Computational screening for investigating the synergistic regulatory potential of drugs and phytochemicals in combination with 2-deoxy-D-glucose against SARS-CoV-2.

COVID-19 disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was declared a global pandemic by the World Health Organization (WHO) in March 2020. Since then, the SARS-CoV-2 virus has impacted millions of lives worldwide. Various preclinical and clinical trials on the treatment of COVID-19 disease have revealed that the drugs that work in combination are more likely to reduce reinfection and multi-organ failure. Considering the combination drug therapy, herein, we performed a systematic computational study starting with the formation of sixty-two combinations of drugs and phytochemicals with 2-deoxy-D-glucose (2-DG). The top nineteen combinations resulting from Drug-Drug Interaction (DDI) analysis were selected for individual and multiple-ligand-simultaneous docking (MLSD) study with a host target Serine Protease (TMPRSS2; PDB ID: 7MEQ) and two viral targets, Main Protease (3CLpro; PDB ID: 6LU7) and Uridylate-Specific Endoribonuclease (NSP15; PDB ID: 6VWW). We found that the resulting drugs and phytochemicals in combination with 2-DG shows better binding than the individual compounds. We performed the re-docking of the top three drug combinations by utilizing the polypharmacology approach to validate the binding patterns of drug combinations with multiple targets for verifying the best drug combinatorial output obtained by blind docking. A strong binding affinity pattern was observed for 2-DG + Ruxolitinib (NIH-recommended drug), 2-DG + Telmisartan (phase 4 clinical trial drug), and 2-DG + Punicalagin (phytochemical) for all the selected targets. Additionally, we conducted multiple-ligand-simultaneous molecular dynamics (MLS-MD) simulations on the selected targets with the 2-DG + Ruxolitinib combination. The MLS-MD analysis of the drug combinations shows that stabilization of the interaction complexes could have significant inhibition potential against SARS CoV-2. This study provides an insight into developing drug combinations utilizing integrated computational approaches to uncover their potential in synergistic drug therapy. Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-02049-0.

The dual role of phytochemicals on SARS-CoV-2 inhibition by targeting host and viral proteins.

BACKGROUND: The severe acute respiratory syndrome-2019 has affected more than 190 million people around the world and caused severe crises throughout the globe. Due to rapid mutation in the viral genome, its became important to simultaneously improvise the host immunity while targeting viral proteins to reduce the severity of infection. AIM: The current computational work focuses on multi-level rigorous screening of 47 medicinal plant-based phytochemicals for discovering effective phytochemical inhibitors against the host and viral targets. EXPERIMENTAL PROCEDURE: A total of 586 phytochemicals were analyzed in detail based on their drug-likeness, pharmacological properties, and structure-based activity against the viral proteins (Spike glycoprotein, Papain-like protease, and Main protease) and host proteins (ACE2, Importin-subunit α-5, and ß-1). Phytochemicals showing higher binding affinity with the dual capacity to target both the categories of proteins were further analyzed by profiling of their chemical reactivity using Density-Functional Theory (DFT) based quantum chemical methods. Finally, detailed molecular dynamics simulations were performed to analyze the interactions of the complexes. RESULTS AND CONCLUSION: The results revealed that the selected phytochemicals from Andrographis paniculata, Aconitum heterophyllum, Costus speciosus and Inula racemosa may have the capacity to act with prominent affinity towards the host and viral proteins. Therefore, the combination of active phytochemicals of these plants may prove to be more beneficial and can be used for developing the potential phytotherapeutic intervention.

Deep Transfer Learning-Based COVID-19 Prediction Using Chest X-Rays

The novel coronavirus disease (COVID-19) is spreading very rapidly across the globe because of its highly contagious nature and is declared as a pandemic by the World Health Organization (WHO). Scientists are endeavouring to ascertain the drugs for its efficacious treatment. Because, until now, no full-proof drug is available to cure this deadly disease. Therefore, identifying COVID-19 positive people and quarantining them can be an effective solution to control its spread. Many machine learning and deep learning techniques are being used quite effectively to classify positive and negative cases. In this work, a deep transfer learning-based model is proposed to classify the COVID-19 cases using chest X-rays or CT scan images of infected persons. The proposed model is based on the ensembling of DenseNet121 and SqueezeNet1.0, which is named as DeQueezeNet. The model can extract the importance of various influential features from the X-ray images, which are effectively used to classify the COVID-19 cases. The performance study of the proposed model depicts its effectiveness in terms of accuracy and precision. A comparative study has also been done with the recently published works, and it is observed that the performance of the proposed model is significantly better.

Current clinical trials and vaccine development strategies for corona virus disease (COVID-19). (Special Issue: Coronaviruses and COVID-19- Past, Present, and Future.)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has reached global epidemic status claiming more than 319K lives and affecting more than 4.81M people and counting worldwide. Considering the severity of the situation and low recovery rate many research institutions and pharmaceutical industries are rushing to learn more about this new virus and the morbid physiology of this disease with effective diagnostic methods, therapeutic agents and vaccines. Various approaches are highlighted for comparing the possible treatment methods available for COVID-19 some of which are BCG vaccination on COVID-19 and Non-pharmaceutical interventions, drug based clinical trials of Hydroxychloroquine-Azithromycin, chloroquine, lopinavir/ritonavir, ChAdOx1 nCoV-19, Remdesivir, Stem Cell therapy and mesenchymal stromal cell therapy, etc.

Comprehensive Mental Health Facets And Association With Age, Stress And Coping Amid 'The New Normal' Pandemic: How Do Adolescents Differ From Adults? (preprint)

Background: Given varied forms of stressors in the backdrop of the COVID 19 pandemic, adolescents are particularly vulnerable to specific mental health challenges. It pertinent to explore how adolescents differ from adults regarding the comprehensive mental health facets amid the 'new normal, i.e., the duration between the first and second wave of COVID-19 in a developing country like India. The present study aimed to compare the comprehensive mental health facets of adolescents with the adults. Also, it aimed to explore the association of mental health facets with age, perceived stress, coping and impact of pandemic. Methods: The study followed a cross-sectional design with 1,027 participants [456 adolescents; 347 young and 224 middle age-adults] recruited from schools and colleges. The Comprehensive DSM-5 Self-Rated Level 1 Cross-Cutting Symptom Measure, Perceived Stress Scale and Brief COPE Scale were used for assessment. The difference between groups was analyzed using the Chi-Square Test of Independence and correlational analysis was done using Spearman Rank Correlation. Multiple regression analyses were performed for the mental health facets along with bootstrapping method. Results: 33.77% of adolescents, 25.65% of young adults, and 17.41% of middle-aged adults reported that their symptoms started during the pandemic. Compared to adults, the adolescents reported higher depression, anxiety, suicidal ideations, anger, and somatic complaints. Significantly higher adolescent females (39.9%) were found to have sleep disturbances compared to their male counterparts (25.5%). Therefore, it can be observed Adolescents are more clinically vulnerable in most domains. The correlational analysis showed that most mental health domains, except substance use showed moderate-to-low correlations with ‘Impact of COVID’. Perceived stress, impact of COVID, self-distraction, self-blaming were significant independent positive predictors for all the mental health domains except substance use. ‘Age’ was negatively associated with depression anxiety, repetitive thoughts, personality changes, suicidal ideations and memory, and positively associated with ‘substance use’ at low levels. Maladaptive coping was moderately positively correlated with all the mental health domains. Conclusion: It can be observed Adolescents are more clinically vulnerable in most domains. This study provides a comprehensive analysis for assessment and clinical decision-making to combat the mental health problems arising and exacerbating due to the COVID-19 pandemic. The findings will help in planning and implementing an appropriate interventional program, and making policy decisions related to the vulnerable group of adolescents.

Workplace deviance in the virtual workspace

PurposeThis paper aims to discuss ways in which working in the virtual space can give rise to negative norm violating behaviours of employees in organizations. Further, it describes some of the measures that can be taken by organizations to manage such behaviour such that organizational and individual goals are met.Design/methodology/approachThis paper discusses the impact and importance of managing deviant behaviour of employees. Using relevant examples procured from secondary sources, this paper further provides a glance at how organizations can minimize such behaviour and maintain a productive and supportive work environment.FindingsIn today’s scenario when remote working has become a norm, organizations can prevent employees from engaging in deviant behaviour by providing supportive work environment, recalibrating their policies as per the situation and by adopting a top-down approach of communication.Originality/valueThis paper aims to provide a glance at the people-related challenges that the shift to virtual working may have given rise to. It provides measures that organizations can adopt to keep their employees focussed and prevent them from engaging in deviant behaviours.

Analogue discovery of safer alternatives to HCQ and CQ drugs for SAR-CoV-2 by computational design.

COVID-19 outbreak poses a severe health emergency to the global community. Due to availability of limited data, the selection of an effective treatment is a challenge. Hydroxychloroquine (HCQ), a chloroquine (CQ) derivative administered for malaria and autoimmune diseases, has been shown to be effective against both Severe Acute Respiratory Syndrome (SARS-CoV-1) and SARS-CoV-2. Apart from the known adverse effects of these drugs, recently the use of CQ and HCQ as a potential treatment for COVID-19 is under flux globally. In this study, we focused on identifying a more potent analogue of HCQ and CQ against the spike protein of SAR-CoV-2 that can act as an effective antiviral agent for COVID-19 treatment. Systematic pharmacokinetics, drug-likeness, basicity predictions, virtual screening and molecular dynamics analysis (200 ns) were carried out to predict the inhibition potential of the analogous compounds on the spike protein. This work identifies the six potential analogues, out of which two compounds, namely 1-[1-(6-Chloroquinolin-4-yl) piperidin-4-yl]piperidin-3-ol and (1R,2R)-2-N-(7-Chloroquinolin-4-yl)cyclohexane-1,2-diamine interact with the active site of the spike protein similar to HCQ and CQ respectively with augmented safety profile.