Repositioning of anti-infective compounds against monkeypox virus core cysteine proteinase: a molecular dynamics study.

Monkeypox virus (MPXV) core cysteine proteinase (CCP) is one of the major drug targets used to examine the inhibitory action of chemical moieties. In this study, an in silico technique was applied to screen 1395 anti-infective compounds to find out the potential molecules against the MPXV-CCP. The top five hits were selected after screening and processed for exhaustive docking based on the docked score of ≤ -9.5 kcal/mol. Later, the top three hits based on the exhaustive-docking score and interaction profile were selected to perform MD simulations. The overall RMSD suggested that two compounds, SC75741 and ammonium glycyrrhizinate, showed a highly stable complex with a standard deviation of 0.18 and 0.23 nm, respectively. Later, the MM/GBSA binding free energies of complexes showed significant binding strength with ΔGTOTAL from -21.59 to -15 kcal/mol. This report reported the potential inhibitory activity of SC75741 and ammonium glycyrrhizinate against MPXV-CCP by competitively inhibiting the binding of the native substrate.

Antifungal drug discovery for targeting Candida albicans morphogenesis through structural dynamics study.

In response to the escalating threat of drug-resistant fungi to human health, there is an urgent need for innovative strategies. Our focus is on addressing this challenge by exploring a previously untapped target, yeast casein kinase (Yck2), as a potential space for antifungal development. To identify promising antifungal candidates, we conducted a thorough screening of the diverse-lib drug-like molecule library, comprising 99,288 molecules. Five notable drug-like compounds with diverse-lib IDs 24334243, 24342416, 17516746, 17407455, and 24360740 were selected based on their binding energy scores surpassing 11 Kcal/mol. Our investigation delved into the interaction studies and dynamic stability of these compounds. Remarkably, all selected molecules demonstrated acceptable RMSD values during the 200 ns simulation, indicating their stable nature. Further analysis through Principal Component Analysis (PCA)-based Free Energy Landscape (FEL) revealed minimal energy transitions for most compounds, signifying dynamic stability. Notably, the two compounds exhibited slightly different behaviour in terms of energy transitions. These findings mark a significant breakthrough in the realm of antifungal drugs against C. albicans by targeting the Yck2 protein. However, it is crucial to note that additional experimental validation is imperative to assess the efficacy of these molecules as potential antifungal candidates. This study serves as a promising starting point for further exploration and development in the quest for effective antifungal solutions.Communicated by Ramaswamy H. Sarma.

Antiviral actions of natural compounds against dengue virus RNA dependent RNA polymerase: insights from molecular dynamics and Gibbs free energy landscape.

Dengue fever, a major global health challenge, affects nearly half the world's population and lacks effective treatments or vaccines. Addressing this, our study focused on natural compounds that potentially inhibit the dengue virus's RNA-dependent RNA polymerase (RdRp), a crucial target in the viral replication cycle. Utilizing the MTiOpenScreen webserver, we screened 1226 natural compounds from the NP-lib database. This screening identified four promising compounds ZINC000059779788, ZINC0000044404209, ZINC0000253504517 and ZINC0000253499146), each demonstrating high negative binding energies between -10.4 and -9.9 kcal/mol, indicative of strong potential as RdRp inhibitors. These compounds underwent rigorous validation through re-docking and a detailed 100 ns molecular dynamics (MD) simulation. This analysis affirmed the dynamic stability of the protein-ligand complexes, a critical factor in the effectiveness of potential drug candidates. Additionally, we conducted essential dynamics and free energy landscape calculations to understand the structural transitions in the RdRp protein upon ligand binding, providing valuable insights into the mechanism of inhibition. Our findings present these natural molecules as promising therapeutic agents against the dengue virus. By targeting the allosteric site of RdRp, these compounds offer a novel approach to hinder the viral replication process. This research significantly contributes to the search for effective anti-dengue treatments, positioning natural compounds as potential key players in dengue virus control strategies.Communicated by Ramaswamy H. Sarma.

Investigation of Zika virus methyl transferase inhibitors using steered molecular dynamics.

Zika virus (ZIKV) spread is considered a major public health threat by the World Health Organization (WHO). There are no vaccines or drugs available to control the infection of the Zika virus, therefore a highly effective medicinal molecule is urgently required. In this study, a computationally intensive investigation was performed to identify a potent natural compound that could inhibit the ZIKV NS5 methyltransferase. This research approach is based on target-based drug identification principles where the native inhibitor SAH (S-adenosylhomocysteine) of ZIKV NS5 methyltransferase was selected as a reference. High-throughput virtual screening and tanimoto similarity coefficient were applied to the natural compound library for ranking the potential candidates. The top five compounds were selected for interaction analysis, MD simulation, total binding free energy through MM/GBSA, and steered MD simulation. Among these compounds, Adenosine 5'-monophosphate monohydrate, Tubercidin, and 5-Iodotubercidin showed stable binding to the protein compared to the native compound, SAH. These three compounds also showed less fluctuations in RMSF in contrast to native compound. Additionally, the same interacting residues observed in SAH also made strong interactions with these three compounds. Adenosine 5'-monophosphate monohydrate and 5-Iodotubercidin had greater total binding free energies than the reference ligand. Moreover, the dissociation resistance of all three compounds was equivalent to that of the reference ligand. This study suggested binding properties of three-hit compounds that could be used to develop drugs against Zika virus infections.Communicated by Ramaswamy H. Sarma.

Exploration of phytochemical compounds against Marburg virus using QSAR, molecular dynamics, and free energy landscape.

Marburg virus disease (MVD) is caused by the Marburg virus, a one-of-a-kind zoonotic RNA virus from the genus Filovirus. Thus, this current study employed AI-based QSAR and molecular docking-based virtual screening for identifying potential binders against the target protein (nucleoprotein (NP)) of the Marburg virus. A total of 2727 phytochemicals were used for screening, out of which the top three compounds (74977521, 90470472, and 11953909) were identified based on their predicted bioactivity (pIC50) and binding score (< - 7.4 kcal/mol). Later, MD simulation in triplicates and trajectory analysis were performed which showed that 11953909 and 74977521 had the most stable and consistent complex formations and had the most significant interactions with the highest number of hydrogen bonds. PCA (principal component analysis) and FEL (free energy landscape) analysis indicated that these compounds had favourable energy states for most of the conformations. The total binding free energy of the compounds using the MM/GBSA technique showed that 11953909 (ΔGTOTAL = - 30.78 kcal/mol) and 74977521 (ΔGTOTAL = - 30 kcal/mol) had the highest binding affinity with the protein. Overall, this in silico pipeline proposed that the phytochemicals 11953909 and 74977521 could be the possible binders of NP. This study aimed to find phytochemicals inhibiting the protein's function and potentially treating MVD.

Current and Future Technologies for the Detection of Antibiotic-Resistant Bacteria.

Antibiotic resistance is a global public health concern, posing a significant threat to the effectiveness of antibiotics in treating bacterial infections. The accurate and timely detection of antibiotic-resistant bacteria is crucial for implementing appropriate treatment strategies and preventing the spread of resistant strains. This manuscript provides an overview of the current and emerging technologies used for the detection of antibiotic-resistant bacteria. We discuss traditional culture-based methods, molecular techniques, and innovative approaches, highlighting their advantages, limitations, and potential future applications. By understanding the strengths and limitations of these technologies, researchers and healthcare professionals can make informed decisions in combating antibiotic resistance and improving patient outcomes.

Immunoinformatic Execution and Design of an Anti-Epstein-Barr Virus Vaccine with Multiple Epitopes Triggering Innate and Adaptive Immune Responses.

One of the most important breakthroughs in healthcare is the development of vaccines. The life cycle and its gene expression in the numerous virus-associated disorders must be considered when choosing the target vaccine antigen for Epstein-Barr virus (EBV). The vaccine candidate used in the current study will also be effective against all other herpesvirus strains, based on the conservancy study, which verified that the protein is present in all herpesviruses. From the screening, two B-cell epitopes, four MHC-I, and five MHC-II restricted epitopes were chosen for further study. The refined epitopes indicated 70.59% coverage of the population in Malaysia and 93.98% worldwide. After removing the one toxin (PADRE) from the original vaccine design, it was projected that the new vaccine would not be similar to the human host and would instead be antigenic, immunogenic, non-allergenic, and non-toxic. The vaccine construct was stable, thermostable, soluble, and hydrophilic. The immunological simulation projected that the vaccine candidate would be subject to a long-lasting active adaptive response and a short-lived active innate response. With IgM concentrations of up to 450 cells per mm3 and active B-cell concentrations of up to 400 cells per mm3, the B-cells remain active for a considerable time. The construct also discovered other conformational epitopes, improving its ability to stimulate an immune response. This suggests that, upon injection, the epitope will target the B-cell surface receptors and elicit a potent immune response. Furthermore, the discotope analysis confirmed that our conformational B-cell epitope was not displaced during the design. Lastly, the docking complex was stable and exhibited little deformability under heat pressure. These computational results are very encouraging for future testing of our proposed vaccine, which may potentially help in the management and prevention of EBV infections worldwide.

Prevalence of Hepatocellular Carcinoma in Hepatitis B Population within Southeast Asia: A Systematic Review and Meta-Analysis of 39,050 Participants.

BACKGROUND AND AIM: Hepatocellular carcinoma (HCC) is a significant complication of hepatitis B and still poses a global public health concern. This systematic review and meta-analysis provide adequate details on the prevalence of HCC in the HBV population within Southeast Asian countries. METHOD: Following the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) criteria, a thorough search for literature discussing the prevalence of HCC in the HBV population within southeast Asia was performed. Eligible studies were subjected to a meta-analysis utilising a DerSimonian and Laird approach and a random effect model. A protocol was registered with PROSPERO (CRD42023423953). RESULT: Our study meticulously recovered 41 articles from seven countries in Southeast Asia, namely Cambodia, Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam. A total of 39,050 HBV patients and 7479 HCC cases in southeast Asia were analysed. The pooled prevalence of HCC in HBV cases within southeast Asia was 45.8% (95% CI, 34.3-57.8%, I2 = 99.51%, p < 0.001). Singapore (62.5%, CI: 42.4-79.1) had the highest pooled prevalence of HCC in the HBV population compared to Vietnam, with the lowest estimate (22.4%, CI: 9.9-44.9). There was a drop in the pooled prevalence of HCC in HBV from 2016 until now (37.6%, CI: 19.2-60.5). CONCLUSION: The findings of this review reveal a high pooled prevalence of HCC in the HBV population and therefore stir the need for routine screening, management, and surveillance.

Post COVID-19 Symptoms Among Infected Vaccinated Individuals: A Cross-Sectional Study in Saudi Arabia.

INTRODUCTION: Multiple studies investigated the endurance and occurrence of symptoms three months after SARS-CoV-2 infection. This study examines the possible effects of COVID-19 vaccination on the persistence of post-recovery symptoms. PATIENTS AND METHODS: A cross-sectional survey was conducted in Saudi Arabia to evaluate 14 prevalent long COVID-19 symptoms among vaccinated individuals. Patients self-reported their acute COVID-19 experience, demographic information, chronic conditions, vaccine history, and persistent symptoms. RESULTS: Of the 484 patients, four respondents were excluded from the study as they had not received the vaccine, and 111 (23.1%) were vaccinated but did not get infected and were also excluded. The remaining 369 (76.9%) reported COVID-19 and a vaccination and thus they were included in the study. The occurrence of post-COVID-19 symptoms was reported in 59 (16.1%) for ≤ 3 months, 202 (54.8%) experienced persistent symptoms 3-6 months, and 108 (29.1%) reported symptoms lasting > 6 months. In relation to age group, persistent symptoms 3-6 months after recovery was more common in those > 50 years and symptoms lasting > 6 months were more common in 30-50 years of age (p < 0.001). Persistence of symptoms for 3-6 months was more common in those who were infected prior to vaccination compared to those who were infected after vaccination (P < 0.001). Of the included patients, 323 (87.5%) rated their health as good, 41 (11.1%) considered it fair, and 5 (1.4%) described their well-being as poor or terrible. CONCLUSION: The study provides information of persistent symptoms in vaccinated individuals who had recovered from COVID-19 and highlights the need for targeted interventions to alleviate post-COVID-19 symptoms. The study is limited by its reliance on self-reported data and potential selection bias. Future research is needed to understand the mechanisms underlying persistent symptoms in vaccinated individuals and to identify effective interventions for long COVID.

Deep and Transfer Learning Approaches for Automated Early Detection of Monkeypox (Mpox) Alongside Other Similar Skin Lesions and Their Classification.

The world faces multiple public health emergencies simultaneously, such as COVID-19 and Monkeypox (mpox). mpox, from being a neglected disease, has emerged as a global threat that has spread to more than 100 nonendemic countries, even as COVID-19 has been spreading for more than 3 years now. The general mpox symptoms are similar to chickenpox and measles, thus leading to a possible misdiagnosis. This study aimed at facilitating a rapid and high-brevity mpox diagnosis. Reportedly, mpox circulates among particular groups, such as sexually promiscuous gay and bisexuals. Hence, selectively vaccinating, isolating, and treating them seems difficult due to the associated social stigma. Deep learning (DL) has great promise in image-based diagnosis and could help in error-free bulk diagnosis. The novelty proposed, the system adopted, and the methods and approaches are discussed in the article. The present work proposes the use of DL models for automated early mpox diagnosis. The performances of the proposed algorithms were evaluated using the data set available in public domain. The data set adopted for the study was meant for both training and testing, the details of which are elaborated. The performances of CNN, VGG19, ResNet 50, Inception v3, and Autoencoder algorithms were compared. It was concluded that CNN, VGG19, and Inception v3 could help in early detection of mpox skin lesions, and Inception v3 returned the best (96.56%) classification accuracy.

Unleashing the power of artificial intelligence for diagnosing and treating infectious diseases: A comprehensive review.

Infectious diseases present a global challenge, requiring accurate diagnosis, effective treatments, and preventive measures. Artificial intelligence (AI) has emerged as a promising tool for analysing complex molecular data and improving the diagnosis, treatment, and prevention of infectious diseases. Computer-aided detection (CAD) using convolutional neural networks (CNN) has gained prominence for diagnosing tuberculosis (TB) and other infectious diseases such as COVID-19, HIV, and viral pneumonia. The review discusses the challenges and limitations associated with AI in this field and explores various machine-learning models and AI-based approaches. Artificial neural networks (ANN), recurrent neural networks (RNN), support vector machines (SVM), multilayer neural networks (MLNN), CNN, long short-term memory (LSTM), and random forests (RF) are among the models discussed. The review emphasizes the potential of AI to enhance the accuracy and efficiency of diagnosis, treatment, and prevention of infectious diseases, highlighting the need for further research and development in this area.

Identification of natural potent inhibitors against Mycobacterium tuberculosis isocitrate lyase: an in silico study.

Tuberculosis (TB) is a global burden to humanity due to its adverse effects on health and society since time is not clearly defined. The existence of drug-resistant strains and the potential threat posed by latent tuberculosis act as strong impetuses for developing novel anti-tuberculosis drugs. In this study, various flavonoids were tested against the Mycobacterium tuberculosis (Mtb) Isocitrate Lyase (ICL), which has been identified as an authorised therapeutic target for treating Mtb infection. Using in silico drug discovery approach, a library of 241 flavonoid compounds was virtually screened against the binding pocket of the crystalline ligand, the VGX inhibitor, in the Mtb ICL protein. As a result, the top four flavonoids were selected based on binding score and were further considered for redocking and intermolecular contact profiling analysis. The global and local fluctuations in the protein and ligand structure were analysed using their root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values obtained from the GROMACS generated 100 ns molecular dynamics (MD) simulation trajectories. The end-state binding free energy was also calculated using the MMPBSA approach for all the respective docked complexes. All four selected compounds exhibited considerable stability and affinity compared to control ligands, i.e. VGX inhibitor; however, Vaccarin showed the highest stability and affinity against the Mtb ICL protein active site, followed by the Genistin, Glabridin, and Corylin. Therefore, this study recommends selected flavonoids for in vitro and in vivo experimental studies to check their potency and efficacy against Mtb.

Experimental drugs in randomized controlled trials for long-COVID: what's in the pipeline? A systematic and critical review.

INTRODUCTION: Over three years have passed since the emergence of coronavirus disease 2019 (COVID-19), and yet the treatment for long-COVID, a post-COVID-19 syndrome, remains long overdue. Currently, there is no standardized treatment available for long-COVID, primarily due to the lack of funding for post-acute infection syndromes (PAIS). Nevertheless, the past few years have seen a renewed interest in long-COVID research, with billions of dollars allocated for this purpose. As a result, multiple randomized controlled trials (RCTs) have been funded in the quest to find an effective treatment for long-COVID. AREAS COVERED: This systematic review identified and evaluated the potential of current drug treatments for long-COVID, examining both completed and ongoing RCTs. EXPERT OPINION: We identified four completed and 22 ongoing RCTs, investigating 22 unique drugs. However, most drugs were deemed to not have high potential for treating long-COVID, according to three pre-specified domains, a testament to the ordeal of treating long-COVID. Given that long-COVID is highly multifaceted with several proposed subtypes, treatments likely need to be tailored accordingly. Currently, rintatolimod appears to have modest to high potential for treating the myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) subtype, LTY-100 and Treamid for pulmonary fibrosis subtype, and metformin for general long-COVID prevention.

Cheminformatics and machine learning approaches for repurposing anti-viral compounds against monkeypox virus thymidylate kinase.

One of the emerging epidemic concerns is Monkeypox disease which is spreading globally. This disease is caused by the monkeypox virus (MPXV), with an increasing global incidence with an outbreak in 2022. One of the novel targets for monkeypox disease is thymidylate kinase, which is involved in pyrimidine metabolism. In this study, docking-based virtual screening and molecular dynamics techniques were employed in addition to the machine learning (ML) model to investigate the potential anti-viral natural small compounds to inhibit thymidylate kinase of MPXV. Several potential hits were identified through high-throughput virtual screening, and further top three candidates were selected, which ranked using the ML model. These three compounds were then examined under molecular dynamics simulation and MM/GBSA-binding free energy analysis. Among these, Chlorhexidine HCl showed high potential for binding to the thymidylate kinase with stable and consistent conformation with RMSD < 0.3 nm. The MM/GBSA analysis also showed the minimum binding free energy (ΔGTOTAL) of -62.41 kcal/mol for this compound. Overall, this study used structure-based drug design complemented by machine learning-guided ligand-based drug design to screen potential hit compounds from the anti-viral natural compound database.

Attitudes and Practices of the Public Toward Precautionary Measures Post-COVID-19 Pandemic in Saudi Arabia.

Objective: This study aimed to assess the practices and attitudes of the general population towards coronavirus disease-2019 (COVID)-19 after the removal of precautionary and preventive measures in Saudi Arabia. Methods: A cross-sectional study was conducted among the general population in all regions of the Kingdom of Saudi Arabia, from September 2022 to October, 2022 via a virtual survey to evaluate the practices, and attitudes of the general population towards COVID-19. A stratified random sampling technique was applied to collect the sample with inclusion criteria for all individuals who are Arabic language speakers using social media platforms. The individuals selected for this study were 18 years and older. Results: A total of 2406 responses were received for the study questionnaire. Most of participants (66.3%) were females aged 18 to 29 years (61.8%). Half of the participants reported a positive history of COVID-19 infection. Nearly 90% of participants still wear masks, 80% attended a crowded event, and 60% often wash their hands even though the Saudi government has erased the precautions. Females, young (30-39 years) and elderly (60 years and over) individuals, singles, those with a postgraduate degree, those who are employed, and healthcare workers were more likely to adhere to COVID-19 precautionary measures (p<0.05). Conclusion: The study's findings indicate that most of the population discontinued practicing precautionary measures after lifting the measures in Saudi Arabia. More public health initiatives should raise the scores of sanitary best practices to prevent the spread of viral illnesses.

A Comprehensive Review on Monkeypox Viral Disease with Potential Diagnostics and Therapeutic Options.

The purpose of this review is to give an up-to-date, thorough, and timely overview of monkeypox (Mpox), a severe infectious viral disease. Furthermore, this review provides an up-to-date treatment option for Mpox. The monkeypox virus (MPXV) has remained the most virulent poxvirus for humans since the elimination of smallpox approximately 41 years ago, with distribution mainly in central and west Africa. Mpox in humans is a zoonotically transferred disease that results in symptoms like those of smallpox. It had spread throughout west and central Africa when it was first diagnosed in the Republic of Congo in 1970. Mpox has become a major threat to global health security, necessitating a quick response by virologists, veterinarians, public health professionals, doctors, and researchers to create high-efficiency diagnostic tests, vaccinations, antivirals, and other infection control techniques. The emergence of epidemics outside of Africa emphasizes the disease's global significance. A better understanding of Mpox's dynamic epidemiology may be attained by increased surveillance and identification of cases.

An Updated Review on Monkeypox Viral Disease: Emphasis on Genomic Diversity.

Monkeypox virus has remained the most virulent poxvirus since the elimination of smallpox approximately 41 years ago, with distribution mostly in Central and West Africa. Monkeypox (Mpox) in humans is a zoonotically transferred disease that results in a smallpox-like disease. It was first diagnosed in 1970 in the Democratic Republic of the Congo (DRC), and the disease has spread over West and Central Africa. The purpose of this review was to give an up-to-date, thorough, and timely overview on the genomic diversity and evolution of a re-emerging infectious disease. The genetic profile of Mpox may also be helpful in targeting new therapeutic options based on genes, mutations, and phylogeny. Mpox has become a major threat to global health security, necessitating a quick response by virologists, veterinarians, public health professionals, doctors, and researchers to create high-efficiency diagnostic tests, vaccinations, antivirals, and other infection control techniques. The emergence of epidemics outside of Africa emphasizes the disease's global significance. Increased monitoring and identification of Mpox cases are critical tools for obtaining a better knowledge of the ever-changing epidemiology of this disease.

COVID-19 Vaccine Acceptance and Hesitancy among Migrants, Refugees, and Foreign Workers: A Systematic Review and Meta-Analysis.

Despite the effectiveness of current vaccines in reducing the spread and severity of SARS-CoV-2 infections, many people, including migrants, refugees, and foreign workers, are hesitant to be vaccinated. This systematic review and meta-analysis (SRMA) was conducted to determine the pooled prevalence estimate of the acceptance and hesitancy rates of the COVID-19 vaccine among these populations. A comprehensive search of the peer-reviewed literature indexed in PubMed, Scopus, Science Direct, and Web of Science databases was conducted. Initially, 797 potential records were identified, of which 19 articles met the inclusion criteria. A meta-analysis of proportions using data from 14 studies revealed that the overall acceptance rate of COVID vaccination among 29,152 subjects was 56.7% (95% CI: 44.9-68.5%), while the prevalence of vaccine hesitancy among 26,154 migrants reported in 12 studies was estimated to be 31.7% (95% CI: 44.9-68.5%). The acceptance rate for the COVID-19 vaccination first declined from 77.3% in 2020 to 52.9% in 2021 and then slightly increased to 56.1% in 2022. The most frequent factors influencing vaccine hesitancy were worries about vaccine efficacy and safety. Intensive vaccination campaigns should be implemented to raise vaccination awareness among migrants, which will increase the acceptance rate for the COVID-19 vaccine and result in herd immunity.

Exploration of potent antiviral phytomedicines from Lauraceae family plants against SARS-CoV-2 RNA-dependent RNA polymerase.

RNA-dependent RNA polymerase, also known as RdRp, is a possible therapeutic target that could be used to suppress the proliferation of RNA viruses such as SARS-CoV-2. This protein has two major functional sites (a) catalytic and (b) substrate entry, which regulate the natural substrate entry and its corresponding interaction with the protein. In this study, a computational drug design pipeline was applied to investigate potential inhibitors against SARS-CoV-2 RdRp from Lauraceae plants, and five top hits were selected based on the docked score (< -7 kcal/mol). The docking study suggested that the Glochidioboside had a minimum binding score of -7.8 kcal/mol. This compound showed total five hydrogen bonds while two of them were with catalytic residues Asp618 and Asp760. However, another compound, Sitogluside showed a binding score of -7.3 kcal/mol with four hydrogen bonds targeting three functional residues (Arg555, Ser759, and Asp760). Later, 100 ns explicit solvent molecular dynamics (MD) simulation was performed to evaluate the stability of the protein-ligand docked system. These compounds translocated their positions from the catalytic site to the substrate entry site, as observed in the MD simulation trajectory. However, translocation did not affect the binding strength of these compounds, and they retained the strong binding affinity (ΔG < -11.5 kcal/mol), estimated using the MM/GBSA method. In general, the findings of this study indicated the potential therapeutic compounds that may be used targeting SARS-CoV-2 RdRp. However, these compounds still need to be validated by experimentation in order to determine their inhibitory function.Communicated by Ramaswamy H. Sarma.

Regulatory T Cells (Tregs) and COVID-19: Unveiling the Mechanisms, and Therapeutic Potentialities with a Special Focus on Long COVID.

The COVID-19 pandemic has caused havoc all around the world. The causative agent of COVID-19 is the novel form of the coronavirus (CoV) named SARS-CoV-2, which results in immune system disruption, increased inflammation, and acute respiratory distress syndrome (ARDS). T cells have been important components of the immune system, which decide the fate of the COVID-19 disease. Recent studies have reported an important subset of T cells known as regulatory T cells (Tregs), which possess immunosuppressive and immunoregulatory properties and play a crucial role in the prognosis of COVID-19 disease. Recent studies have shown that COVID-19 patients have considerably fewer Tregs than the general population. Such a decrement may have an impact on COVID-19 patients in a number of ways, including diminishing the effect of inflammatory inhibition, creating an inequality in the Treg/Th17 percentage, and raising the chance of respiratory failure. Having fewer Tregs may enhance the likelihood of long COVID development in addition to contributing to the disease's poor prognosis. Additionally, tissue-resident Tregs provide tissue repair in addition to immunosuppressive and immunoregulatory activities, which may aid in the recovery of COVID-19 patients. The severity of the illness is also linked to abnormalities in the Tregs' phenotype, such as reduced expression of FoxP3 and other immunosuppressive cytokines, including IL-10 and TGF-beta. Hence, in this review, we summarize the immunosuppressive mechanisms and their possible roles in the prognosis of COVID-19 disease. Furthermore, the perturbations in Tregs have been associated with disease severity. The roles of Tregs are also explained in the long COVID. This review also discusses the potential therapeutic roles of Tregs in the management of patients with COVID-19.