Structural modeling of protein ensembles between E3 RING ligases and SARS-CoV-2: The role of zinc binding domains

Chasapis, Christos T.; Perlepes, Spyros P.; Bjørklund, Geir; Peana, Massimiliano

doi:10.1016/j.jtemb.2022.127089

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Cited by 2 publications

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SARS-CoV-2 and UPS with potentials for therapeutic interventions

Ferdoush,

Abdul Kadir,

Simay Kaplanoglu

et al. 2024

Gene

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SARS-CoV-2 and UPS with potentials for therapeutic interventions

Ferdoush,

Abdul Kadir,

Simay Kaplanoglu

et al. 2024

Gene

View full text Add to dashboard Cite

Pandemic preparedness through genomic surveillance: Overview of mutations in SARS-CoV-2 over the course of COVID-19 outbreak

Najar,

Murphy,

Linde

et al. 2023

Preprint

View full text Add to dashboard Cite

Genomic surveillance is a vital strategy for preparedness against the spread of infectious diseases and to aid in development of new treatments. In an unprecedented effort, millions of samples from COVID-19 patients have been sequenced worldwide for SARS-CoV-2. Using more than 8 million sequences that are currently available in GenBank SARS-CoV-2 database, we report a comprehensive overview of mutations in all 26 proteins and open reading frames (ORFs) from the virus. The results indicate that the spike protein, NSP6, nucleocapsid protein, envelope protein and ORF7b have shown the highest mutational propensities so far (in that order). In particular, the spike protein has shown rapid acceleration in mutations in the post-vaccination period. Monitoring the rate of non-synonymous mutations (Ka) provides a fairly reliable signal for genomic surveillance, successfully predicting surges in 2022. Further, the external proteins (spike, membrane, envelope, and nucleocapsid proteins) show a significant number of mutations compared to the NSPs. Interestingly, these four proteins showed significant changes in Ka typically 2 to 4 weeks before the increase in number of human infections (surges). Therefore, our analysis provides real time surveillance of mutations of SARS-CoV-2, accessible through the project website http://pandemics.okstate.edu/covid19/. Based on ongoing mutation trends of the virus, predictions of what proteins are likely to mutate next are also made possible by our approach. The proposed framework is general and is thus applicable to other pathogens. The approach is fully automated and provides the needed genomic surveillance to address a fast-moving pandemic such as COVID-19.

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Structural modeling of protein ensembles between E3 RING ligases and SARS-CoV-2: The role of zinc binding domains

Cited by 2 publications

References 48 publications

SARS-CoV-2 and UPS with potentials for therapeutic interventions

SARS-CoV-2 and UPS with potentials for therapeutic interventions

Pandemic preparedness through genomic surveillance: Overview of mutations in SARS-CoV-2 over the course of COVID-19 outbreak

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