Dataset Information

The potential effects of clinical antidiabetic agents on SARS-CoV-2.

ABSTRACT:

Background

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is currently posing significant threats to public health worldwide. It is notable that a substantial proportion of patients with sever COVID-19 have coexisting diabetic conditions, indicating the progression and outcome of COVID-19 may relate to diabetes. However, it is still unclear whether diabetic treatment principles can be used for the treatment of COVID-19.

Methods

We conducted a computational approach to screen all commonly used clinical oral hypoglycemic drugs to identify the potential inhibitors for the main protease (M^pro ) of SARS-CoV-2, which is one of the key drug targets for anti-COVID-19 drug discovery.

Results

Six antidiabetic drugs with docking scores higher than 8.0 (cutoff value), including repaglinide, canagliflozin, glipizide, gliquidone, glimepiride, and linagliptin, were predicted as the promising inhibitors of M^pro . Interestingly, repaglinide, one of the six antidiabetic drugs with the highest docking score for M^pro , was similar to a previously predicted active molecule nelfinavir, which is a potential anti-HIV and anti-COVID-19 drug. Moreover, we found repaglinide shared similar docking pose and pharmacophores with a reported ligand (N3 inhibitor) and nelfinavir, demonstrating that repaglinide would interact with M^pro in a similar way.

Conclusion

These results indicated that these six antidiabetic drugs may have an extra effect on the treatment of COVID-19, although further studies are necessary to confirm these findings.

SUBMITTER: Qu H

PROVIDER: S-EPMC7753367 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The potential effects of clinical antidiabetic agents on SARS-CoV-2.

Qu Hua H Zheng Yi Y Wang Yuren Y Li Hongwei H Liu Xiufei X Xiong Xin X Zhang Linlin L Gu Jing J Yang Gangyi G Zhu Zhiming Z Zheng Hongting H Ouyang Qin Q

Journal of diabetes 20201219 3

<h4>Background</h4>Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is currently posing significant threats to public health worldwide. It is notable that a substantial proportion of patients with sever COVID-19 have coexisting diabetic conditions, indicating the progression and outcome of COVID-19 may relate to diabetes. However, it is still unclear whether diabetic treatment principles can be used for the treatment of COVID-19.<h4>Met ...[more]

PMID: 33210826

Similar Datasets

Project description:BackgroundOsteoarthritis is a leading cause of disability, and disease-modifying osteoarthritis drugs (DMOADs) could represent a pivotal advancement in treatment. Identifying the potential of antidiabetic medications as DMOADs could impact patient care significantly.MethodsWe designed a comprehensive analysis pipeline involving two-sample Mendelian Randomization (MR) (genetic proxies for antidiabetic drug targets), summary-based MR (SMR) (for mRNA), and colocalisation (for drug-target genes) to assess their causal relationship with 12 osteoarthritis phenotypes. Summary statistics from the largest genome-wide association meta-analysis (GWAS) of osteoarthritis and gene expression data from the eQTLGen consortium were utilised.FindingsSeven out of eight major types of clinical antidiabetic medications were identified, resulting in fourteen potential drug targets. Sulfonylurea targets ABCC8/KCNJ11 were associated with increased osteoarthritis risk at any site (odds ratio (OR): 2.07, 95% confidence interval (CI): 1.50-2.84, P < 3 × 10-4), while PPARG, influenced by thiazolidinediones (TZDs), was associated with decreased risk of hand (OR: 0.61, 95% CI: 0.48-0.76, P < 3 × 10-4), finger (OR: 0.50, 95% CI: 0.35-0.73, P < 3 × 10-4), and thumb (OR: 0.49, 95% CI: 0.34-0.71, P < 3 × 10-4) osteoarthritis. Metformin and GLP1-RA, targeting GPD1 and GLP1R respectively, were associated with reduced risk of knee and finger osteoarthritis. In the SMR analyses, gene expression of KCNJ11, GANAB, ABCA1, and GSTP1, targeted by antidiabetic drugs, was significantly linked to at least one osteoarthritis phenotype and was replicated across at least two gene expression datasets. Additionally, increased KCNJ11 expression was related to decreased osteoarthritis risk and co-localised with at least one osteoarthritis phenotype.InterpretationOur findings suggest a potential therapeutic role for antidiabetic drugs in treating osteoarthritis. The results indicate that certain antidiabetic drug targets may modify disease progression, with implications for developing targeted DMOADs.FundingThis study was funded by the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant (2022), the Shanghai Municipal Health Commission Health Industry Clinical Research Project (Grant No. 20224Y0139), Beijing Natural Science Foundation (Grant No. 7244458), and the Postdoctoral Fellowship Program (Grade C) of China Postdoctoral Science Foundation (Grant No. GZC20230130).

Dataset Information

The potential effects of clinical antidiabetic agents on SARS-CoV-2.

Background

Methods

Results

Conclusion

Publications

The potential effects of clinical antidiabetic agents on SARS-CoV-2.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets