Artificial Intelligence: A Next-Level Approach in Confronting the COVID-19 Pandemic.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which caused coronavirus diseases (COVID-19) in late 2019 in China created a devastating economical loss and loss of human lives. To date, 11 variants have been identified with minimum to maximum severity of infection and surges in cases. Bacterial co-infection/secondary infection is identified during viral respiratory infection, which is a vital reason for morbidity and mortality. The occurrence of secondary infections is an additional burden to the healthcare system; therefore, the quick diagnosis of both COVID-19 and secondary infections will reduce work pressure on healthcare workers. Therefore, well-established support from Artificial Intelligence (AI) could reduce the stress in healthcare and even help in creating novel products to defend against the coronavirus. AI is one of the rapidly growing fields with numerous applications for the healthcare sector. The present review aims to access the recent literature on the role of AI and how its subfamily machine learning (ML) and deep learning (DL) are used to curb the pandemic's effects. We discuss the role of AI in COVID-19 infections, the detection of secondary infections, technology-assisted protection from COVID-19, global laws and regulations on AI, and the impact of the pandemic on public life.

In Silico Docking Analysis of Poly Herbal Formulation Aadathodai Kudineer used in Siddha medicine in inhibiting Main Protease and ACE2 Receptor Spike protein SARS-CoV-2

Corona virus disease (COVID-19) is an infectious pandemic disease caused by the newly discovered novel corona virus. World Health Organization has declared the global health emergency due to COVID19 outbreak. Currently, there is no specific treatment or vaccine for fighting against this infectious disease. Aadathodai Kudineer is a drug indicated for Iya Erumal, Kozhai Kattu, Kabasuram. Upon the mortality and severity of the disease COVID19, we tried to identify the possible inhibition of phytocomponents of Aadathodai Kudineer in inhibiting Main Protease and ACE2 Receptor Spike protein SARS-CoV-2 through molecular docking studies. Methodology: In Silico molecular docking analysis was performed for phytocomponents present in the Aadathodai Kudineer formulation for targets main protease and ACE2 Receptor Spike protein, PDB ID: 6LU7 and PDB ID: 2AJF using Autodock tool. ADME properties was also predicted for all the above compounds. Results: Among the 9 active Phytocompounds present in the Aadathodai Kudineer formulation, Lupeol showed high binding affinity with COVID19 main protease and ACE2 receptor which shows the promising contrivance of protease inhibition. The ADME suggested that the formulation is free from toxic. Conclusion: The phytocomponents showed possible affinity towards these targets and has the lead molecules that inhibits COVID19 main protease and ACE2 receptor.