Pharmacogenomic considerations for repurposing of dexamethasone as a potential drug against SARS-CoV-2 infection.
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ABSTRACT:
SUBMITTER: Vohra M
PROVIDER: S-EPMC8186476 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A critical step to evaluate the potential in vivo antiviral activity of a drug is to connect the in vivo exposure to its in vitro antiviral activity. The Anti-SARS-CoV-2 Repurposing Drug Database is a database that includes both in vitro anti-SARS-CoV-2 activity and in vivo pharmacokinetic data to facilitate the extrapolation from in vitro antiviral activity to potential in vivo antiviral activity for a large set of drugs/compounds. In addition to serving as a data source for in vitro anti-SARS-CoV-2 activity and in vivo pharmacokinetic information, the database is also a calculation tool that can be used to compare the in vitro antiviral activity with in vivo drug exposure to identify potential anti-SARS-CoV-2 drugs. Continuous development and expansion are feasible with the public availability of this database.
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Project description:Since the beginning of the COVID-19 pandemic, large in silico screening studies and numerous in vitro studies have assessed the antiviral activity of various drugs on SARS-CoV-2. In the context of health emergency, drug repurposing represents the most relevant strategy because of the reduced time for approval by international medicines agencies, the low cost of development and the well-known toxicity profile of such drugs. Herein, we aim to review drugs with in vitro antiviral activity against SARS-CoV-2, combined with molecular docking data and results from preliminary clinical studies. Finally, when considering all these previous findings, as well as the possibility of oral administration, 11 molecules consisting of nelfinavir, favipiravir, azithromycin, clofoctol, clofazimine, ivermectin, nitazoxanide, amodiaquine, heparin, chloroquine and hydroxychloroquine, show an interesting antiviral activity that could be exploited as possible drug candidates for COVID-19 treatment.
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Project description:A novel severe acute respiratory syndrome human coronavirus (SARS HCoV) was identified from respiratory illness patients (named SARS-CoV-2 by ICTV) in December 2019 and has recently emerged as a serious threat to world public health. However, no approved drugs have been found to effectively inhibit the virus. Since it has been reported that HIV protease inhibitors can be used as anti-SARS drugs by targeting SARS-CoV-1 3CLpro, we chose six approved anti-HIV drugs and investigated their binding interactions with 3CLpro to evaluate their potential to become clinical drugs for the new coronavirus pneumonia (COVID-19) caused by SARS-CoV-2 infection. The molecular docking results indicate that the 3CLpro of SARS-CoV-2 has a higher binding affinity for all the studied inhibitors than does SARS-CoV-1. Two docking complexes (indinavir and darunavir) with high docking scores were further subjected to MM-PBSA binding free energy calculations to detail the molecular interactions between these two protease inhibitors and SARS HCoV 3CLpro. Our results show that, among the inhibitors tested, darunavir has the highest binding affinity with SARS-CoV-2 and SARS-CoV-1 3CLpro, indicating that it may have the potential to be used as an anti-COVID-19 clinical drug. The mechanism behind the increased binding affinity of HIV protease inhibitors toward SARS-CoV-2 3CLpro (as compared to SARS-CoV-1) was investigated by MD simulations. Our study provides insight into the possible role of structural flexibility during interactions between SARS HCoV 3CLpro and inhibitors and sheds light on structure-based design of anti-COVID-19 drugs targeting SARS-CoV-2 3CLpro.
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Project description:Since December 2019, SARS-CoV-2 (COVID-19) has been a worldwide pandemic with enormous consequences for human health and the world economy. Remdesivir is the only drug in the world that has been approved for the treating of COVID-19. This drug, as well as vaccination, still has uncertain effectiveness. Drug repurposing could be a promising strategy how to find an appropriate molecule: rapamycin could be one of them. The authors performed a systematic literature review of available studies on the research describing rapamycin in association with COVID-19 infection. Only peer-reviewed English-written articles from the world's acknowledged databases Web of Science, PubMed, Springer and Scopus were involved. Five articles were eventually included in the final analysis. The findings indicate that rapamycin seems to be a suitable candidate for drug repurposing. In addition, it may represent a better candidate for COVID-19 therapy than commonly tested antivirals. It is also likely that its efficiency will not be reduced by the high rate of viral RNA mutation.
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Project description:The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has generated a critical need for treatments to reduce morbidity and mortality associated with this disease. However, traditional drug development takes many years, which is not practical solution given the current pandemic. Therefore, a viable option is to repurpose existing drugs. The structural data of several proteins vital for the virus became available shortly after the start of the pandemic. In this review, we discuss the importance of these targets and their available potential inhibitors predicted by the computational approaches. Among the hits identified by computational approaches, 35 candidates were suggested for further evaluation, among which ten drugs are in clinical trials (Phase III and IV) for treating Coronavirus 2019 (COVID-19).
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Project description:Background: In the current SARS-CoV-2 outbreak, drug repositioning emerges as a promising approach to develop efficient therapeutics in comparison to de novo drug development. The present investigation screened 130 US FDA-approved drugs including hypertension, cardiovascular diseases, respiratory tract infections (RTI), antibiotics and antiviral drugs for their inhibitory potential against SARS-CoV-2. Materials & methods: The molecular drug targets against SARS-CoV-2 proteins were determined by the iGEMDOCK computational docking tool. The protein homology models were generated through SWISS Model workspace. The pharmacokinetics of all the ligands was determined by ADMET analysis. Results: The study identified 15 potent drugs exhibiting significant inhibitory potential against SARS-CoV-2. Conclusion: Our investigation has identified possible repurposed drug candidates to improve the current modus operandi of the treatment given to COVID-19 patients.
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Project description:This article highlights recent pioneering work by Günther et al. towards the discovery of potential repurposed antiviral compounds (peptidomimetic and non-peptidic) against the SARS-CoV-2 main protease (Mpro ). The antiviral activity of the most potent drugs is discussed along with their binding mode to Mpro as observed through X-ray crystallographic screening.
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Project description:The health sector has been on the race to find a potent therapy for coronavirus disease (COVID)-19, a diseases caused by severe acute respiratory syndrome coronavirus (SARS-CoV)-2. Repurposed anti-viral drugs have played a huge role in combating the virus, and most recently, dexamethasone (Dex) have shown its therapeutic activity in severe cases of COVID-19 patients. The study sought to provide insights on the anti-COVID-19 mechanism of Dex at both atomic and molecular level against SARS-CoV-2 targets. Computational methods were employed to predict the binding affinity of Dex to SARS-CoV-2 using the Schrodinger suite (v2020-2). The target molecules and ligand (Dex) were retrieved from PDB and PubChem, respectively. The selected targets were SARS-CoV-2 main protease (Mpro), and host secreted molecules glucocorticoid receptor, and Interleukin-6 (IL-6). Critical analyses such as Protein and ligand preparation, molecular docking, molecular dynamic (MD) simulations, and absorption, distribution, metabolism, excretion (ADME), and toxicity analyses were performed using the targets and the ligand as inputs. Dex showed stronger affinity to its theoretical (glucocorticoid) receptor with a superior docking score of -14.7 and a good binding energy value of -147.48 kcal/mol; while short hydrogen bond distances were observed in both Mpro and IL-6 when compared to glucocorticoid receptor. Based on these findings, Dex-target complexes were used to perform MD simulations to analyze Dex stability at 50 ns. This study demonstrates that Dex could bind to both the viral and host receptors as a potential drug candidate for COVID-19. To ascertain the biological fitness of this study, other SARS-CoV-2 targets should be explored. Also, the in vitro studies of dexamethasone against several SARS-CoV-2 targets warrant further investigation.Communicated by Ramaswamy H. Sarma.
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Project description:Drug repurposing is an important approach to the assignment of already approved drugs for new indications. This technique bypasses some steps in the traditional drug approval system, which saves time and lives in the case of pandemics. Direct acting antivirals (DAAs) have repeatedly repurposed from treating one virus to another. In this study, 16 FDA-approved hepatitis C virus (HCV) DAA drugs were studied to explore their activities against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) human and viral targets. Among the 16 HCV DAA drugs, telaprevir has shown the best in silico evidence to work on both indirect human targets (cathepsin L [CTSL] and human angiotensin-converting enzyme 2 [hACE2] receptor) and direct viral targets (main protease [Mpro]). Moreover, the docked poses of telaprevir inside both hACE2 and Mpro were subjected to additional molecular dynamics simulations monitored by calculating the binding free energy using MM-GBSA. In vitro analysis of telaprevir showed inhibition of SARS-CoV-2 replication in cell culture (IC50 = 11.552 μM, CC50 = 60.865 μM, and selectivity index = 5.27). Accordingly, based on the in silico studies and supported by the presented in vitro analysis, we suggest that telaprevir may be considered for therapeutic development against SARS-CoV-2.
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Project description:The COVID-19 pandemic has accelerated the need to identify new antiviral therapeutics at pace, including through drug repurposing. We employed a Quadratic Unbounded Binary Optimization (QUBO) model, to search for compounds similar to Remdesivir, the first antiviral against SARS-CoV-2 approved for human use, using a quantum-inspired device. We modelled Remdesivir and compounds present in the DrugBank database as graphs, established the optimal parameters in our algorithm and resolved the Maximum Weighted Independent Set problem within the conflict graph generated. We also employed a traditional Tanimoto fingerprint model. The two methods yielded different lists of lead compounds, with some overlap. While GS-6620 was the top compound predicted by both models, the QUBO model predicted BMS-986094 as second best. The Tanimoto model predicted different forms of cobalamin, also known as vitamin B12. We then determined the half maximal inhibitory concentration (IC50) values in cell culture models of SARS-CoV-2 infection and assessed cytotoxicity. We also demonstrated efficacy against several variants including SARS-CoV-2 Strain England 2 (England 02/2020/407073), B.1.1.7 (Alpha), B.1.351 (Beta) and B.1.617.2 (Delta). Lastly, we employed an in vitro polymerization assay to demonstrate that these compounds directly inhibit the RNA-dependent RNA polymerase (RdRP) of SARS-CoV-2. Together, our data reveal that our QUBO model performs accurate comparisons (BMS-986094) that differed from those predicted by Tanimoto (different forms of vitamin B12); all compounds inhibited replication of SARS-CoV-2 via direct action on RdRP, with both models being useful. While Tanimoto may be employed when performing relatively small comparisons, QUBO is also accurate and may be well suited for very complex problems where computational resources may limit the number and/or complexity of possible combinations to evaluate. Our quantum-inspired screening method can therefore be employed in future searches for novel pharmacologic inhibitors, thus providing an approach for accelerating drug deployment.
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