Identifying epitopes for cluster of differentiation and design of new peptides inhibitors against human SARS-CoV-2 spike RBD by an in-silico approach

Abstract

The coronavirus disease 19 (COVID-19) is a highly contagious and rapidly spreading infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In some cases, the disease can be fatal which resulted in more than one million deaths worldwide according the WHO. Currently, there is no effective vaccine or treatment for COVID-19, however many small-molecule inhibitors have shown potent antiviral activity against SARS-CoV-2 and some of them are now under clinical trials. Despite their promising activities, the development of these small molecules for the clinical use can be limited by many factors like the off-target effect, the poor stability, and the low bioavailability. The clusters of differentiation CD147, CD209, CD299 have been identified as essential entry co-receptors for SARS-CoV-2 species specificity to humans, although the underlying mechanisms are yet to be fully elucidated. In this paper, protein-protein docking was utilized for identifying the critical epitopes in CD147, CD209 and CD299 which are involved in the binding with SARS-CoV-2 Spike receptor binding domain (RBD). The results of binding free energies showed a high affinity of SARS-CoV-2 RBD to CD299 receptor which was used as a reference to derive hypothetical peptide sequences with specific binding activities to SARS-CoV-2 RBD. Molecular docking and molecular dynamics simulations of the newly designed peptides showed favorable binding features and stability with SARS-CoV-2 RBD and therefore can be further considered as potential candidates in future anti-SARS CoV-2 drug discovery studies.

Keywords: Biological sciences; Chemistry; Cluster of differentiation; Computer science; Coronavirus 19; Engineering; Molecular docking; Molecular dynamics; Peptide-based drugs; Physics; Spike protein.

Figure 1

An overview of Integrative workflow adopted in this study. The methods included screening of three CD Markers targets using molecular docking, MM-GBSA binding free energy estimation and molecular dynamics simulations.

Figure 2

Docking of SARS-CoV-2 RBD (yellow cartoon) and SARS-CoV-1 RBD (grey cartoon) against CD299 receptor using ZDOCK algorithm. Hydrogen bonds at the interface of two proteins are represented by the green lines.

Figure 3

Comparisons of binding free energies of Hydrogen bond residues of the CD299 receptor inside SARS-CoV-2 RBD and SARS-CoV RBD throughout the Docking using MM-GBSA HawkDock server.

Figure 4

Analysis of all backbone atom root mean square deviations (RMSD) values of RBD-CoV-2/CD299 and RBD-CoV/CD299 complex (A and B) respectively over 5 ns simulation time.

Figure 5

Root mean square fluctuations (RMSF) of CD299/SARS-CoV-2 RBD and CD299/SARS-CoV-2 RBD complex (A and B) respectively, were computed and plotted of each residue for the RBD domain (residues 130–300) and the CD299 (residues 0–129).

Figure 6

Multiple Sequence Alignment and Secondary Structure Elements (SSE%) analysis of SARS-CoV-2 RBD–CD299 and SARS-CoV RBD–CD299 complexes during (MD) simulation: A: Multiple Sequence Alignment using ClustalW, Asterisks (∗) indicated fully conserved residues, the colon symbol (:) indicates conservation between groups of very similar properties, and the period symbol (.) indicates conservation between groups of weakly similar properties. (B: RBD SARS-CoV-) (C: RBD SARS-CoV) Secondary Structure Elements (SSE%), alpha helix and beta strand regions are highlighted in red and blue backgrounds, respectively.

Figure 7

Docking models of SARS-CoV-2 RBD epitopes/CD299, the binding site epitopes SARS-CoV-2 RBD surface indicated by red color, and the binding site in CD299 indicated by blue color.

Figure 8

Tertiary structure of designed peptides. The cartoon and line representation of the peptidomimetics structures (A: peptide P1, B: peptide P2, C: peptide P3, D: peptide P4).

Figure 9

The binding modes of complex SARS-CoV-2 RBD/New designed peptides P1,P2, P3, P4 and anti-SARS-CoV. The New designed peptides binding site of the domain RBD is shaded in red and RBD SARS-CoV-2 are shaded in gray using CABS-dock. (A:P1/CD299, B: P2/CD299, C: P3/CD299, D: P4/CD299 E: Inhibitor SARS-CoV/CD299).

Figure 10

Contact map of the interface between SARS-CoV-2 RBD and the best Peptide score affinity throughout the Docking using CABS-dock server.

Figure 11

Per-residue binding free energy decomposition (kcal/mol) of complexes RBD-CoV-2/CD299 and RBD-CoV-2/CD299 throughout the Docking using MM-GBSA module in HawkDock server.

Figure 12

Analysis of all backbone atom root mean square deviations (RMSD) of all new peptides inhibitors designs over 5 ns simulation time with RBD domain SARS-CoV-2 over 5 ns. A: peptide P1, B: peptide P2, C: peptide P3 D: peptide P4.

Figure 13

Root mean square fluctuations (RMSF) of all new peptides inhibitors designs calculated for every residue with RBD domain SARS-CoV-2 over 5 ns. Calculated and plotted for each residue of the RBD domain (residue 20–200) and the peptides (residue 0–19). A: peptide P1, B: peptide P2, C: peptide P3 D: peptide P4.

Figure 14

Analysis of molecular characteristics of the new memic peptides design. The PepCalc program was used to analyses the physic-chemical characteristics peptides sequences, showing differences in amphipathic properties (top: hydrophilic; bottom: hydrophobic). (A: peptide P1, B: peptide P2, C: peptide P3, D: peptide P4).