Bioinformatics Helps with Drug Discovery for COVID-19 Treatment

Yicheng Lou, Keyi Shen, Shihhao Fang, Zelu Huang, Yan Lin

2022

Abstract

This paper is a review of the process of drug discovery for COVID-19 treatment based on spike protein. This work discussed three fundamental approaches: dynamic programming, progressive alignment construction, and consensus method. Then, the paper used the amino acid sequences (of viral proteins) downloaded from the UniProt database and applied Clustal Omega (an alignment tool) to conduct multiple alignments on four spike proteins: SARS-CoV, SARS-CoV-2, MERS-CoV, HCoV-NL63. A brief phylogenetic analysis was also conducted to support the predicted alignment results. After that, the paper includes a review of applications of drug discovery based on spike protein alignment—both within the coronaviridae species and with HIV.

Paper Citation

in Harvard Style

Lou Y., Shen K., Fang S., Huang Z. and Lin Y. (2022). Bioinformatics Helps with Drug Discovery for COVID-19 Treatment. In Proceedings of the 4th International Conference on Biomedical Engineering and Bioinformatics - Volume 1: ICBEB, ISBN 978-989-758-595-1, pages 1104-1111. DOI: 10.5220/0011378100003443

in Bibtex Style

@conference{icbeb22,
author={Yicheng Lou and Keyi Shen and Shihhao Fang and Zelu Huang and Yan Lin},
title={Bioinformatics Helps with Drug Discovery for COVID-19 Treatment},
booktitle={Proceedings of the 4th International Conference on Biomedical Engineering and Bioinformatics - Volume 1: ICBEB,},
year={2022},
pages={1104-1111},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011378100003443},
isbn={978-989-758-595-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Biomedical Engineering and Bioinformatics - Volume 1: ICBEB,
TI - Bioinformatics Helps with Drug Discovery for COVID-19 Treatment
SN - 978-989-758-595-1
AU - Lou Y.
AU - Shen K.
AU - Fang S.
AU - Huang Z.
AU - Lin Y.
PY - 2022
SP - 1104
EP - 1111
DO - 10.5220/0011378100003443