Molecular dynamics and intrinsic disorder analysis of the SARS-CoV-2 Nsp1 structural changes caused by substitution and deletion mutations

ABSTRACT

SARS-CoV-2 non-structural protein 1 (Nsp1) is a virulence factor that inhibits the translation of host mRNAs and interacts with viral RNA. To date, hundreds of mutations (base substitutions, deletions, and insertions) have been reported in SARS-CoV-2 Nsp1. Despite the relevance of Nsp1, a few studies have been conducted to understand the effect of those mutations on Nsp1 structure and function. In this study, the effects of the most frequent mutations were investigated using molecular dynamics simulations. We found that several mutations profoundly affect the local intrinsic disorder predisposition, with most deletions increasing disorder propensity and replacement mutations inducing variable effects. We found that deletions Δ80–90 and Δ156–158 destabilise the protein structure. For example, the Δ156–158 cause a higher root-mean-square deviation (RMSD) and R_g values than those of the wild-type of SARS-CoV-2 Nsp1. We also found that the SARS-CoV-2 Nsp1 is slightly more disordered than its counterpart from SARS-CoV. A better understanding of the complexity and dynamic nature of interactions between intrinsically disordered segments of Nsp1 and ribosome subunits might help develop novel therapeutic countermeasures against the SARS-CoV-2 variants.

Highlights

1. Multiple mutations have been found in the N/C-termini of the SARS-CoV-2 Nsp1.

2. The effects of deletions are greater than substitutions on SARS-CoV-2 Nsp1.

3. Δ80–90 and Δ156–158 destabilise the protein structure and may increase the SARS-CoV-2 virulence.

4. F157S, E159D, L173P, and R175H mutations affect the structure of the SARS-CoV-2 Nsp1 and may cause increased infectivity.

5. The most disorder-promoting mutations were F157L and M174 K, whereas E159D and E159 K were the most order-promoting.

KEYWORDS:

• SARS-CoV-2
• Nsp1
• mutations
• MD simulation
• intrinsically disordered regions

Acknowledgements

The support and resources from the Center for High Performance Computing at the Shahid Beheshti University of Iran are gratefully acknowledged. We would also like to thank all the researchers who have kindly shared genomes in public databases.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research has been conducted using the research credits of Shahid Beheshti University, G.C., Tehran, Iran (grant number; SAD/600/1451). This work was partially supported by the Fundação para a Ciência e a Tecnologia [RESEARCH 4 COVID-19 project n. 029] and the EOSCsecretariat.eu COVID-19 Fast Track Funding. EOSCsecretariat.eu has received funding from the European Union’s Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant Agreement number 831644.