The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2, or SARS-CoV-2, has been ongoing for over two years. The virus spreads easily and is more unpredictable than well-known viruses like the flu, making it important to have reliable combative measures before we fully drop non-vaccine preventive actions, like mask-wearing.Therefore, we used computational protein modeling to investigate the interactions of three nonstructural proteins (abbreviated Nsp) encoded in the viral RNA genome– Nsp3, Nsp5, and Nsp6 – which are involved in the viral life cycle, with human P-type polyamine transporting ATPases ATP13A2 and ATP13A3, whose disease symptoms when mutated mimic certain COVID-19 complications. Understanding these interactions can help shed light on the mechanism of unexpected symptoms seen in COVID-19 and provide an avenue through which to treat infections. Additionally, papain-like protease (PLpro) and 3-chymotrypsin-like protease (3CLpro), which correspond to Nsp3 and Nsp5, respectively, are highly conserved between SARS-CoV and SARS-CoV-2 and thus make good potential drug targets due to their active sites and presumable lower ability to tolerate mutations (reducing the likelihood of treatments becoming ineffective), although the potential effects on the human proteasome would need to be further investigated. In addition, Nsp6 may help the virus evade host defenses by limiting the ability of autophagosomes to deliver viral particles to lysosomes, so limiting its interactions may increase the ability of the host cell to target its viral invader. One compound in particular, Haloperidol, showed promising results; predicted docking (via computational molecular docking software) to Nsp6 alone, as well as to Nsp6-heteroprotein complexes suggested strong binding, indicating a potential strong interaction that could impact the viral protein function and thus the viral life cycle.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:honorstheses-2300 |
Date | 01 January 2022 |
Creators | Huitsing, Jessica |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Honors Undergraduate Theses |
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