with a concentration for 50% of maximal effect [EC50] of 0.98 μmol/L. The viral RNA yield in cells treated with 10 μmol/L CEP was 15,393-fold lower than in cells without CEP treatment ([6.48 ± 0.02] × 10vs. 1.00 ± 0.12, t = 150.38, P < 0.001) at 72 h post-infection (p.i.). Plaque assays found no production of live viruses in media containing 10 μmol/L CEP at 48 h p.i. Furthermore, we found CEP had potent anti-viral activities against both viral entry (0.46 ± 0.12, vs.1.00 ± 0.37, t = 2.42, P < 0.05) and viral replication ([6.18 ± 0.95] × 10vs. 1.00 ± 0.43, t = 3.98, P < 0.05).ConclusionsOur pangolin coronavirus GX_P2V is a workable model for 2019-nCoV research. CEP, selamectin, and mefloquine hydrochloride are potential drugs for treating 2019-nCoV infection. Our results strongly suggest that CEP is a wide-spectrum inhibitor of pan-betacoronavirus, and further study of CEP for treatment of 2019-nCoV infection is warranted.

Project description:Acute myeloid leukemia (AML) is a blood cancer caused by the abnormal proliferation and differentiation of hematopoietic stem cells in the bone marrow. The actual genetic markers and molecular mechanisms of AML prognosis are unclear till today. This study used bioinformatics approaches for identifying hub genes and pathways associated with AML development to uncover potential molecular mechanisms. The expression profiles of RNA-Seq datasets, GSE68925 and GSE183817, were retrieved from the Gene Expression Omnibus (GEO) database. These two datasets were analyzed by GREIN to obtain differentially expressed genes (DEGs), which were used for performing the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI), and survival analysis. The molecular docking and dynamic simulation were performed to identify the most effective drug/s for AML from the drug list approved by the Food and Drug Administration (FDA). By integrating the two datasets, 238 DEGs were identified as likely to be affected by AML progression. GO enrichment analyses exhibited that the upregulated genes were mainly associated with inflammatory response (BP) and extracellular region (CC). The downregulated DEGs were involved in the T-cell receptor signalling pathway (BP), an integral component of the lumenal side of the endoplasmic reticulum membrane (CC) and peptide antigen binding (MF). The pathway enrichment analysis showed that the upregulated DEGs were mainly associated with the T-cell receptor signalling pathway. Among the top 15 hub genes, the expression levels of ALDH1A1 and CFD were associated with the prognosis of AML. Four FDA-approved drugs were selected, and a top-ranked drug was identified for each biomarker through molecular docking studies. The top-ranked drugs were further confirmed by molecular dynamic simulation that revealed their binding stability and confirmed their stable performance. Therefore, the drug compounds, enasidenib and gilteritinib, can be recommended as the most effective drugs against the ALDH1A1 and CFD proteins, respectively.

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Molecular docking and dynamic simulation of approved drugs targeting against spike protein (6VXX) of 2019-nCoV (novel coronavirus)

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