Chemical system biology approach to identify multi-targeting FDA inhibitors for treating COVID-19 and associated health complications

Abstract

In view of many European countries and the USA leading to the second wave of COVID-19 pandemic, winter season, the evolution of new mutations in the spike protein, and no registered drugs and vaccines for COVID-19 treatment, the discovery of effective and novel therapeutic agents is urgently required. The degrees and frequencies of COVID-19 clinical complications are related to uncontrolled immune responses, secondary bacterial infections, diabetes, cardiovascular disease, hypertension, and chronic pulmonary diseases. It is essential to recognize that the drug repurposing strategy so far remains the only means to manage the disease burden of COVID-19. Despite some success of using single-target drugs in treating the disease, it is beyond suspicion that the virus will acquire drug resistance by acquiring mutations in the drug target. The possible synergistic inhibition of drug efficacy due to drug-drug interaction cannot be avoided while treating COVID-19 and allied clinical complications. Hence, to avoid the unintended development drug resistance and loss of efficacy due to drug-drug interaction, multi-target drugs can be promising tools for the most challenging disease. In the present work, we have carried out molecular docking studies of compounds from the FDA approved drug library, and the FDA approved and passed phase -1 drug libraries with ten therapeutic targets of COVID-19. Results showed that known drugs, including nine anti-inflammatory compounds, four antibiotics, six antidiabetic compounds, and one cardioprotective compound, could effectively inhibit multiple therapeutic targets of COVID-19. Further in-vitro, in vivo, and clinical studies will guide these drugs' proper allocation to treat COVID-19.Communicated by Ramaswamy H. Sarma.

Keywords: COVID-19; FDA/passed phase-1 inhibitors; molecular docking; molecular dynamics; multi-targeting compounds.

Figure 1A.

Representation of protein-ligand interacting residues of compound Rutin hydrate with its best four protein targets i.e. (A) 3 C-like proteinase, (B) Helicase, (C) Papine-like proteinase (PLpro) and (D) RNA Dependent RNA Polymerase (RDRP).

Figure 1B.

Showing protein-ligand contacts between the compound Silymarin and its best four protein targets i.e. (A) EndoRNase, (B) Exoribonuclease, (C) Nucleocapsid and (D) Spike glycoprotein.

Figure 1C.

2 D-interaction diagram representing protein-ligand contacts of Luteolin with its best four targets i.e. (A)3c-like proteinase (B) EndoRNase (C) Helicase (D) Methyltransferase.

Figure 1D.

Representing protein-ligand contacts of Amikacin hydrate with its best four protein targets i.e. (A) Spike glycoprotein-ACE2 (B) EndoRNase (C) Methyltransferase (D) Exoribonuclease.

Figure 1E.

Displaying protein-ligand contact residues of Geneticin with its best four protein targets i.e. (A) EndoRNase, (B) Methyltransferase, (C) RNA dependent RNA polymerase (RDRP) and (D) Spike glycoprotein-ACE2.

Figure 1F.

2 D-interaction diagram indicating protein-ligand contacts of acarbose with its best four targets i.e. (A) Spike glycoprotein-ACE2, (B) Papine like proteinase (PLpro), (C) Exoribonuclease and (D) Nucleocapsid.

Figure 1G.

Showing protein-ligand contacts between the compound apigenin and its best four protein targets i.e. (A) 3c-like proteinase (3CLpro), (B) Methyltransferase, (C) Exoribonuclease and (D) Nucleocapsid.

Figure 2.

Protocol validation for SP and XP mode of docking through the depiction of both actives and decoys compounds by mapping the ROC curve.

Figure 3.

Plot of RMSD of Cα atoms of A) RDRP-Rutinhydrate B) Exo-Silymarin C) Helicase-Luteolin D) Methyltransferase-Amikacin hydrate E) Methyltransferase-Geneticin in angstroms as a function of simulation time in pico seconds.

Figure 4.

Plot of RMSF of Cα atoms of A) RDRP-Rutinhydrate B) Exo-Silymarin C) Helicase-Luteolin D) Methyltransferase-Amikacin hydrate E) Methyltransferase-Geneticin in angstroms as a function of Residue Index.

Figure 5.

Plot of Radius of gyration of A) RDRP-Rutinhydrate B) Exo-Silymarin C) Helicase-Luteolin D) Methyltransferase-Amikacin hydrate E) Methyltransferase-Geneticin in angstroms as a function of simulation time in pico seconds.

Figure 6.

Plot of solvation free energy of A) RDRP-Rutinhydrate B) Exo-Silymarin C) Helicase-Luteolin D) Methyltransferase-Amikacin hydrate E) Methyltransferase-Geneticin in kcal/mol as a function of simulation time in pico seconds.