Exploring Toxins for Hunting SARS-CoV-2 Main Protease Inhibitors: Molecular Docking, Molecular Dynamics, Pharmacokinetic Properties, and Reactome Study

Abstract

The main protease (M^pro) is a potential druggable target in SARS-CoV-2 replication. Herein, an in silico study was conducted to mine for M^pro inhibitors from toxin sources. A toxin and toxin-target database (T3DB) was virtually screened for inhibitor activity towards the M^pro enzyme utilizing molecular docking calculations. Promising toxins were subsequently characterized using a combination of molecular dynamics (MD) simulations and molecular mechanics-generalized Born surface area (MM-GBSA) binding energy estimations. According to the MM-GBSA binding energies over 200 ns MD simulations, three toxins-namely philanthotoxin (T3D2489), azaspiracid (T3D2672), and taziprinone (T3D2378)-demonstrated higher binding affinities against SARS-CoV-2 M^pro than the co-crystalized inhibitor XF7 with MM-GBSA binding energies of -58.9, -55.9, -50.1, and -43.7 kcal/mol, respectively. The molecular network analyses showed that philanthotoxin provides a ligand lead using the STRING database, which includes the biochemical top 20 signaling genes CTSB, CTSL, and CTSK. Ultimately, pathway enrichment analysis (PEA) and Reactome mining results revealed that philanthotoxin could prevent severe lung injury in COVID-19 patients through the remodeling of interleukins (IL-4 and IL-13) and the matrix metalloproteinases (MMPs). These findings have identified that philanthotoxin-a venom of the Egyptian solitary wasp-holds promise as a potential M^pro inhibitor and warrants further in vitro/in vivo validation.

Keywords: SARS-CoV-2 Mpro; in silico screening; molecular docking calculations; molecular dynamics (MD) simulations; reactome; toxins.

Figure 1

(a) 3D representation of the anticipated docking pose of XF7 (in pink) and experimental structure (in mauve) of XF7, (b) 3D, in addition to (c) 2D representations of the predicted binding mode of XF7 complexed with SARS-CoV-2 main protease (M^pro).

Figure 2

3D and 2D molecular interactions of the predicted docking poses of toxins (i) T3D2489, (ii) T3D2672, and (iii) T3D2378 towards SARS-CoV-2 M^pro.

Figure 3

Calculated MM-GBSA binding energies for the native XF7 inhibitor and the most seven potent toxins complexed with SARS-CoV-2 M^pro throughout 5 ns, 50 ns, and 200 ns MD simulations.

Figure 4

Components of the MM-GBSA binding energies for (a) XF7, (b) T3D2489, (c) T3D2672, and (d) T3D2378 complexed with SARS-CoV-2 M^pro throughout the simulation time of 200 ns.

Figure 5

Energy participation of the proximal residues to the total binding free energy (kcal/mol) of T3D2489, T3D2672, T3D2378, and XF7 complexed with SARS-CoV-2 main protease (M^pro).

Figure 6

Computed MM-GBSA binding energy per frame for XF7 (in black), T3D2489 (in red), T3D2672 (in blue), in addition to T3D2378 (in cyan) in complex with SARS-CoV-2 main protease (M^pro) throughout 200 ns MD simulations.

Figure 7

Number of hydrogen bonds formed between XF7 (in black), T3D2489 (in red), T3D2672 (in blue), and T3D2378 (in cyan) and SARS-CoV-2 M^pro throughout 200 ns MD simulations.

Figure 8

Distance between the center-of-mass (CoM) (in Å) of XF7 (in black), T3D2489 (in red), T3D2672 (in blue), and T3D2378 (in cyan) and GLN189 of SARS-CoV-2 M^pro over the 200 ns MD simulations.

Figure 9

Root-mean-square deviation (RMSD) of the backbone atoms from the initial structure of XF7 (in black), T3D2489 (in red), T3D2672 (in blue), and T3D2378 (in cyan) with SARS-CoV-2 M^pro during the simulation time of 200 ns.

Figure 10

Bioinformatic analysis: (A) The PPI network of top genes; (B) the top 20 gene comparison in lung adenocarcinoma and lung squamous cell carcinoma; (C,D) Gene Expression Profiling Interactive Analysis (GEPIA), the expression level of CTSB was increased in lung adenocarcinoma and squamous cell lung carcinoma.

Figure 11

The Reacfoam map shows the top enriched pathway (Interleukin-4 and Interleukin-13 signaling) influenced by the top 20 gene targets in response to philanthotoxin (T3D2489).

Figure 12

Graphic representation of the Interleukin-4 and Interleukin-13 signaling Reactome pathway influenced as a response to philanthotoxin (T3D2489) in the human genome.