In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing | Zendy

Yogesh Kumar | Zendy; Harvijay Singh | Zendy; Chirag Patel | Zendy

Open Access

In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing

Author(s) -

Yogesh Kumar,

Harvijay Singh,

Chirag Patel

Publication year - 2020

Publication title -

journal of infection and public health

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.983

H-Index - 35

eISSN - 1876-035X

pISSN - 1876-0341

DOI - 10.1016/j.jiph.2020.06.016

Subject(s) - virtual screening , in silico , docking (animal) , computational biology , drug repositioning , lopinavir , drug discovery , biology , protease , ritonavir , virology , protein data bank (rcsb pdb) , biopharmaceutical , drug , chemistry , virus , medicine , enzyme , genetics , pharmacology , bioinformatics , biochemistry , viral load , gene , nursing , antiretroviral therapy

The rapidly enlarging COVID-19 pandemic caused by the novel SARS-corona virus-2 is a global public health emergency of an unprecedented level. Unfortunately no treatment therapy or vaccine is yet available to counter the SARS-CoV-2 infection, which substantiates the need to expand research efforts in this direction. The indispensable function of the main protease in virus replication makes this enzyme a promising target for inhibitors screening and drug discovery to treat novel coronavirus infection. The recently concluded α-ketoamide ligand-bound X-ray crystal structure of SARS-CoV-2 M pro (PDB ID: 6Y2F) from Zhang et al. has revealed the potential inhibitor binding mechanism and the molecular determinants responsible for substrate binding.

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