A Review of Protein Sequences of COVID-19 Using Machine Learning and Deep Learning Approaches - Golwelkar, Anurag; Kothari, Abhay (2023 IEEE International Conference on ICT in Business Industry & Government (ICTBIG), 2023)
The COVID-19 protein sequences are of great interest for the purposes of understanding the behavior of the SARS-CoV-2 virus and devising effective therapeutic treatments. COVID-19 is an illness caused by the SARS-CoV-2 virus. These protein sequences encode the building blocks of viral proteins, which play key roles in viral replication, infection, and interaction with the immune system of the host. The structure of the virus, its functions, and its evolutionary history may be better understood via the study and analysis of these protein sequences. The study on COVID-19 focuses on a number of important proteins, including the nucleocapsid (N) protein, the membrane (M) protein, the spike (S) protein, and the envelope (E) protein. Because it binds to the ACE2 receptor, the spike protein is especially significant because it makes it easier for viruses to enter the cells of their hosts. It is the key target for the production of vaccines as well as the subject of intensive research aimed at understanding its structure, antigenicity, and variations. In order to analyze and understand the COVID- 19 protein sequences, a number of computer methods, such as multiple sequence alignment (MSA), machine learning, and deep learning, are used. This contributes to the process of determining prospective therapeutic targets and creating antiviral medicines. In addition, research into the protein sequences allows for a better understanding of the influence that mutations have on the behavior, transmissibility, and immune evasion of viruses. Researchers are able to monitor the appearance of novel viral variants and evaluate the possible influence these variants may have on diagnostics, vaccines, and treatment techniques if they keep track of the genetic differences that occur in viral proteins.