Is GSK3β a molecular target of chloroquine treatment against COVID-19?

A deep learning drug screening framework for integrating local-global characteristics: A novel attempt for limited data

At the beginning of the "Disease X" outbreak, drug discovery and development are often challenged by insufficient and unbalanced data. To address this problem and maximize the information value of limited data, we propose a drug screening model, LGCNN, based on convolutional neural network (CNN), which enables rapid drug screening by integrating features of drug molecular structures and drug-target interactions at both local and global (LG) levels. Experimental results show that LGCNN exhibits better performance compared to other state-of-the-art classification methods under limited data. In addition, LGCNN was applied to anti-SARS-CoV-2 drug screening to realize therapeutic drug mining against COVID-19. LGCNN transcends the limitations of traditional models for predicting interactions between single drug targets and shows new advantages in predicting multi-target drug-target interactions. Notably, the cross-coronavirus generalizability of the model is also implied by the analysis of targets, drugs, and mechanisms in the prediction results. In conclusion, LGCNN provides new ideas and methods for rapid drug screening in emergency situations where data are scarce.

Chloroquine modulates the sulforaphane anti-obesity mechanisms in a high-fat diet model: Role of JAK-2/ STAT-3/ SOCS-3 pathway

The phytochemical sulforaphane (SFN) has been studied for its potential anti-obesity effect, but neither its molecular targets nor its interaction with the antimalarial drug chloroquine (CQ) has been fully delineated. Therefore, high-fat diet (HFD) obese rats were randomly allocated into one of five groups and were left untreated or gavaged orally with SFN (0.5 or 1 mg/kg), CQ (5 mg/kg), or their combination (0.5/5 mg/kg) for six successive weeks to assess their potential interaction and the enrolled mechanisms. SFN effectively reduced the HFD-induced weight gain, blood glucose, and serum leptin levels, and improved lipid profile. On the molecular level, SFN inhibited the lipogenesis-related enzymes, namely sterol regulatory element-binding protein (SREBP)-1c, fatty acid synthase (FAS), and acetyl-CoA carboxylase (ACC) in both liver and visceral white adipose tissue (vWAT) of HFD obese rats. SFN also turned off the inflammatory pathway conserved Janus kinase/signaling transducers and activators of transcription/suppressor of cytokine signaling (JAK-2/STAT-3/SOCS-3) in these tissues, as well as the inflammatory markers nuclear factor-kappa (NF-κ) B and interleukin (IL)-22 in serum. In contrast, SFN downregulated the gene expression of microRNA (miR-200a), while significantly increasing the autophagic parameters; viz., beclin-1, autophagy-related protein (ATG)-7, and microtubule-associated protein 2 light chain 3 (LC3-II) in both liver and vWAT. On most of the parameters mentioned above, treatment with CQ solely produced a satisfactory effect and intensified the low dose of SFN in the combination regimen. These findings demonstrated the beneficial effects of using CQ as an add-on anti-obesity medicine to SFN.

Integrative COVID-19 biological network inference with probabilistic core decomposition

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for millions of deaths around the world. To help contribute to the understanding of crucial knowledge and to further generate new hypotheses relevant to SARS-CoV-2 and human protein interactions, we make use of the information abundant Biomine probabilistic database and extend the experimentally identified SARS-CoV-2-human protein-protein interaction (PPI) network in silico. We generate an extended network by integrating information from the Biomine database, the PPI network and other experimentally validated results. To generate novel hypotheses, we focus on the high-connectivity sub-communities that overlap most with the integrated experimentally validated results in the extended network. Therefore, we propose a new data analysis pipeline that can efficiently compute core decomposition on the extended network and identify dense subgraphs. We then evaluate the identified dense subgraph and the generated hypotheses in three contexts: literature validation for uncovered virus targeting genes and proteins, gene function enrichment analysis on subgraphs and literature support on drug repurposing for identified tissues and diseases related to COVID-19. The major types of the generated hypotheses are proteins with their encoding genes and we rank them by sorting their connections to the integrated experimentally validated nodes. In addition, we compile a comprehensive list of novel genes, and proteins potentially related to COVID-19, as well as novel diseases which might be comorbidities. Together with the generated hypotheses, our results provide novel knowledge relevant to COVID-19 for further validation.

Antivirals for COVID-19: A critical review

No specific drugs have been approved for coronavirus disease 2019 (COVID-19) to date as the development of antivirals usually requires time. Therefore, assessment and use of currently available antiviral drugs is critical for a timely response to the current pandemic. Here, we have reviewed anti-SARS-CoV-2 potencies of available antiviral drug groups such as fusion inhibitors, protease inhibitors, neuraminidase inhibitors, and M2 ion-channel protein blockers. Although clinical trials to assess the efficacy of these antivirals are ongoing, this review highlights important information including docking and modeling analyses, in vitro studies, as well as results from clinical uses of these antivirals against COVID-19 pandemic.

Molecular mechanisms and pharmacological interventions in the replication cycle of human coronaviruses

SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), as well as SARS-CoV from 2003 along with MERS-CoV from 2012, is a member of the Betacoronavirus genus of the Nidovirales order and is currently the cause of the pandemic called COVID-19 (or Coronavirus disease 2019). COVID-19, which is characterized by cough, fever, fatigue, and severe cases of pneumonia, has affected more than 23 million people worldwide until August 25th, 2020. Here, we present a review of the cellular mechanisms associated with human coronavirus replication, including the unique molecular events related to the replication transcription complex (RTC) of coronaviruses. We also present information regarding the interactions between each viral protein and cellular proteins associated to known host-pathogen implications for the coronavirus biology. Finally, a specific topic addresses the current attempts for pharmacological interventions against COVID-19, highlighting the possible effects of each drug on the molecular events of viral replication. This review intends to aid future studies for a better understanding of the SARS-CoV-2 replication cycle and the development of pharmacological approaches targeting COVID-19.

Screening of potential drug for Alzheimer's disease: a computational study with GSK-3 β inhibition through virtual screening, docking, and molecular dynamics simulation

The global impact of Alzheimer's disease (AD) necessitates intensive research to find appropriate and effective drugs. Many studies in AD suggested beta-amyloid plaques and neurofibrillary tangles-associated tau protein as the key targets for drug development. On the other hand, it is proved that triggering of Glycogen Synthase Kinase-3β (GSK-3β) also cause AD, therefore, GSK-3β is a potential drug target to combat AD. We, in this study, investigated the ability of small molecules to inhibit GSK-3β through virtual screening, Absorption, Distribution, Metabolism, and Excretion (ADME), induced-fit docking (IFD), molecular dynamics simulation, and binding free energy calculation. Besides, molecular docking was performed to reveal the binding and interaction of the ligand at the active site of GSK-3β. We found two compounds such as 6961 and 6966, which exhibited steady-state interaction with GSK-3β for 30 ns in molecular dynamics simulation. The compounds (6961 and 6966) also achieved a docking score of -9.05 kcal/mol and -8.11 kcal/mol, respectively, which is relatively higher than the GSK-3β II inhibitor (-6.73 kcal/mol). The molecular dynamics simulation revealed that the compounds have a stable state during overall simulation time, and lesser root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) values compared with co-crystal. In conclusion, we suggest the two compounds (6966 and 6961) as potential leads that could be utilized as effective inhibitors of GSK-3β to combat AD.

Updates on the Pharmacology of Chloroquine against Coronavirus Disease 2019 (COVID-19): A Perspective on its Use in the General and Geriatric Population

BACKGROUND

Chloroquine has been used to treat malaria for more than 70 years. Its safety profile and cost-effectiveness are well-documented. Scientists have found that chloroquine has in vitro activity against novel coronavirus (SARS-CoV-2). Currently, chloroquine has been adopted in the Protocol for Managing Coronavirus Disease 2019 (COVID-19) (Version 7) issued by the China National Health Commission for clinically managing COVID-19.

OBJECTIVE

This review will focus on the antiviral mechanism, effectiveness and safety, dosage and DDIs of chloroquine, for the purpose of providing evidence-based support for rational use of chloroquine in the treatment of COVID-19.

METHODS

Use the search terms "chloroquine" linked with "effectiveness", "safety", "mechanism", "drug-drug interaction (DDIs)" or other terms respectively to search relevant literature through PubMed.

RESULTS

After searching, we found literature about antivirus mechanism, dosage, DDIs of chloroquine. However, studies on the effectiveness and safety of chloroquine treatment for COVID-19 for the general and geriatric patients are not enough.

CONCLUSION

According to literature reports, chloroquine has been proven to have anti-SARS-CoV-2 effect in vitro and the potential mechanism of chloroquine in vivo. Pharmacokinetic characteristics and DDIs study are helpful in guiding rational drug use in general and geriatric patients. Although there have been reports of successful clinical application of chloroquine in the treatment COVID-19, more clinical test data are still needed to prove its effectiveness and safety.

Discovery of Synergistic and Antagonistic Drug Combinations against SARS-CoV-2 In Vitro

COVID-19 is undoubtedly the most impactful viral disease of the current century, afflicting millions worldwide. As yet, there is not an approved vaccine, as well as limited options from existing drugs for treating this disease. We hypothesized that combining drugs with independent mechanisms of action could result in synergy against SARS-CoV-2. Using in silico approaches, we prioritized 73 combinations of 32 drugs with potential activity against SARS-CoV-2 and then tested them in vitro . Overall, we identified 16 synergistic and 8 antagonistic combinations, 4 of which were both synergistic and antagonistic in a dose-dependent manner. Among the 16 synergistic cases, combinations of nitazoxanide with three other compounds (remdesivir, amodiaquine and umifenovir) were the most notable, all exhibiting significant synergy against SARS-CoV-2. The combination of nitazoxanide, an FDA-approved drug, and remdesivir, FDA emergency use authorization for the treatment of COVID-19, demonstrate a strong synergistic interaction. Notably, the combination of remdesivir and hydroxychloroquine demonstrated strong antagonism. Overall, our results emphasize the importance of both drug repurposing and preclinical testing of drug combinations for potential therapeutic use against SARS-CoV-2 infections.

Lithium as a candidate treatment for COVID-19: Promises and pitfalls

The pandemic of respiratory illness caused by a novel coronavirus (SARS-nCoV-2) is a global health crisis. Despite numerous preliminary results, there is as yet no treatment of proven efficacy for this condition. In this context, the pharmacological properties of lithium, better known as a treatment for mood disorders, merit closer examination. Lithium has shown in vitro efficacy at inhibiting the replication of coronaviruses responsible for gastrointestinal and respiratory diseases in animals. It has immunomodulatory properties that may be of additional benefit in moderating the host inflammatory response to the novel coronavirus (SARS-CoV-2). Furthermore, there is evidence that lithium may exert a protective action against upper respiratory infections and influenza-like illnesses in patients taking it for other indications. These promising reports must be balanced against the narrow therapeutic index and high risk of toxicity associated with lithium therapy, its documented interactions with several commonly used drugs, and the absence of evidence of its efficacy against coronaviruses responsible for human disease. Nevertheless, naturalistic studies of the risk of COVID-19 in patients already receiving lithium could provide indirect evidence of its efficacy, and understanding the putative antiviral and immune-regulatory mechanisms of lithium in models of SARS-CoV-2 infection may provide leads for the development of safer and more effective treatments with a specific action against COVID-19.