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. 2022 Aug:573:96-110.
doi: 10.1016/j.virol.2022.06.008. Epub 2022 Jun 15.

In-Silico targeting of SARS-CoV-2 NSP6 for drug and natural products repurposing

Ahmed Abdelkader  1 , Amal A Elzemrany  2 , Mennatullah El-Nadi  3 , Sherif A Elsabbagh  4 , Moustafa A Shehata  5 , Wagdy M Eldehna  6 , Mohamed El-Hadidi  2 , Tamer M Ibrahim  7
Affiliations

In-Silico targeting of SARS-CoV-2 NSP6 for drug and natural products repurposing

Ahmed Abdelkader et al. Virology. 2022 Aug.

Abstract

Non-Structural Protein 6 (NSP6) has a protecting role for SARS-CoV-2 replication by inhibiting the expansion of autophagosomes inside the cell. NSP6 is involved in the endoplasmic reticulum stress response by binding to Sigma receptor 1 (SR1). Nevertheless, NSP6 crystal structure is not solved yet. Therefore, NSP6 is considered a challenging target in Structure-Based Drug Discovery. Herein, we utilized the high quality NSP6 model built by AlphaFold in our study. Targeting a putative NSP6 binding site is believed to inhibit the SR1-NSP6 protein-protein interactions. Three databases were virtually screened, namely FDA-approved drugs (DrugBank), Northern African Natural Products Database (NANPDB) and South African Natural Compounds Database (SANCDB) with a total of 8158 compounds. Further validation for 9 candidates via molecular dynamics simulations for 100 ns recommended potential binders to the NSP6 binding site. The proposed candidates are recommended for biological testing to cease the rapidly growing pandemic.

Keywords: COVID-19; Docking; DrugBank; Molecular dynamics; NSP6; Natural products.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Image 1
Graphical abstract
Fig. 1
Fig. 1
(A) Multiple Sequence Alignment (MSA) for NSP6 Protein from 10 different beta-Coronaviruses utilized by ClustalW (Larkin et al., 2007) using muscle (Madeira et al., 2019). The color-coding of ClustalW indicates the physicochemical properties of amino acid residues. Hydrophobic, polar, positive- and negative-charged residues are highlighted blue, green, red, and magenta, respectively. Glycine, proline, and aromatic residues are shaded orange, yellow and cyan, respectively. Non-conserved amino acid residues are highlighted in white. (B) Percentage identity matrix for NSP6 among the 10 beta-Coronaviruses. (C) The phylogenetic tree of MSA.
Fig. 2
Fig. 2
3D structure of the generated model and structural validation using Ramachandran plot and statistics. (A) NSP6 model predicted by AlphaFold. (B) Ramachandran plot shows 94.7% of residues in most favored regions, and 5.3% in allowed regions. (C) ERRAT output with overall quality factor 99.270.
Fig. 3
Fig. 3
Protein-protein interaction of SR1 and NSP6. (A) SR1 and NSP6 protein-protein interaction as an output of docking experiment (Alsulami et al., 2021), as shown in yellow and green cartoons, respectively. (B) a closer view of NSP6-SR1 interaction. Represented as violet sticks of Sigma Receptor 1 and amino acids of NSP 6 involved in the binding site.
Fig. 4
Fig. 4
Overall binding modes of molecules generated by molecular docking of the top 14 FDA-approved drugs and top 5 natural products with the selected region in the NSP6 protein. (A) Docking poses of 14 top-scored FDA-approved drugs (Venetoclax, Glecaprevir, Digitoxin, Dactinomycin, Oritavancin, Ledipasvir, Ergotamine, Irinotecan, Apixaban, Siponimod, Dihydroergocristine, Acetyldigitoxin). (B) Docking poses of 5 top-scored natural products from NANPDB (Euphoroscopin, Arjunin, Chebulagic acid, 3′-O-methyl-4-O-(3″,4″-di-O-galloyl-alpha-L-rhamnopyranosyl), and Owerreine). (C) Docking poses of 5 top-scored natural products from SANCDB (Cephalostatin 2, Cephalostatin 11, Cephalostatin 3, Cephalostatin 16, and Cephalostatin 19). All poses appeared to occupy the predicted binding site and were speculated to inhibit SR1-NSP6 protein-protein interactions.
Fig. 5
Fig. 5
Generated binding modes of the selected natural products with the selected region in the NSP6 protein. Cephalostatin 2 (SA1) (A, B), Cephalostatin 11 (SA2) (C, D) and Chebulagic acid (NA) (E, F), were presented as cyan sticks in the predicted binding site of NSP-6 in three- and two-dimensions. Their docking scores are −10.3, −10.1 and −9.2 (kcal/mol), respectively.
Fig. 6
Fig. 6
The binding modes of the selected FDA-approved drugs. Docking poses of FDA-approved drugs, namely: Venetoclax (DB11581) (A, B), Digitoxin (DB01396) (C, D), Dactinomycin (DB00970) (E, F). Their docking scores are −9.7, −9.1, −9 (kcal/mol), respectively.
Fig. 7
Fig. 7
Docking poses of FDA-approved drugs, namely: Glecaprevir (DB13879) (A, B) and Ledipasvir (DB09027) (C, D). Their docking scores are −9.2 and −8.8 (kcal/mol), respectively.
Fig. 8
Fig. 8
The root mean squared deviation of the protein backbone atoms during the MD simulation of (A) FDA approved and (B) natural compounds.
Fig. 9
Fig. 9
Assessment of protein-ligand complexes stability throughout the simulation process the computed root mean squared deviation (RMSD) of candidates from FDA approved drugs (A) and natural compounds (B).
Fig. 10
Fig. 10
Protein flexibility assessment using root mean square fluctuations (RMSF) throughout the simulation process. The protein backbone atoms root mean-squared fluctuations (RMSF) acquired from candidates from FDA approved drugs (A) and natural compounds (B).
Fig. 11
Fig. 11
Protein compactness evaluation by radius of gyration (Rg). Protein compactness using the radius of gyration (Rg) including the apo form and candidates from FDA approved drugs (A) and natural products (B).
Fig. 12
Fig. 12
Evaluation of protein-ligand hydrogen bonds. H-bond count calculated between the protein and candidates from natural products and FDA approved drugs.
Fig. 13
Fig. 13
Free Energy Landscape (FEL) of NSP6 and top selected complex systems. (A) NSP6, (B) NSP6-DB00970, (C) NSP6-DB11581, (D) NSP6-SA1 and (E) NSP6-NA1 systems.
Fig. 14
Fig. 14
Per-residue energy decomposition analysis of (A) Venetoclax (DB11581) and (B) Dactinomycin (DB00970).
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