Aim: Peptide/protein-based inhalers are excessively used to treat respiratory disorders. The molecular docking was performed for these inhalers including human neutralizing S230 light chain-antibody (monoclonal antibodies [mAbs]), alpha-1-antitrypsin (AAT), short-palate-lung and nasal-epithelial clone-1-derived peptides (SPLUNC1) and dornase-alfa (DA) against spike glycoprotein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to assess their inhibitory activity. Materials & methods: HawkDock was used to dock these biologics against SARS-CoV-2 spike-glycoprotein. Results: Results showed that DA, AAT and mAb were quite active against spike glycoprotein with a binding free energy of -26.35 and -22.94 kcal/mol. Conclusion: mAB and AAT combined with DA can be used in the treatment of coronavirus disease of 2019 as a potential anti-SARS-CoV-2 agent.
Bitcoin was the first cryptocurrency introduced as a cryptographic proof-based electronic payment system in 2009. Till now approximately more than 10,000 digital coins are active in the crypto market. Cryptocurrency is a virtual digital asset that uses cryptography and blockchain technology for transaction verification and records maintenance. Its trading is gaining attention due to volatile behavior, decentralized nature, and liquidity in this digital asset. Trading this digital asset provides anonymity and security in transactions. Groundless fluctuations in its price contribute to making its trade risky. Market Prediction of the cryptocurrency is trending because it can reduce the trade loss risk. Data related to this market is vast and publicly available on the internet. It is nearly impossible to infer the market by simple data analysis. Statistical price prediction approaches are less effective due to the absence of seasonality in cryptocurrency market data. Therefore researchers proposed efficient price prediction techniques utilizing statistical, algorithmic, and neural network-based Machine Learning models. This paper provides a detailed literature survey related to the state-of-the-art Machine learning-based prediction methodologies for the market prediction of the digital asset from 2014 to 2022. This research will categorize, summarize, and review the existing research in cryptocurrency market prediction using Machine Learning classifiers. This paper will benefit researchers to be productive in the right direction in the future.
<div>Severe Acute Respiratory Syndrome (SARS-CoV2) infected about 93 million people and killed over two million worldwide. The disease transmits very quickly, therefore; due to its severity and widespread the World Health Organization has declared this menace as ‘Global Pandemic’. An urgent need was felt to manage this disease through aggressive and efficient research process all over the globe. That’s why drug re-purposing of 212 chemical entities (CEs) against SARS-COV2 was found to be one of the efficient ways in finding new indications of already discovered drugs amisdst of the discovery of a new drug. Results of this study revealed that out of 212 CEs, only Etodolac forms a hydrogen (H)-bond with a relatively low energy and active central fragment, demonstrating more significant interaction with SARS-CoV2 viral proteins. Other CEs exhibit good pharmacokinetics properties with the least acute toxicity through ADMET analysis. We also discovered other therapeutic applications of these CEs through Molinspiration. Etodolac, a non-steroidal anti-inflammatory drug forms H-bonding with 5.6 kcal/mol binding energy with active residues of this receptor. This drug created H-bonding with PHE326 and PRO328, with pyridine group, and was found more suitable to control SARS-CoV2.</div>
<div>Severe Acute Respiratory Syndrome (SARS-CoV2) infected about 93 million people and killed over two million worldwide. The disease transmits very quickly, therefore; due to its severity and widespread the World Health Organization has declared this menace as ‘Global Pandemic’. An urgent need was felt to manage this disease through aggressive and efficient research process all over the globe. That’s why drug re-purposing of 212 chemical entities (CEs) against SARS-COV2 was found to be one of the efficient ways in finding new indications of already discovered drugs amisdst of the discovery of a new drug. Results of this study revealed that out of 212 CEs, only Etodolac forms a hydrogen (H)-bond with a relatively low energy and active central fragment, demonstrating more significant interaction with SARS-CoV2 viral proteins. Other CEs exhibit good pharmacokinetics properties with the least acute toxicity through ADMET analysis. We also discovered other therapeutic applications of these CEs through Molinspiration. Etodolac, a non-steroidal anti-inflammatory drug forms H-bonding with 5.6 kcal/mol binding energy with active residues of this receptor. This drug created H-bonding with PHE326 and PRO328, with pyridine group, and was found more suitable to control SARS-CoV2.</div>
<div>Severe Acute Respiratory Syndrome (SARS-CoV2) infected about 93 million people and killed over two million worldwide. The disease transmits very quickly, therefore; due to its severity and widespread the World Health Organization has declared this menace as ‘Global Pandemic’. An urgent need was felt to manage this disease through aggressive and efficient research process all over the globe. That’s why drug re-purposing of 212 chemical entities (CEs) against SARS-COV2 was found to be one of the efficient ways in finding new indications of already discovered drugs amisdst of the discovery of a new drug. Results of this study revealed that out of 212 CEs, only Etodolac forms a hydrogen (H)-bond with a relatively low energy and active central fragment, demonstrating more significant interaction with SARS-CoV2 viral proteins. Other CEs exhibit good pharmacokinetics properties with the least acute toxicity through ADMET analysis. We also discovered other therapeutic applications of these CEs through Molinspiration. Etodolac, a non-steroidal anti-inflammatory drug forms H-bonding with 5.6 kcal/mol binding energy with active residues of this receptor. This drug created H-bonding with PHE326 and PRO328, with pyridine group, and was found more suitable to control SARS-CoV2.</div>
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