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. 2021 Sep:136:104759.
doi: 10.1016/j.compbiomed.2021.104759. Epub 2021 Aug 10.

Computational screening of 645 antiviral peptides against the receptor-binding domain of the spike protein in SARS-CoV-2

Md Minhas Hossain Sakib  1 , Aktiya Anjum Nishat  1 , Mohammad Tarequl Islam  1 , Mohammad Abu Raihan Uddin  1 , Md Shahriar Iqbal  1 , Farhan Fuad Bin Hossen  1 , Mohammad Imran Ahmed  1 , Md Samiul Bashir  1 , Takbir Hossain  1 , Umma Sumia Tohura  1 , Saiful Islam Saif  1 , Nabilah Rahman Jui  1 , Mosharaf Alam  1 , Md Aminul Islam  1 , Md Mehadi Hasan  1 , Md Abu Sufian  2 , Md Ackas Ali  1 , Rajib Islam  1 , Mohammed Akhter Hossain  3 , Mohammad A Halim  4
Affiliations

Computational screening of 645 antiviral peptides against the receptor-binding domain of the spike protein in SARS-CoV-2

Md Minhas Hossain Sakib et al. Comput Biol Med. 2021 Sep.

Abstract

The receptor-binding domain (RBD) of SARS-CoV-2 spike (S) protein plays a vital role in binding and internalization through the alpha-helix (AH) of human angiotensin-converting enzyme 2 (hACE2). Thus, it is a potential target for designing and developing antiviral agents. Inhibition of RBD activity of the S protein may be achieved by blocking RBD interaction with hACE2. In this context, inhibitors with large contact surface area are preferable as they can form a potentially stable complex with RBD of S protein and would not allow RBD to come in contact with hACE2. Peptides represent excellent features as potential anti-RBD agents due to better efficacy, safety, and tolerability in humans compared to that of small molecules. The present study has selected 645 antiviral peptides known to inhibit various viruses and computationally screened them against the RBD of SARS-CoV-2 S protein. In primary screening, 27 out of 645 peptides exhibited higher affinity for the RBD of S protein compared to that of AH of the hACE2 receptor. Subsequently, AVP1795 appeared as the most promising candidate that could inhibit hACE2 recognition by SARS-CoV 2 as was predicted by the molecular dynamics simulation. The critical residues in RBD found for protein-peptide interactions are TYR 489, GLY 485, TYR 505, and GLU 484. Peptide-protein interactions were substantially influenced by hydrogen bonding and hydrophobic interactions. This comprehensive computational screening may provide a guideline to design the most effective peptides targeting the spike protein, which could be studied further in vitro and in vivo for assessing their anti-SARS CoV-2 activity.

Keywords: Angiotensin converting enzyme 2; Antiviral peptide; Molecular dynamics simulation; Receptor-binding domain; SARS-CoV-2.

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Conflict of interest statement

Please check the following as appropriate.

  1. •All authors have participated in (a) conception and design, or analysis and interpretation of the data; (b) drafting the article or revising it critically for important intellectual content; and (c) approval of the final version.

  2. •This manuscript has not been submitted to, nor is under review at, another journal or other publishing venue.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
Flowchart for methodology.
Fig. 2
Fig. 2
Frequency distribution of all antiviral peptides over a range of docking scores.
Fig. 3
Fig. 3
Structure and sequences of the six best peptides obtained from docking protocols.
Fig. 4
Fig. 4
Binding interaction. (A) Interacting residues of RBD; (B) Distribution of non-covalent interactions; (C) Residue-residue Contact of the peptide-RBD docked complexes.
Fig. 5
Fig. 5
Molecular dynamics simulation (a) Root-mean-square deviation (RMSD); (b) Radius of gyration (Rg); (c) Solvent accessible surface area (SASA); and (d) Root-mean-square fluctuation (RMSF); (e) Score plot and (f) Loading plot of top eight peptide.
Fig. 6
Fig. 6
Representative snapshots (a) AH-RBD; (b) AVP1795-RBD; (c) AVP1784-RBD; (d) AVP0673-RBD; and (e) AVP1775-RBD over the course of 150 ns simulations. RBD is shown in cyan color.
Fig. 7
Fig. 7
Binding free energies, interactions, and secondary structure. (a) Distribution of binding free energies (Kcal/mol); (b) frequency of interaction (hydrogen, hydrophobic, electrostatic); Secondary structure of the (c) highest and (d) lowest frequency peptide residues.
Fig. 8
Fig. 8
RBD-AVP 1795. (a) Interacting RBD residues; (b) Interacting AVP 1795 residues; (c) Distribution of non-covalent interactions; (d) Representative snapshot (at 150 ns); AVP 1795 (purple) and RBD (grey) over 150 ns MD simulation. Arrows mark ≥90% time participation in bond formation during MD simulation.
See this image and copyright information in PMC

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