Dataset Information

Rilpivirine inhibits SARS-CoV-2 protein targets: A potential multi-target drug.

ABSTRACT:

Background

COVID-19 disease caused by SARS-CoV-2 is lacking efficient medication although certain medications are used to relief its symptoms.

Objectives

We tested an FDA-approved antiviral medication namely rilpivirine to find a drug against SARS-CoV-2.

Methods

The inhibition of rilpivirine against multiple SARS-CoV-2 therapeutic targets was studied using in silico method. The binding attraction of the protein-ligand complexes were calculated using molecular docking analysis.

Results

Docking rilpivirine with main protease (Mpro), papin like protease (PLpro), sprike protein (Spro), human angiotensin converting enzyme-2 (ACE2), and RNA dependent-RNA polymerase (RdRp) yielded binding energies of -8.07, -8.40, -7.55, -9.11, and -8.69 kcal/mol, respectively. The electrostatic interaction is the key force in stabilizing the RdRp-rilpivirine complex, while van der Waals interaction dominates in the ACE2 rilpivirine case. Our findings suggest that rilpivirine can inhibit SARS-CoV-2 replication by targeting not only ACE2, but also RdRp and other targets, and therefore, it can be used to invoke altered mechanisms at the pre-entry and post-entry phases.

Conclusion

As a result of our in silico molecular docking study, we suggest that rilpivirine is a compound that could act as a powerful inhibitor against SARS-CoV-2 targets. Although in vitro and in vivo experiments are needed to verify this prediction we believe that this antiviral drug may be used in preclinical trials to fight against SARS coronavirus.

SUBMITTER: Ameen F

PROVIDER: S-EPMC8294774 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe ongoing COVID-19 outbreak has caused devastating mortality and posed a significant threat to public health worldwide. Despite the severity of this illness and 2.3 million worldwide deaths, the disease mechanism is mostly unknown. Previous studies that characterized differential gene expression due to SARS-CoV-2 infection lacked robust validation. Although vaccines are now available, effective treatment options are still out of reach.ResultsTo characterize the transcriptional activity of SARS-CoV-2 infection, a gene signature consisting of 25 genes was generated using a publicly available RNA-Sequencing (RNA-Seq) dataset of cultured cells infected with SARS-CoV-2. The signature estimated infection level accurately in bronchoalveolar lavage fluid (BALF) cells and peripheral blood mononuclear cells (PBMCs) from healthy and infected patients (mean 0.001 vs. 0.958; P < 0.0001). These signature genes were investigated in their ability to distinguish the severity of SARS-CoV-2 infection in a single-cell RNA-Sequencing dataset. TNFAIP3, PPP1R15A, NFKBIA, and IFIT2 had shown bimodal gene expression in various immune cells from severely infected patients compared to healthy or moderate infection cases. Finally, this signature was assessed using the publicly available ConnectivityMap database to identify potential disease mechanisms and drug repurposing candidates. Pharmacological classes of tricyclic antidepressants, SRC-inhibitors, HDAC inhibitors, MEK inhibitors, and drugs such as atorvastatin, ibuprofen, and ketoconazole showed strong negative associations (connectivity score < - 90), highlighting the need for further evaluation of these candidates for their efficacy in treating SARS-CoV-2 infection.ConclusionsThus, using the 25-gene SARS-CoV-2 infection signature, the SARS-CoV-2 infection status was captured in BALF cells, PBMCs and postmortem lung biopsies. In addition, candidate SARS-CoV-2 therapies with known safety profiles were identified. The signature genes could potentially also be used to characterize the COVID-19 disease severity in patients' expression profiles of BALF cells.