Identification of characteristics frequency and hot-spots in protein sequence of COVID-19 disease

• Published in: Biomedical signal processing and control 2022-09, Vol.78, p.103909-103909, Article 103909
• Main Authors: Pathak, Vikas, Nanda, Satyasai Jagannath, Joshi, Amit Mahesh, Sahu, Sitanshu Sekhar
• Format: Article
• Language: English
• Subjects: COVID-19; Hot-spots identification; IIR digital filter; SARS CoV2
• ISSN: 1746-8094; 1746-8108; 1746-8094
• DOI: 10.1016/j.bspc.2022.103909

COVID-19 has threatened the whole world since December 2019 and has also infected millions of people around the globe. It has been transmitted through the SARS CoV-2 virus. Various proteins of the SARS CoV-2 virus have an important role in its interaction with human cells. Specifically, the interaction of S-protein with human ACE-2 protein helps in entering of SARS CoV-2 virus into a 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 for new variants of COVID-19 disease. An attempt has been made in this paper for understanding this interaction by finding the characteristics frequency of SARS-related protein families using the resonance recognition model (RRM). Hardware implementation of Bandpass notch (BPN) lattice IIR filter system architecture is also carried out, which is used for hot-spots identification in SARS CoV-2 proteins. Various signal processing techniques like retiming, pipelining, etc. are explored for performance improvement. Synthesis of proposed BPN filter system has been done using Xilinx ISE EDA tool on Zynq-series (Zybo-board) FPGA family. It is found that retimed and pipelined architecture of hardware-implemented 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. •Proposed BPN lattice IIR filter architecture for hot-spots identification in SARS CoV-2.•Hot-spot identification is useful for vaccine development of new variants of COVID-19.•Synthesis is done using Xilinx ISE and implemented on Zynq-series FPGA.•Experimentation is carried out on five proteins and identified hot-spots are reported.•Comparative analysis of proposed filter is done with MATLAB simulation.