Identification of Characteristics Frequency and Hot-Spots in Protein Sequence of COVID-19 Disease

The COVID-19 has threatened the whole world since December, 2019 and has also infected millions of the peoples around the globe which is transmitted through SARS CoV-2 virus. Various proteins of SARS CoV-2 virus have important role in its interaction with human cells. Specifically, interaction of S-protein with human ACE-2 protein helps in entering of SARS CoV-2 virus into human cell. This interaction take-place at some specific amino-acid locations called as hot-spots. Understanding of this interaction is helpful for drug designing and vaccine development of COVID-19 disease. An attempt has been made in this paper for understanding of this interaction by finding the characteristics frequency of SARS related protein-families using resonance recognition model (RRM) and than using the BPN lattice IIR filter system for hot-spots identification in those proteins. Various signal processing techniques like retiming, pipelining etc. are explored for performance improvement. It is found that retimed and pipelined architecture of BPN lattice IIR filter based hot-spots detection system improves the speed (computational time) by 14 to 31 times for different SARS CoV2 related proteins as compared to its MATLAB simulation with similar functionality.