Virtual Screening for SARS-CoV-2 Main Protease Inhibitory Peptides from the Putative Hydrolyzed Peptidome of Rice Bran

Abstract

The Coronavirus Disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the loss of life and has affected the life quality, economy, and lifestyle. The SARS-CoV-2 main protease (Mpro), which hydrolyzes the polyprotein, is an interesting antiviral target to inhibit the spreading mechanism of COVID-19. Through predictive digestion, the peptidomes of the four major proteins in rice bran, albumin, glutelin, globulin, and prolamin, with three protease enzymes (pepsin, trypsin, and chymotrypsin), the putative hydrolyzed peptidome was established and used as the input dataset. Then, the prediction of the antiviral peptides (AVPs) was performed by online bioinformatics tools, i.e., AVPpred, Meta-iAVP, AMPfun, and ENNAVIA programs. The amino acid composition and cytotoxicity of candidate AVPs were analyzed by COPid and ToxinPred, respectively. The ten top-ranked antiviral peptides were selected and docked to the SARS-CoV-2 main protease using GalaxyPepDock. Only the top docking scored candidate (AVP4) was further analyzed by molecular dynamics simulation for one nanosecond. According to the bioinformatic analysis results, the candidate SARS-CoV-2 main protease inhibitory peptides were 7-33 amino acid residues and formed hydrogen bonds at Thr22-24, Glu154, and Thr178 in domain 2 with short bonding distances. In addition, these top-ten candidate bioactive peptides contain hydrophilic amino acid residues and have a positive net charge. We hope that this study will provide a potential starting point for peptide-based therapeutic agents against COVID-19.

Keywords: SARS-CoV-2 main protease; antiviral peptide; bioinformatics; molecular docking; molecular dynamics; rice bran.

Figure 1

The workflow of the bioinformatic virtual screening for antiviral peptide (AVP) candidates and the in silico analysis of the SARS-CoV-2 main protease inhibition using molecular docking simulation.

Figure 2

Percentage of the peptides’ properties with respect to their (a) length, (b) hydrophobicity, and (c) net charge based on 71 putative AVPs.

Figure 3

Compositional analysis represents the preferences between the significant AVPs and non-AVPs.

Figure 4

Comparative molecular docking of the ten top-ranked AVPs (AVP1 to AVP10) on the crystal structure of the SARS-CoV-2 main protease in the apo state (PDB ID: 7C2Q) shown with (A) and without (B) the enzyme structure. The structure of the SARS-CoV-2 main protease is shaded in gold, and the peptides are labeled with different colors.

Figure 5

Molecular docking of the ten top-ranked AVPs (AVP1 (A), AVP2 (B), AVP3 (C), AVP4 (D), AVP5 (E), AVP6 (F), AVP7 (G), AVP8 (H), AVP9 (I), and AVP10 (J)) to the crystal structure of the SARS-CoV-2 main protease in the apo state (PDB ID: 7C2Q). The structure of the SARS-CoV-2 main protease is shaded in gold, and the peptide sequences are colored as labeled above. The hydrogen bonds are shown as red lines.

Figure 6

Molecular dynamics simulation of the Mpro–AVP4 complex; radius of teg gyrus plot (A), fraction of native contact analysis (B), and statistics of the hydrogen bonds (C).