Identification of Potential Drug Targets and Prediction of the Potential Impact of High Risk Non Synonymous Single Nucleotide Polymorphism in SARS-CoV-2 3C like Proteinase (3CLpro): A Computational Approach

Sahar Elbager, Abdelrahman hamza, Afra M. Al Bkrye, Asia M. Alrashied, Entisar N. M. Ali Hadeel, A. Mohamed, Hazem A. Abubaker, Israa A. Mohamed, Manal A. H. Goda, Mohammed Y. Basher, Naglla F.A Gabir, Safinaz I. Khalil

10.26434/chemrxiv.12235181.v1

Research curated

Abstract

On January 2020, a new coronavirus (officially named SARS-CoV-2) was associated with alarming outbreak of a pneumonia-like illness, which was later named by the WHO as COVID-19, originating from Wuhan City, China. Although many clinical studies involving antiviral and immunomodulatory drug treatments for SARS-CoV-2 all without reported results, no approved drugs have been found to effectively inhibit the virus so far. Full genome sequencing of the virus was done, and uploaded to be freely available for the world scientists to explore. A promising target for SARS-CoV-2 drug design is a chymotrypsin-like cysteine protease (3CLpro), a main protease responsible for the replication and maturation of functional proteins in the life cycle of the SARS coronavirus. Here we aim to explore SARS-CoV-2 3CLpro as possible drug targets based on ligand- protein interactions. In addition, ADME properties of the ligands were also analyzed to predict their drug likeliness. The results revealed Out of 9 ligands, 8 ligands (JFM, X77, RZG, HWH, T8A, 0EN, PEPTIDE and DMS) showed best ADME properties. These findings suggest that these ligands can be used as potential molecules for developing potent inhibitors against SARS-CoV-2 3CLpro, which could be helpful in inhibiting the propagation of the COVID-19. Furthermore, 10 potential amino acids residues were recognized as potential drug binding site (THR25, HIS41, GLY143, SER144, CYS145, MET165, GLU166, GLN189, ASP295 and ARG298). All those amino acid residues were subjected to missense SNP analysis were recognized to affect the structure and function of the protein. These characteristics provide them the promising to be target sites for the fresh generation inhibitors to work with and overcome drug resistance. These findings would be beneficial for the drug development for inhibiting SARS-CoV-2 3CLpro hence assisting the pharmacogenomics effort to manage the infection. of SARS-CoV-2.

Source: ChemRxiv

Related molecules

Name	Synonyms	Genes
Asiatic acid
Guaijaverin	Guajaverin, Guajaverin
Avicularin
Hydrocortisone
Dinoprost tromethamine
(8R,9Z,12Z)-8-hydroxy-6-oxooctadeca-9,12-dienoic acid
Mupirocin	Pseudomonic acid
Reidispongiolide C
nsp9	replicase
Unspecific
Myricitrin	Myricetin, Cannabiscetin, MYC, Myricetin, Myricetol
RNA dependent RNA polymerase	RDR, viral RNA polymerase, RdRp, nsp12	rep, ORF1a-1b, RdRp
Simvastatin
3C-like protease	3CLpro, Mpro, SARS coronavirus main peptidase, 3CLpro-SARS-CoV-2	rep, ORF1a-1b
Spike glycoprotein	Spike protein, S glycoprotein, S-Protein, S1, S2, S3, Peplomer protein, E2	S, ORF2
Withaferin
Diosmin	diosmetin 7-neohesperidoside ,Diosmetin 7-O-rutinoside ,Diosmin ,Diosmina ,Diosmine ,Diosminum

Related interactions

Target	Drug	Type	Result
Unspecific	Hydrocortisone	Computational	positive
Unspecific	Dinoprost tromethamine	Computational	positive
Unspecific	(8R,9Z,12Z)-8-hydroxy-6-oxooctadeca-9,12-dienoic acid	Computational	positive
Unspecific	Diosmin	Computational	positive
3C-like protease	Myricitrin	Computational	positive
Unspecific	Myricitrin	Computational	positive
Unspecific	Mupirocin	Computational	positive
Unspecific	Reidispongiolide C	Computational	positive
3C-like protease	Asiatic acid	Computational	positive
3C-like protease	Avicularin	Computational	positive
Spike glycoprotein	Asiatic acid	Computational	positive
Spike glycoprotein	Guaijaverin	Computational	positive
nsp9	Asiatic acid	Computational	positive
RNA dependent RNA polymerase	Myricitrin	Computational	positive
Unspecific	Simvastatin	Computational	positive
3C-like protease	Diosmin	Computational	positive