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Structural analysis, virtual screening and molecular simulation to identify potential inhibitors targeting 2'-O-ribose methyltransferase of SARS-CoV-2 coronavirus.

ABSTRACT: SARS-CoV-2, an emerging coronavirus, has spread rapidly around the world, resulting in over ten million cases and more than half a million deaths as of July 1, 2020. Effective treatments and vaccines for SARS-CoV-2 infection do not currently exist. Previous studies demonstrated that nonstructural protein 16 (nsp16) of coronavirus is an S-adenosyl methionine (SAM)-dependent 2'-O-methyltransferase (2'-O-MTase) that has an important role in viral replication and prevents recognition by the host innate immune system. In the present study, we employed structural analysis, virtual screening, and molecular simulation approaches to identify clinically investigated and approved drugs which can act as promising inhibitors against nsp16 2'-O-MTase of SARS-CoV-2. Comparative analysis of primary amino acid sequences and crystal structures of seven human CoVs defined the key residues for nsp16 2-O'-MTase functions. Virtual screening and docking analysis ranked the potential inhibitors of nsp16 from more than 4,500 clinically investigated and approved drugs. Furthermore, molecular dynamics simulations were carried out on eight top candidates, including Hesperidin, Rimegepant, Gs-9667, and Sonedenoson, to calculate various structural parameters and understand the dynamic behavior of the drug-protein complexes. Our studies provided the foundation to further test and repurpose these candidate drugs experimentally and/or clinically for COVID-19 treatment. Communicated by Ramaswamy H. Sarma.

SUBMITTER: Jiang Y

PROVIDER: S-EPMC7544923 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Structural analysis, virtual screening and molecular simulation to identify potential inhibitors targeting 2'-O-ribose methyltransferase of SARS-CoV-2 coronavirus.

Jiang Yuanyuan Y Liu Lanxin L Manning Morenci M Bonahoom Madison M Lotvola Aaron A Yang Zhe Z Yang Zeng-Quan ZQ

Journal of biomolecular structure & dynamics 20201004 3

SARS-CoV-2, an emerging coronavirus, has spread rapidly around the world, resulting in over ten million cases and more than half a million deaths as of July 1, 2020. Effective treatments and vaccines for SARS-CoV-2 infection do not currently exist. Previous studies demonstrated that nonstructural protein 16 (nsp16) of coronavirus is an S-adenosyl methionine (SAM)-dependent 2'-O-methyltransferase (2'-O-MTase) that has an important role in viral replication and prevents recognition by the host inn ...[more]

PMID: 33016237

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Project description:The recent pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) calls the whole world into a medical emergency. For tackling Coronavirus Disease 2019 (COVID-19), researchers from around the world are swiftly working on designing and identifying inhibitors against all possible viral key protein targets. One of the attractive drug targets is guanine-N7 methyltransferase which plays the main role in capping the 5'-ends of viral genomic RNA and sub genomic RNAs, to escape the host's innate immunity. We performed homology modeling and molecular dynamic (MD) simulation, in order to understand the molecular architecture of Guanosine-P3-Adenosine-5',5'-Triphosphate (G3A) binding with C-terminal N7-MTase domain of nsp14 from SARS-CoV-2. The residue Asn388 is highly conserved in present both in N7-MTase from SARS-CoV and SARS-CoV-2 and displays a unique function in G3A binding. For an in-depth understanding of these substrate specificities, we tried to screen and identify inhibitors from the Traditional Chinese Medicine (TCM) database. The combination of several computational approaches, including screening, MM/GBSA, MD simulations, and PCA calculations, provides the screened compounds that readily interact with the G3A binding site of homology modeled N7-MTase domain. Compounds from this screening will have strong potency towards inhibiting the substrate-binding and efficiently hinder the viral 5'-end RNA capping mechanism. We strongly believe the final compounds can become COVID-19 therapeutics, with huge international support.[Formula: see text]The focus of this study is to screen for antiviral inhibitors blocking guanine-N7 methyltransferase (N7-MTase), one of the key drug targets involved in the first methylation step of the SARS-CoV-2 RNA capping mechanism. Compounds binding the substrate-binding site can interfere with enzyme catalysis and impede 5'-end cap formation, which is crucial to mimic host RNA and evade host cellular immune responses. Therefore, our study proposes the top hit compounds from the Traditional Chinese Medicine (TCM) database using a combination of several computational approaches.Communicated by Ramaswamy H. Sarma.

Dataset Information

Structural analysis, virtual screening and molecular simulation to identify potential inhibitors targeting 2'-O-ribose methyltransferase of SARS-CoV-2 coronavirus.

Publications

Structural analysis, virtual screening and molecular simulation to identify potential inhibitors targeting 2'-O-ribose methyltransferase of SARS-CoV-2 coronavirus.

Similar Datasets

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