Interaction of SCoV-2 NSP7 or NSP8 alone may cause constriction of the RNA entry channel in NSP12: Implications for novel RdRp inhibitor drug discovery (preprint)

RNA-dependent RNA polymerase (RdRP) is a critical component of the RNA virus life cycle, including SCoV-2. Among the Coronavirus-encoded proteins, non-structural protein 12 (NSP12) exhibits polymerase activity in collaboration with one unit of NSP7 and two units of NSP8, constituting the RdRp holoenzyme. While there is abundant information on SCoV-2 RdRp-mediated RNA replication, the influence of interplay among NSP12, NSP7, and NSP8 on template RNA binding and primer extension activity remains relatively unexplored and poorly understood. Here, we recreated a functional RdRp holoenzyme in vitro using recombinant SCoV-2 NSP12, NSP7, and NSP8, and established its functional activity. Subsequently, molecular interactions among the NSPs in the presence of a variety of templates and their effects on polymerase activity were studied, wherein we found that NSP12 alone exhibited notable polymerase activity that increased significantly in the presence of NSP7 and NSP8. However, this activity was completely shut down, and the template RNA primer complex was detached from NSP12 when one of the to cofactors was present. Through computational analysis, we found that the template RNA entry channel was more constricted in the presence of one of the two cofactors, which was relatively more constricted in the presence of NSP8 compared to that in the presence of NSP7. In conclusion, we report that NSP7 and NSP8 together synergise to enhance the activity of NSP12, but antagonise when present alone. Our findings have implications for novel drug development, and compounds that obstruct the binding of NSP7 or NSP8 to NSP12 can have lethal effects on viral RNA replication.

Interruption of BCG Therapy for NMIBC During COVID-19 Crisis, Dilemma in Its Continuation: a Review of Available Evidence and Suggested Management Strategies.

The COVID-19 disease, caused by SARS-CoV-2 virus, has been one of the worst pandemics ever to hit the human mankind. Undoubtedly the start of the second wave of COVID-19 has literally ripped apart the hearts of millions of people. Cancer patients have been left of the beaten track to their fate, with no access to treatments. Intravesical BCG instillation is the standard of care for patients with non-muscle invasive bladder cancer (NMIBC). Several patients were in the middle of their treatment regimen when this pandemic struck. As slowly the word is recuperating from concussion effect of this pandemic and routine health services are being restored, uro-oncologist will face a unique scenario with respect to intravesical BCG therapy i.e., whether to restart the course of BCG therapy or to continue course from where it was interrupted. There are no studies in literature to directly answer this peculiar question and to resolve this dilemma. So, we in this review article propose to explore the literature for the most appropriate therapeutic regimen for these patients with interruption of intravesical BCG therapy. We plan to divide the patients with interruption to BCG therapy into the following three groups:Group 1: Patients who had interruption during the induction period.Group 2: Patients who completed the induction course but maintenance course could not be started.Group 3: Patients who had interruption during maintenance phase of BCG therapy. We will compile the recent recommendations by NCCN, AUA, and EAU for the administration of intravesical BCG in non-muscle invasive bladder cancer. We herein want to review the literature to propose the most appropriate strategy, its safety profile for these subsets of patients. Supplementary Information: The online version contains supplementary material available at 10.1007/s13193-023-01742-8.

A prospective and observational study to evaluate short-term adverse event following immunization of COVID-19 vaccination

Background: COVID-19 severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was declared Pandemic by the World Health Organization on January 30, 2020. Vaccination represents the best possibility to resolve this pandemic. The current global challenge is the immunization against the SARS-CoV-2. However, the adverse events following immunization (AEFI) of the corona vaccine remains unclear. Aim and Objectives: This observational study aims to represent an accountable data of the AEFI between Covaxin and Covishield in North Indian population. Materials and Methods: The hospital-based prospective and observational study was employed from January 2021 to December 2021 for detecting and monitoring of AEFI in adults. All population vaccinated either covishield or covaxin with both doses were enrolled in the study as targeted population. Post-vaccination vaccinated population were telephonic follow-up with prior consent. Results: A total of 1015 vaccinated individuals were included in this study for assessment of AEFI. After statistical analysis of AEFI between both vaccination at 24 h P = 0.13, 3-7 days 0.4 and complete AEFI P = 0.06 observed. There is no association that was found significant P < 0.05 with the incidence of AEFI. Conclusion: The short-term outcome has not attribute any serious AEFI. This study demonstrated that both vaccines were well-tolerated and safe in generalized population.

Repurposing immune boosting and anti-viral efficacy of Parkia bioactive entities as multi-target directed therapeutic approach for SARS-CoV-2: exploration of lead drugs by drug likeness, molecular docking and molecular dynamics simulation methods.

The COVID-19 pandemic has caused adverse health (severe respiratory, enteric and systemic infections) and environmental impacts that have threatened public health and the economy worldwide. Drug repurposing and small molecule multi-target directed herbal medicine therapeutic approaches are the most appropriate exploration strategies for SARS-CoV-2 drug discovery. This study identified potential multi-target-directed Parkia bioactive entities against SARS-CoV-2 receptors (S-protein, ACE2, TMPRSS2, RBD/ACE2, RdRp, MPro, and PLPro) using ADMET, drug-likeness, molecular docking (AutoDock, FireDock and HDOCK), molecular dynamics simulation and MM-PBSA tools. One thousand Parkia bioactive entities were screened out by virtual screening and forty-five bioactive phytomolecules were selected based on favorable binding affinity and acceptable pharmacokinetic and pharmacodynamics properties. The binding affinity values of Parkia phyto-ligands (AutoDock: -6.00--10.40 kcal/mol; FireDock: -31.00--62.02 kcal/mol; and HDOCK: -150.0--294.93 kcal/mol) were observed to be higher than the reference antiviral drugs (AutoDock: -5.90--9.10 kcal/mol; FireDock: -35.64--59.35 kcal/mol; and HDOCK: -132.82--211.87 kcal/mol), suggesting a potent modulatory action of Parkia bioactive entities against the SARS-CoV-2. Didymin, rutin, epigallocatechin gallate, epicatechin-3-0-gallate, hyperin, ursolic acid, lupeol, stigmasta-5,24(28)-diene-3-ol, ellagic acid, apigenin, stigmasterol, and campesterol strongly bound with the multiple targets of the SARS-CoV-2 receptors, inhibiting viral entry, attachment, binding, replication, transcription, maturation, packaging and spread. Furthermore, ACE2, TMPRSS2, and MPro receptors possess significant molecular dynamic properties, including stability, compactness, flexibility and total binding energy. Residues GLU-589, and LEU-95 of ACE2, GLN-350, HIS-186, and ASP-257 of TMPRSS2, and GLU-14, MET-49, and GLN-189 of MPro receptors contributed to the formation of hydrogen bonds and binding interactions, playing vital roles in inhibiting the activity of the receptors. Promising results were achieved by developing multi-targeted antiviral Parkia bioactive entities as lead and prospective candidates under a small molecule strategy against SARS-CoV-2 pathogenesis. The antiviral activity of Parkia bioactive entities needs to be further validated by pre-clinical and clinical trials.

Homeopathic Medicines in Second Wave of COVID-19: Prognostic Factor Research.

BACKGROUND/OBJECTIVE: The clinical profile and course of COVID-19 evolved perilously in a second wave, leading to the use of various treatment modalities that included homeopathy. This prognostic factor research (PFR) study aimed to identify clinically useful homeopathic medicines in this second wave. METHODS: This was a retrospective, multi-centred observational study performed from March 2021 to May 2021 on confirmed COVID-19 cases who were either in home isolation or at COVID Care Centres in Delhi, India. The data were collected from integrated COVID Care Centres where homeopathic medicines were prescribed along with conventional treatment. Only those cases that met a set of selection criteria were considered for analysis. The likelihood ratio (LR) was calculated for the frequently occurring symptoms of the prescribed medicines. An LR of 1.3 or greater was considered meaningful. RESULTS: Out of 769 confirmed COVID-19 cases reported, 514 cases were selected for analysis, including 467 in home isolation. The most common complaints were cough, fever, myalgia, sore throat, loss of taste and/or smell, and anxiety. Most cases improved and there was no adverse reaction. Certain new symptoms, e.g., headache, dryness of mouth and conjunctivitis, were also seen. Thirty-nine medicines were prescribed, the most frequent being Bryonia alba followed by Arsenicum album, Pulsatilla nigricans, Belladonna, Gelsemium sempervirens, Hepar sulphuris, Phosphorus, Rhus toxicodendron and Mercurius solubilis. By calculating LR, the prescribing indications of these nine medicines were ascertained. CONCLUSION: Add-on use of homeopathic medicines has shown encouraging results in the second wave of COVID-19 in integrated care facilities. Further COVID-related research is required to be undertaken on the most commonly prescribed medicines.

Combating the Pandemic with ICT-Based Learning Tools and Applications: A Case of Indian Higher Education Platforms

With the limitations imposed by COVID-19 pandemic, educational regulatory bodies in India recommended a number of online education portals to support higher education. Present work undertakes a detailed study on these recommended platforms and presents a comparative analysis based on the relevant features. 'SWAYAM' a widely popular and emphasized Indian MOOC platform has been compared with the other popular e-learning platforms of the international market. The study revealed that e-learning platforms vary in terms of offerings such as: method of dissemination of knowledge, target audiences, fee, target audiences, etc. Also, in terms of user base, courses offered, and certificates offered, 'SWAYAM' has to work a lot to compete with the international peers. Finally, SWOC analysis was carried out to present the threats and opportunities associated with recommended e-learning portals. The work will be profoundly helpful to frame the comprehensive education policies to meet the stakeholder's expectations and lead to the innovation of educational development.

Enablers for resilience and pandemic preparedness in food supply chain

The recent COVID-19 pandemic has caused enormous disruptions to supply chain (SCs). Border restrictions forced countless businesses to close either permanently or temporarily. However, the food industry is an essential sector that needs to be operational during a pandemic. Although the food industry has proactively worked towards fulfilling human needs, the food supply chain (FSC) faced numerous challenges, forcing SC managers to rethink their business strategy to cater to consumer demands effectively. In a pandemic situation, manufacturing operations need to repurpose and adapt to produce different high-demand products. Resilience initiatives help fight disruption phases in an uncertain environment by building capacity to resist and recover to a better position. This study identifies 14 key enablers to develop a resilient FSC and reveals the most significant enablers in India. We used a hybrid Delphi-interpretive structural modeling (ISM) and Fuzzy decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) methodology to achieve these goals. The Delphi technique identified essential enablers, while the ISM analyzed the interrelationship among enablers and level of importance in a hierarchical structural model. Finally, the Fuzzy-DEMATEL categorized the enablers into the cause-effect group. This study helps SC decision-makers recognize the enablers and the contextual and causal relationships to improve resilience initiatives. It also helps them repurpose their manufacturing operations and shift to other highly required and high-demand production.

Implicit, Intrinsic, Extrinsic, and Host Factors Attributing the COVID-19 Pandemic. Part 3- Host Factor GDP: A Systematic Analysis (preprint)

Despite successful large laboratory studies, the progression of novel coronavirus disease 2019 (COVID-19) is still underway. As with a short time, COVID-19 escalated into a 'global pandemic', emphasized a special attention for ‘global data analysis’. Using a large global dataset (n=166), we demonstrate that COVID-19 distribution remained particularly unequal across the world's four income groups and global percentage of infectivity including deaths fairly suppressed from high (18.44% e.g. Estonia- 2385 deaths), upper middle (4.44% e.g. Mauritius- 934 deaths), lower middle (2.64% e.g. Timor Leste- 129 deaths) to low-income countries (0.23% e.g. Burundi- 38 deaths). All above reported 4 countries have almost similar population (1.2M-1.3M). Both deaths and infectivity differences between high and upper middle, or upper middle and lower middle, or lower middle and low provides fair visibility in unbiased analyses. Nonetheless, a significant linear relationship (r= 0.72 ± 0.02) over a long 18 months between GDP and COVID-19 infection by country entails risk of contracting COVID-19 (Mar 2020: t-test one-tail/two-tail p < 0.05, F-test one-tail p< 0.05, df= 165, F= 449.03, r2= 0.732, r2 aj= 0.731 and SS=63867700637). Our finding connects health areas that shape unequal distribution of COVID-19 through the resident functional alleles, for example HLA-A*01:01 and HLA-B*46:01 alleles for increased risk in high income countries. The evidence-based views laid foundation for unusual heterogenic immune responses among different human habitats. The ancient evolution theory by natural selection also underlies high susceptibility in high-income countries, due to no adaptive challenges for the lives and improved living standards over the years.

THERMOD: Development of a Cost Effective Solution for Integrated Sensing and Logging.

With the outbreak of the Covid-19 pandemic, vaccination has become mandatory. Further, for effective results, the vaccines should be stored within the recommended temperature range, typically between 2°C to 8°C, transported safely without any mishandling and temperature excursion. In order to assure vaccine potency, it is essential to have detailed information on the entire temperature data recorded at user-defined intervals. In this paper, we develop functionality interaction to bring different sensors, memory, and processing units to an integrated platform, providing a compact, power-efficient, and low-cost commercial TemperatuRE, Humidity, and MOvement Data-logger (THERMOD). Moreover, the THERMOD hardware is packed with interactive algorithms that address the aforementioned concerns and log the real-time temperature and jerks (3-dimensional movement) encountered throughout the journey, and the logged data can be retrieved by plugging THERMOD into the host computer/laptop. The THERMOD hardware formulation and algorithm embedding have been done in the institution lab, which enables end-to-end storage and monitoring. Also, the proposed design is built with the defined standards by health organizations, e.g., WHO. Further, to validate the proficiency of the proposed design, comparative analysis has been done; a) a cost analysis has been done to state the cost efficiency of the proposed solution, b) real-time power performance graphs have been plotted which depict that THERMOD outperforms the existing solutions. Moreover, a number of experiments were performed for the validation of the proposed design.

Automatic diagnosis of COVID-19 from Chest X-ray images using transfer learning-based deep features and machine learning models (preprint)

The novel Coronavirus, declared as a pandemic by WHO, has caused a health crisis and disrupted the daily course of the people globally. The effectiveness of Chest X-ray (CXR) in the differentiation of COVID from non-COVID has exhorted us to propose a diagnostic model based on deep features. This paper proposes a diagnostic framework to diagnose COVID-19 from Chest X-rays (CXR). Further Grad-CAM visualizations are shown to get a visual interpretation for the predicted images. We validated the performance of the proposed diagnostic model using the area under the curve (AUC), accuracy, precision, recall, F1-score and geometric mean (G-mean). Few popular machine learning models such as random forest, dense neural network, support vector machine (SVM), twin SVM (TWSVM), extreme learning machine (ELM), random vector functional link (RVFL) and kernel ridge regression (KRR) have been selected for diagnosing the COVID cases. The deep features are extracted by transfer learning. Grad-CAM visualizations are presented for the predicted images. We have achieved the best AUC score of 0.98 on TWSVM classifier on the feature vector extracted by ResNet50 architecture. The feature vector extracted from ResNet50 outperforms all other CNN architecture rank wise based on AUC. The experimental outcome indicates the efficiency of the proposed diagnostic framework.

EFFECT OF RAAS INHIBITORS ON OUTCOMES OF HOSPITALIZED PATIENTS WITH SARS-COV-2 INFECTION

B Conclusions: b Patients on RAAS inhibitors prior to hospitalization for SARS-CoV-2 infection had higher mortality and complications than those not on these medications. B Introduction: b The aim of our study was to determine the effect of prior use of renin-angiotensin-aldosterone system (RAAS) inhibitors on mortality and outcomes in hospitalized patients with laboratory-confirmed SARS-CoV-2 infection. [Extracted from the article] Copyright of Critical Care Medicine is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A nationwide cross-sectional study to assess the impact of COVID-19 on surgical residency programs in India.

BACKGROUND: The COVID-19 pandemic with its plenitude of hardships has been a challenge for residents in training. Besides the fear of contracting the disease, the complete reconfiguration of hospital services has severely affected the surgical residency programs across India. The current study highlights the lacunae that have arisen in the residency programs and design appropriate solutions to reframe the remaining part of the surgical training. MATERIALS AND METHODS: The present study is an observational study based on a questionnaire survey done in November 2020 aimed at gauging the mood and perspective of residents across India pursuing surgical residency programs on how the pandemic has impacted various domains of their residency namely surgical training, clinical skills, research, academic curriculum, and mental health. The analysis was performed using an Internet-based program. RESULTS: Seventy-eight percent of residents felt that they have lost crucial months of surgical training. Impact on clinical skills was reported by 73.9% of residents. Almost half of the residents (49.1%) believed that there has been a definite increase in research activities and 81.7% believed that the academic curriculum was affected during the past 6 months. Furthermore, 86% of respondents admitted to have had a profound impact on their mental health as a result of the pandemic. CONCLUSION: Formulating reform policies in the current residency programs is paramount to train the current and future generation of surgeons. Whereas personal safety and wellness of the residents is paramount during these times, residency training via digital medical education and various other innovative ways needs to continue.

METABOLIC SYNDROME AND ARDS IN COVID-19

B Conclusions: b MetS, diagnosed by the clustering of obesity, prediabetes/DM, HTN, and dyslipidemia, is associated with significantly increased mortality and ARDS in a global population of hospitalized COVID-19 patients. B Introduction/Hypothesis: b Little is known about metabolic syndrome (MetS) and ARDS in COVID-19. However, patients from non-US hospitals had significantly higher hospital mortality as compared with US hospitals (24.5% vs 15.7%, aOR 1.58 [CI 1.41-1.77]) with similar findings noted when patients were stratified by MetS (34.1% vs 21.3%, aOR 1.49 [CI 1.08-2.06]). [Extracted from the article] Copyright of Critical Care Medicine is the property of Lippincott Williams & Wilkins and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Feasibility and usefulness of online virtual training of urology residents in times of COVID-19: A single-center experience and an evidence-based strength, weakness, opportunity, and threat analysis.

BACKGROUND: The COVID-19 disease has resulted in an almost complete shutdown of all services worldwide. Hospitals continued to provide emergency services and treatment for COVID-19 disease. Teaching hospitals like ours had another responsibility at hand; training of our surgical residents. Not allowing this pandemic to take away months of training, we resorted to online virtual training programs, for continuing academic activities. After having conducted thirty such sessions, we took feedback from the participating students and faculty members to evaluate the usefulness of this new initiative and identify the lacunae that needed to be addressed. MATERIALS AND METHODS: The initial twenty classes were held on the GoTo Meeting ® online platform, whereas the last ten were conducted using the Google Meet application. A 20-item questionnaire covering four broad domains of general perception, feasibility, knowledge gained, and drawbacks was circulated, and 19 responses were registered anonymously. Strength, weakness, opportunity, and threat analysis was done based on the responses received. RESULTS: About 89.5% of the participants believed that online classes were the ideal platform for continuing education and 84.2% of the participants were overall satisfied with the whole exercise. The Achilles' heel was the availability of a good Internet connection, and the major lacunae were the poor quality of video and audio transmission. Seventy-four percent of the participants wanted to continue online training in the future too, whereas 26% wanted to revert to the traditional face-to-face teaching. CONCLUSION: Online virtual training classes are an effective and feasible alternative to traditional teaching in times such as these, which demanded strict social distancing. It naturally lacked the warmth and personal touch of the traditional teaching classes, but it allowed us to continue teaching our residents and also prepare them to face the biggest menace of all times.

SARS-CoV-2 cell receptor gene ACE2 -mediated immunomodulation in breast cancer subtypes.

The recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has impacted the world severely. The binding of the SARS-CoV-2 virus to the angiotensin-converting enzyme 2 (ACE2) and its intake by the host cell is a necessary step for infection. ACE2 has garnered widespread therapeutic possibility as it is entry/interactive point for SARS-CoV-2, responsible for coronavirus disease 2019 (COVID-19) pandemic and providing a critical regulator for immune modulation in various disease. Patients with suffering from cancer always being on the verge of being immune compromised therefore gaining knowledge about how SARS-CoV-2 viruses affecting immune cells in human cancers will provides us new opportunities for preventing or treating virus-associated cancers. Despite COVID-19 pandemic got center stage at present time, however very little research being explores, which increase our knowledge in context with how SARS-CoV-2 infection affect cancer a cellular level. Therefore, in light of the ACE-2 as an important contributor of COVID-19 global, we analyzed correlation between ACE2 and tumor immune infiltration (TIL) level and the type markers of immune cells were investigated in breast cancer subtypes by using TIMER database. Our findings shed light on the immunomodulatory role of ACE2 in the luminal A subtype which may play crucial role in imparting therapeutic resistance in this cancer subtype.

Heat-based N95 mask decontamination and reuse in a large hospital setting (preprint)

The shortage of N95 masks have spurred efforts on developing safe and scientifically-validated decontamination and reuse protocols that are easily scalable and universally applicable even in low-resource settings. We report on the development and implementation of a heat-based N95 mask decontamination system in a large hospital setting (Tata Memorial Hospital, Mumbai, India) with over 8000 N95 masks from about 1400 individual users decontaminated and in reuse till date. We describe the challenges and constraints in choosing a proven, scalable, and easy-to-implement decontamination solution. We discuss the heat treatment and particle filtration efficiency measurement experiments done to validate a decontamination treatment protocol at a target temperature of 70{degrees}C for a duration of 60 minutes, and the scaling up of this method using a standard hot drying cabinet at the hospital. The logistics of ensuring optimal utilization of the decontamination facility without compromising on basic safety principles are detailed. Our method relies on equipment available in standard hospitals, is simple to set-up, scalable, and can be easily replicated in low-resource settings. We further believe such limited reuse strategies, even in times of abundant N95 mask availability, would not only be cost-saving but also be environmentally responsible in reducing the amount of medical waste.

Modelling of Covid-19 cases in India using Regression and Time Series models (preprint)

In this article, we analyze the growth pattern of Covid-19 pandemic in India from March 4th to July 11th using regression analysis (exponential and polynomial), auto-regressive integrated moving averages (ARIMA) model as well as exponential smoothing and Holt-Winters smoothing models. We found that the growth of Covid-19 cases follows a power regime of (t^2,t..) after the exponential growth. We found the optimal change points from where the Covid-19 cases shift their course of growth from exponential to quadratic and then from quadratic to linear. After that, we saw a sudden spike in the course of the spread of Covid-19 and the growth moved from linear to quadratic and then to quartic, which is alarming. We have also found the best fitted regression models using the various criteria such as significant p-values, coefficients of determination and ANOVA etc. Further, we search the best fitting ARIMA model for the data using the AIC (Akaike Information Criterion) and provide the forecast of Covid-19 cases for future days. It was noticed that the ARIMA model fits better the Covid-19 cases for small regions. ARIMA (5, 2, 5) and ARIMA (5, 2, 3) are the best possible models for modeling Covid-19 cases for March 4th to July 10th and June 1th to July 10th, respectively.

Phytocompounds of Rheum emodi, Thymus serpyllum and Artemisia annua inhibit COVID-19 binding to ACE2 receptor: In silico approach (preprint)

COVID-19 has been declared as global epidemic and currently there is no drug/vaccine available to treat COVID-19. All over the world, several studies are being conducted to discover the antiviral drugs against COVI-19. Traditional medicinal plants have long history to treat viral infections. We adopted in silico approach to find out if unique phytocompounds such as emodin (Rheum emodi), thymol and carvacrol (Thymus serpyllum) and artemisnin (Artemisia annua) could physically bind COVID-19 target proteins such as SARS-CoV-2 spike glycoprotein (PDB ID: 6VXX), SARS-CoV-2 spike ectodomain structure (PDB ID: 6VYB), and SARS coronavirus spike receptor-binding domain (PDB ID: 2AJF) and in turn preventCOVID-19 binding to the host receptor ACE2. Since Chloroquine (a standard antimalarial drug) has been looked as potential therapy against COVID-19, we also compared the binding of chloroquine and plant origin artemisnin antimalarial drug for its interaction with 6VXX, 6VY and 2AJF. Molecular docking studies using AutoDock/Vina software revealed that among all the phytocompounds artemisinin showed best binding affinity with 6VXX, 6VYB and 2AJF with Etotal -10.5 KJ mol-1, -10.3 KJ mol-1, and -9.1 KJ mol-1 respectively.  Whereas emodin, carvacrol and thymol binds with 6VXX, 6VYB and 2AJF with Etotal -6.4, -6.8, -6.9 KJ mol-1, -8.8, -6.8, -7.4 KJ mol-1, and -6.9, -7.4, -7.2 respectively. Similarly, with Autodock/Vina chloroquine showed less binding affinity with 6VXX (-5.6 KJ mol-1), 6VYB (-5.9 KJ mol-1) and 2AJF (-6.4 KJ mol-1) as compared to all phytocompounds. Toxicity prediction showed non-toxicity and non-carcinogen by admetSAR and PROTOX‑II software.