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Polimery/Polymers ; JOUR(7-8):355-374, 67.
Article in English | Scopus | ID: covidwho-2090963


Because of the present pandemic researchers are seeking for phytocandidates that can inhibit or stop SARS-CoV-2. The main protease (Mpro) of SARS-CoV-2 and spike glycoprotein (S) are both suppressed by bioactive compounds found in plants that work by docking them together. The Mpro proteins 6LU7 (complex with an inhibitor N3) and 5C3N (space group C2221) were employed in docking research. PyRx and AutoDock Vina software were used as docking engine. 22 identified phytoconstituents were selected from IMPPAT, a manually curated database, on the basis of their antiviral effects. Docking studies showed that phytoconstituents β-amyrin (-8.4 kcal/mol), withaferin A (-8.3 kcal/mol), oleanolic acid (-7.8 kcal/mol), and patentiflorin A (-8.1 kcal/mol) had the best results against 5C3N Mpro protein whereas kuwanon L (-7.1 kcal/mol), β-amyrin (-6.9 kcal/mol), oleanolic acid (-6.8 kcal/mol), cucurbitacin D (-6.5 kcal/mol), and quercetin (-6.5 kcal/mol) against 6LU7 Mpro protein. All the compounds were examined for their ADMET characteristics using SwissDock. Present research reports that the phytoconstituents along with docking score will be helpful for future drug development against Covid-19. © 2022 Industrial Chemistry Research Institute. All rights reserved.

1st International Conference on Advances in Computing and Future Communication Technologies, ICACFCT 2021 ; : 33-38, 2021.
Article in English | Scopus | ID: covidwho-2018770


With the periodic rise and fall of COVID-19 and countries being inflicted by its waves, an efficient, economic, and effortless diagnosis procedure for the virus has been the utmost need of the hour. Amongst the infected subjects, the asymptomatic ones need not be entirely free of symptoms caused by the virus. They might not show any observable symptoms like the symptomatic subjects, but they may differ from uninfected ones in the way they cough. These differences in the coughing sounds are minute and indiscernible to the human ear, however, these can be captured using machine learning models. In this paper, we present a deep learning approach to analyze the acoustic dataset provided in Track 1 of the DiCOVA 2021 Challenge containing cough sound recordings belonging to both COVID-19 positive and negative examples. To perform the classification we propose a ConvNet model. It achieved an AUC score percentage of 72.23 on a blind test set provided in the challenge for an unbiased evaluation of the models. Moreover, the ConvNet model incorporated with Data Augmentation further increased the AUC score percentage from 72.23 to 87.07. It also outperformed the DiCOVA 2021 Challenge's baseline model by 23% thus, claiming the top position on the DiCOVA 2021 Challenge leaderboard. This paper proposes the use of Mel Frequency Cepstral Coefficients as the input features to the proposed model. © 2021 IEEE.

International Journal of Current Research and Review ; 13(3):113-119, 2021.
Article in English | Scopus | ID: covidwho-1083469


Introduction: A novel threat to mankind occurred in December 2019 which was an outbreak of infection caused by a novel coronavirus (SARS-CoV-2 or 2019-nCoV). The infection was first developed in Wuhan, China, and has affected more than 200 countries around the world till now. Objective: The present study aims to assess the knowledge related to coronavirus disease (COVID-19), risk perception and preventive behaviours among the Pharmacy students in a part of India approximately 3 months after the onset of this outbreak in India. Methods: This survey was conducted from 2nd to 5th of September 2020 with Indian Pharmacy students (1st to 4th year). The knowledge, self-reported preventive behaviours and risk perceptions of COVID-19 were assessed using an online questionnaire. A total of 21 questions were there in the questionnaire in which 14 questions were about knowledge related to COVID-19, 4 items regarding preventive behaviours and 3 about risk perception. Results: A total of 268 participants completed the questionnaire. The participants were under the age group of 15-30 years. A high level of disease-related knowledge was found in the participants (77.66%). On an average 96.1% of participants were practising preventive behaviours. The aggregate score of items in risk perception section was found to be in the moderate range i.e., 5.38 out of 8. A significant negative correlation was obtained between risk perception and preventive behaviours. Conclusion: The trajectory and severity of this outbreak are very high, therefore, effective treatment against this global threat is required to be developed as early as possible. In the present study, a high level of disease-related knowledge and preventive behaviours were observed among the participants with a moderate level of risk perception. © IJCRR.