Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Nov 26:4:349-355.
doi: 10.1016/j.crstbi.2022.11.001. eCollection 2022.

Insights into the structural properties of SARS-CoV-2 main protease

Affiliations

Insights into the structural properties of SARS-CoV-2 main protease

Ibrahim Yagiz Akbayrak et al. Curr Res Struct Biol. .

Abstract

SARS-CoV-2 is the infectious agent responsible for the coronavirus disease since 2019, which is the viral pneumonia pandemic worldwide. The structural knowledge on SARS-CoV-2 is rather limited. These limitations are also applicable to one of the most attractive drug targets of SARS-CoV-2 proteins - namely, main protease Mpro, also known as 3C-like protease (3CLpro). This protein is crucial for the processing of the viral polyproteins and plays crucial roles in interfering viral replication and transcription. In fact, although the crystal structure of this protein with an inhibitor was solved, Mpro conformational dynamics in aqueous solution is usually studied by molecular dynamics simulations without special sampling techniques. We conducted replica exchange molecular dynamics simulations on Mpro in water and report the dynamic structures of Mpro in an aqueous environment including root mean square fluctuations, secondary structure properties, radius of gyration, and end-to-end distances, chemical shift values, intrinsic disorder characteristics of Mpro and its active sites with a set of computational tools. The active sites we found coincide with the currently known sites and include a new interface for interaction with a protein partner.

Keywords: Dynamics; Replica exchange MD simulations; SARS-CoV-2 main protease.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
Selected conformations of the SARS-CoV-2 Mpro in water from REMD simulations.
Fig. 2
Fig. 2
REMD-obtained structural flexibility of the SARS-CoV-2 Mpro in water with its intrinsic disorder pre-disposition. The figure shows root mean square fluctuations (RMSF) of SARS-CoV-2 Mpro in water by REMD simulations at 280, 290, 300, 310, and 320 ​K and intrinsic disorder profile generated by PONDR® VLXT, PONDR® VSL2, PONDR® FIT, IUPred_short, and IUPres_long.
Fig. 3
Fig. 3
Identification of potential protein/peptide and nucleic acid binding residues in the SARS-CoV-2 Mpro. Panel A. Predisposition of Mpro to interact with proteins and peptides predicted by HybridPBRpred (dark green lines) and PepBCL (light green lines), and with RNA (red lines) and DNA (orange lines) predicted by DRNApred. Putative propensity for binding is shown at the top of the figure while the horizontal bars directly underneath denote the location of the predicted protein binding residues (dark and light green bars). No DNA and RNA binding residues were predicted. The native protein-binding residues associated with the interface of the SARS-CoV-2 Mpro dimer are shown using the dark blue horizontal bar (PDB id: 6lu7). The residues that interact with peptide ligands are color-coded to denote the source complex structures and shown at the bottom of the panel. These annotations were extracted using the BioLip resource from 28 structures of Mpro in complex with peptides (PDB ids: 3atw, 3avz, 3aw0, 6lu7, 7bqy, 6xa4, 6xbg, 6xbh, 6xbi, 6xch, 6xfn, 7c8b, 7kvg, 7cut, 7mgr, 7mgs, 7n6n, 7n89, 7m2p, 7ein, 7s82, 7rnw, 7dvp, 7dvw, 7dvx, 7dvy, 7dw0, and 7dw6). They are grouped by the data of deposition. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4
Fig. 4
Calculated per residue propensities for α-helix, 310-helix, β-sheet, and turn secondary structure of the SARS-CoV-2 Mpro in water with dynamics.
Fig. 5
Fig. 5
K-means clustering along with Rg and REE values of the SARS-CoV-2 Mpro in water. five k values were utilized and centroids were found to be located at Rg ​= ​22.54 ​Å, REE ​= ​20.83 ​Å (Centroid1), Rg ​= ​22.47 ​Å, REE ​= ​30.49 ​Å (Centroid 2), Rg ​= ​22.52 ​Å, REE ​= ​11.29 ​Å (Centroid 3), Rg ​= ​22.54 ​Å, REE ​= ​15.89 ​Å (Centroid 4), Rg ​= ​22.51 ​Å, REE ​= ​5.89 ​Å (Centroid 5).
Fig. 6
Fig. 6
The simulated Cα and Hα chemical shift values (red circles) by REMD simulations and their comparison to experiments (black circles). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Similar articles

Cited by

References

    1. Akaji K., et al. Structure-based design, synthesis, and evaluation of peptide-mimetic SARS 3CL protease inhibitors. J. Med. Chem. 2011;54:7962–7973. - PubMed
    1. Akbayrak I.Y., Caglayan S.I., Durdagi S., Kurgan L., Uversky V.N., Ulver B., Dervisoglu H., Haklidir M., Hasekioglu O., Coskuner-Weber O. Structures of MERS-CoV macro domain in aqueous solution with dynamics: impacts of parallel tempering simulation techniques and CHARMM36m and AMBER99SB force field parameters. Proteins: Struct., Funct., Bioinf. 2021;89(10):1289–1299. doi: 10.1002/prot.26150. - DOI - PMC - PubMed
    1. Cantrelle F.-X., et al. NMR spectroscopy of the main protease of SARS-CoV-2 and fragment-based screening identify three protein hotspots and an antiviral fragment. Angew. Chem., Int. Ed. 2021;60:25428–25435. - PMC - PubMed
    1. Chan-Yeung M., Xu R.-H. SARS: Epidemiology. Respirol. Carlton Vic. 2003;8(Suppl. l):S9–S14. doi: 10.1046/j.1440-1843.2003.00518.x. - DOI - PMC - PubMed
    1. Coskuner O., Uversky V.N. Tyrosine regulates β-sheet structure formation in amyloid-Β42: a new clustering algorithm for disordered proteins. J. Chem. Inf. Model. 2017;57(6):1342–1358. doi: 10.1021/acs.jcim.6b00761. - DOI - PubMed

LinkOut - more resources