Derivatization and combination therapy of current COVID-19 therapeutic agents: a review of mechanistic pathways, adverse effects, and binding sites

Navigating the crisis: A review of COVID-19 research and the importance of academic publications - The case of a private university in Lebanon

Objectives

The threat of the Corona virus has had a profound global impact, prompting extensive discussions among academicians and medical researchers seeking to understand its implications across various fields. Consequently this review aims to explore the COVID-19 research approaches adopted at the Lebanese American University (LAU) between 2019 and 2022 and, to eventually shed light on the importance of the academic publications during this crisis period in the context of Lebanon.

Design Data sources Eligibility criteria

Studies related to "Coronavirus", "SARS-CoV-2," or "COVID-19″ were extracted from the SciVal database spanning the period 2019 to 2022. The identified studies, totaling 97 publications, were indexed in Scopus and Web of Science and underwent narrative analysis along with an evaluation using a predefined scale to determine their eligibility. The majority of the studies were literature reviews, followed by observational studies, modeling studies, systematic reviews, and meta-analyses.

Results

The majority of the identified studies (31 %) were focused on the medical field, primarily the impact of SARS-CoV-2 infection. Additionally, 22 % of studies discussed updates related to global finance and economic markets, while 18 % addressed the psychological burden of the pandemic. Other areas covered in the literature included the impact on performance, nutrition, tourism, politics, and telecommunication.

Conclusion

This study marks a pioneering endeavor that sparks a crucial dialogue regarding peer-reviewed scientific literature during a period of immense need for accurate information. The prevalence of literature reviews can be attributed to the demand for swift dissemination of preliminary findings and the increased call for COVID-19-related research. However, despite the abundance of publications in this specific domain, it is imperative for future research to shift its focus towards the development of novel therapies, preventive measures, psychological insights, and strategies to address the socioeconomic and financial burdens stemming from the pandemic. This study has the potential to establish a standardized framework for addressing similar crises across diverse fields and at various levels.

Limitations

The review readily acknowledges certain limitations. By solely relying on specific databases like Scopus and WoS, there is a possibility of inadvertently overlooking relevant studies. Although the study provides insights into the impact of COVID-19 across different fields and their respective publications, it is important to recognize that the continuous updates to databases and potential exclusions of related studies may have imposed constraints on the findings. Moreover, the urgency for expeditious peer-review during the pandemic may have heightened the chances of errors and diminished transparency. This urgency has unfortunately increased the risk of fraudulent activities and misconduct.

Crowdsourcing temporal transcriptomic coronavirus host infection data: Resources, guide, and novel insights

The emergence of severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) reawakened the need to rapidly understand the molecular etiologies, pandemic potential, and prospective treatments of infectious agents. The lack of existing data on SARS-CoV-2 hampered early attempts to treat severe forms of coronavirus disease-2019 (COVID-19) during the pandemic. This study coupled existing transcriptomic data from severe acute respiratory syndrome-related coronavirus 1 (SARS-CoV-1) lung infection animal studies with crowdsourcing statistical approaches to derive temporal meta-signatures of host responses during early viral accumulation and subsequent clearance stages. Unsupervised and supervised machine learning approaches identified top dysregulated genes and potential biomarkers (e.g. CXCL10, BEX2, and ADM). Temporal meta-signatures revealed distinct gene expression programs with biological implications to a series of host responses underlying sustained Cxcl10 expression and Stat signaling. Cell cycle switched from G1/G0 phase genes, early in infection, to a G2/M gene signature during late infection that correlated with the enrichment of DNA damage response and repair genes. The SARS-CoV-1 meta-signatures were shown to closely emulate human SARS-CoV-2 host responses from emerging RNAseq, single cell, and proteomics data with early monocyte-macrophage activation followed by lymphocyte proliferation. The circulatory hormone adrenomedullin was observed as maximally elevated in elderly patients who died from COVID-19. Stage-specific correlations to compounds with potential to treat COVID-19 and future coronavirus infections were in part validated by a subset of twenty-four that are in clinical trials to treat COVID-19. This study represents a roadmap to leverage existing data in the public domain to derive novel molecular and biological insights and potential treatments to emerging human pathogens.

COWAVE: A labelled COVID-19 wave dataset for building predictive models

The ongoing COVID-19 pandemic has posed a significant global challenge to healthcare systems. Every country has seen multiple waves of this disease, placing a considerable strain on healthcare resources. Across the world, the pandemic has motivated diligent data collection, with an enormous amount of data being available in the public domain. In this manuscript, we collate COVID-19 case data from around the world (available on the World Health Organization (WHO) website), and provide various definitions for waves. Using these definitions to define labels, we create a labelled dataset, which can be used while building supervised learning classifiers. We also use a simple eXtreme Gradient Boosting (XGBoost) model to provide a minimum standard for future classifiers trained on this dataset and demonstrate the utility of our dataset for the prediction of (future) waves. This dataset will be a valuable resource for epidemiologists and others interested in the early prediction of future waves. The datasets are available from https://github.com/RamanLab/COWAVE/.

Identifying health research in the era of COVID-19: A scoping review

Background

Health improvements are considered one of the most important fields of research. Since the coronavirus disease 2019 was declared a pandemic, it might have impacted clinical and public health research in various forms.

Objectives

The goal of this study is to explore health research approaches in the era of coronavirus disease 2019.

Methods

In this scoping review, we reviewed published medical full-text studies and identified potential areas of interest of health research in the era the coronavirus disease 2019 pandemic during the last 3 years within a higher educational setting. A bibliometric analysis was used to compare among published works.

Results

Among the 93 studies that met the inclusion criteria, most focused on mental health (n = 23; 24.7%). Twenty-one publications targeted coronavirus disease 2019 and its consequences on general health. Other studies have described hemato-oncological, cardiovascular, respiratory, and endocrinological diseases. 42 studies were cross-sectional or cohort studies and most of them published in Q1 journals. Almost half of them belonged to the Faculty of Medicine (49.5%) followed by the School of Arts, Sciences, and Psychology (26.9%).

Conclusions

Health research has been demonstrated to be important, at all times, especially during crises. Therefore, researchers need to invest more efforts into seeking new medical updates in various health-related fields, regardless of their correlation with coronavirus disease 2019.

Early recognition of risk of critical adverse events based on deep neural decision gradient boosting

Introduction

Perioperative critical events will affect the quality of medical services and threaten the safety of patients. Using scientific methods to evaluate the perioperative risk of critical illness is of great significance for improving the quality of medical services and ensuring the safety of patients.

Method

At present, the traditional scoring system is mainly used to predict the score of critical illness, which is mainly dependent on the judgment of doctors. The result is affected by doctors' knowledge and experience, and the accuracy is difficult to guarantee and has a serious lag. Besides, the statistical prediction method based on pure data type do not make use of the patient's diagnostic text information and cannot identify comprehensive risk factor. Therefore, this paper combines the text features extracted by deep neural network with the pure numerical type features extracted by XGBOOST to propose a deep neural decision gradient boosting model. Supervised learning was used to train the risk prediction model to analyze the occurrence of critical illness during the perioperative period for early warning.

Results

We evaluated the proposed methods based on the real data of critical illness patients in one hospital from 2014 to 2018. The results showed that the critical disease risk prediction model based on multiple modes had faster convergence rate and better performance than the risk prediction model based on text data and pure data type.

Discussion

Based on the machine learning method and multi-modal data of patients, this paper built a prediction model for critical adverse events in patients, so that the risk of critical events can be predicted for any patient directly based on the preoperative and intraoperative characteristic data. At present, this work only classifies and predicts the occurrence of critical illness during or after operation based on the preoperative examination data of patients, but does not discuss the specific time when the patient was critical illness, which is also the direction of our future work.

Repurposing FDA-approved drugs cetilistat, abiraterone, diiodohydroxyquinoline, bexarotene, and remdesivir as potential inhibitors against RNA dependent RNA polymerase of SARS-CoV-2: A comparative in silico perspective

Vaccines are undoubtedly the most effective means of combating viral diseases like COVID-19. However, there are risks associated with vaccination, such as incomplete viral deactivation or potential adverse effects in humans. However, designing and developing a panel of new drug molecules is always encouraged. In an emergency, drug repurposing research is one of the most potent and rapid options. RdRp (RNA-dependent RNA polymerase) has been discovered to play a pivotal role in viral replication. In this study, FDA-approved drugs bexarotene, diiodohydroxyquinoline, abiraterone, cetilistat, and remdesivir were repurposed against the RdRp by molecular modeling, docking, and dynamic simulation. Furthermore, to validate the potency of these drugs, we compared them to the antiviral remdesivir, which inhibits RdRp. Our finding indicated that the selected drugs have a high potential to be developed as RdRp inhibitors and, with further validation studies, could serve as potential drugs for the treatment of COVID-19.

The Problem of Drug Interactions Between Rosuvastatin and Ticagrelor in the Aspect of the Risk of Rhabdomyolysis: Discussion of the Problem and Description of the Clinical Case

Background. Combination therapy with two antiplatelet agents (ticagrelor or clopidogrel plus acetylsalicylic acid) and a high dose statin is recommended in accordance with clinical guidelines for patients undergoing acute coronary syndrome and coronary intervention. Combined therapeutic regimens have drug-drug interaction potential. Rhabdomyolysis is a known side effect of statin therapy, and there is evidence that co-therapy with ticagrelor increases the risk of this complication.Case description. A 72-year-old female patient was hospitalized with typical signs of rhabdomyolysis: muscle pain, oliguria, weakness, significant increases in creatine kinase (CK), myoglobin and creatinine. One month before that, she was urgently hospitalized with acute recurrent ST-elevation myocardial infarction and underwent endovascular intervention on a critical stenosis of the left anterior descending artery with stent implantation. After that, rosuvastatin 40 mg per day and ticagrelor 90mg 2 times a day were added to her therapy. During the current hospitalization, rosuvastatin, ACE inhibitors and spirolactone were canceled, infusion therapy was carried out, which led to a rapid regression of symptoms, restoration of adequate diuresis, and normalization of CK, myoglobin and creatinine levels. Conclusions. The combined use of ticagrelor with rosuvastatin (especially at a high dose) increases the risk of rhabdomyolysis in elderly patients. Patients taking ticagrelor may require changes in statin therapy, dose adjustments, and possible drug changes to avoid pharmacological interactions and an increased risk of side effects.

A Systematic Review of the Global Intervention for SARS-CoV-2 Combating: From Drugs Repurposing to Molnupiravir Approval

The rising outbreak of SARS-CoV-2 continues to unfold all over the world. The development of novel effective antiviral drugs to fight against SARS-CoV-2 is a time cost. As a result, some specific FDA-approved drugs have already been repurposed and authorized for COVID-19 treatment. The repurposed drugs used were either antiviral or non-antiviral drugs. Accordingly, the present review thoroughly focuses on the repurposing efficacy of these drugs including clinical trials experienced, the combination therapies used, the novel methods followed for treatment, and their future perspective. Therefore, drug repurposing was regarded as an effective avenue for COVID-19 treatment. Recently, molnupiravir is a prodrug antiviral medication that was approved in the United Kingdom in November 2021 for the treatment of COVID-19. On the other hand, PF-07321332 is an oral antiviral drug developed by Pfizer. For the treatment of COVID-19, the PF-07321332/ritonavir combination medication is used in Phase III studies and was marketed as Paxlovid. Herein, we represented the almost history of combating COVID-19 from repurposing to the recently available oral anti-SARS-CoV-2 candidates, as a new hope to end the current pandemic.

Molecular docking and dynamics studies of Nicotinamide Riboside as a potential multi-target nutraceutical against SARS-CoV-2 entry, replication, and transcription: A new insight

The highly contagious Coronavirus Disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which is a newborn infectious member of the dangerous beta-coronaviruses (β-CoVs) following SARS and MERS‐CoVs, can be regarded as the most significant issue afflicting the whole world shortly after December 2019. Considering CoVs as RNA viruses with a single-stranded RNA genome (+ssRNA), the critical viral enzyme RNA dependent RNA polymerase (RdRp) is a promising therapeutic target for the potentially fatal infection COVID-19. Nicotinamide riboside (NR), which is a naturally occurring analogue of Niacin (vitamin B3), is expected to have therapeutic effects on COVID-19 due to its super close structural similarity to the proven RdRp inhibitors. Thus, at the first phase of the current molecular docking and dynamics simulation studies, we targeted SARS-CoV-2 RdRp. On the next phase, SARS-CoV RdRp, human Angiotensin-converting enzyme 2, Inosine-5’-monophosphate dehydrogenase, and the SARS-CoV-2 Structural Glycoproteins Spike, Nonstructural viral protein 3-Chymotrypsin-like protease, and Papain-like protease were targeted using the docking simulation to find other possible antiviral effects of NR serendipitously. In the current study, the resulted scores from molecular docking and dynamics simulations as the primary determinative factor as well as the observed reliable binding modes have demonstrated that Nicotinamide Riboside and its active metabolite NMN can target human ACE2 and IMPDH, along with the viral S^pro, M^pro, PL^pro, and on top of all, RdRp as a potential competitive inhibitor.

Recent Developments on Therapeutic and Diagnostic Approaches for COVID-19

The ongoing pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has made a serious public health threat worldwide with millions of people at risk in a growing number of countries. Though there are no clinically approved antiviral drugs and vaccines for COVID-19, attempts are ongoing for clinical trials of several known antiviral drugs, their combination, as well as development of vaccines in patients with confirmed COVID-19. This review focuses on the latest approaches to diagnostics and therapy of COVID-19. We have summarized recent progress on the conventional therapeutics such as antiviral drugs, vaccines, anti-SARS-CoV-2 antibody treatments, and convalescent plasma therapy which are currently under extensive research and clinical trials for the treatment of COVID-19. The developments of nanoparticle-based therapeutic and diagnostic approaches have been also discussed for COVID-19. We have assessed recent literature data on this topic and made a summary of current development and future perspectives.

A comparative analysis for anti-viral drugs: Their efficiency against SARS-CoV-2

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Coronavirus is continuing its spread across the world,

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More than 42 million confirmed COVID-19 cases was reported.

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Scientist focuses on the finding novel drugs and vaccine for SARS-COV-2.

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Antiviral drugs are mostly used for the treatments of COVID-19.

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Drugs are analyzed and compare the efficiency for the Covid-19 patients.

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The mechanism of actions of anti-COVID-19 drugs was proposed.

Coronavirus, known as the coronavirus pandemic, is continuing its spread across the world, with over 42 million confirmed cases in 189 countries and more than 1.15 million deaths. Although, scientists focus on the finding novel drugs and vaccine for SARS-CoV-2, there is no certain treatment for it. Antiviral drugs such as; oseltamivir, favipiravir, umifenovir, lopinavir, remdesivir, hydroxychloroquine, chloroquine, azithromycin, ascorbic acid, corticosteroids, are mostly used for patients. They prevent cytokine storm that is the main reason of deaths related to SARS-CoV-2. In addition, anti-inflammatory agents have critical roles to inhibit the lung injury and multisystem organ dysfunction. The combination with anti-viral drugs with other drugs displays high synergistic effects. In the present study, the drugs used for Covid-19 are analyzed and compare the efficiency for the Covid-19 patients from the different continents including USA, South Korea, Italy, Spain, Germany, Russia, Brazil, Turkey, and China. Nowadays, all countries tried to find vaccine and new drug candidates for SARS-CoV-2, but anti-viral drugs may be the best candidates for the treatment of Covid-19 before finding novel anti-Covid drug.