In silico comparative analysis of HIV protease inhibitors effect on 2019-nCoV coronavirus 3CL_pro

Protein preparation

The three dimensional crystal structure of 2019-nCoV coronavirus protein 3CL_pro (Pdb id: 6lu7) was obtained from RCSB PDB (https://www.rcsb.org/structure/). The ligand groups and water molecules already present were removed out in order to make this structure suitable for further interactions with other ligands.

Ligand preparation

The HIV protease inhibitors has been scanned for the selected coronavirus protein structure. Three ligands Lopinavir [5], Cobicistat [6], Amprenavir, Atazanavir, Indinavir and Saquinavir [7] were selected from the literature review. The chemical structures for these ligands were obtained from PubChem in SDF format and were converted to PDB format for further interactions analysis.

HIV protease inhibitors and 3CL_pro interactions

The selected ligands were docked to coronavirus protein 3CL_pro using Autodock tool 1.5.6 [8]. Autodock is an automated docking tool to predict how the small molecule or substrate bind to a specific target protein. The protein and ligand PDB formatted files were converted to PDBQT formats followed by docking using Lamarckian genetic algorithm and a total of ten conformations for each ligand docking were observed with their binding energies to find out the best lead compound among them. The protein ligand interactions were obtained followed by the identification of interacting amino acid residues of coronavirus protein 3CL_pro to chemical groups with their respective ligands.

The docking analysis of 3CL_pro and target ligands revealed the interaction types in three ligands. The docking studies involving 3CL_pro with ligands such as Lopinavir, Cobicistat, Amprenavir, Atazanavir, Indinavir and Saquinavir were done to seek greater insight about the amino acid residues of MATE interacting with the specified ligands (Figure 1).

The interaction analysis revealed the occurrence of two amino acid residues ARG4 and LYS5 in interactions with selected ligands which conferred these two amino acid residues to be major drug target sites (Table 1).

The binding energies for ligands and 3CL_pro interactions were observed and analyzed comparatively. The lowest binding energy among the selected drugs; Cobicistat, Lopinavir, Amprenavir, Atazanavir, Indinavir and Saquinavir was found to be associated with Cobicistat which conferred it as one of the best suited ligand for 3CL_pro (Table 2). However, Cobicistat lacks the enzyme inducing activity and thus requires the co-administered drugs with close monitoring of dose adjustments while treating the patients.

The novel coronavirus 2019-nCoV has caused major loss to human lives, socially and economically as well. The urgent cure is the need of hour for this disease. The results observed from present studies has revealed the ligand with lowest binding energy ‘Cobicistat’ among the selected ligands which confers it to be one of the best suited ligand for 3CL_pro. Cobicistat and Ritonavir are structural analogues of each other but Ritonavir has major limitations like poor water solubility which corresponds to difficulty in its co-formulation and drug interactions. Furthermore, the switching between Cobicistat-based drug and Ritonavir-based drug treatment may produce significant problems among the patients. In order to avoid these limitations, only cobicistat has been taken under consideration in this study. The common amino acids ARG4 & LYS5 in the docking studies confirmed these two amino acids as main targets. The amino acid residues involved in interaction with novel coronavirus protein 3CL_pro also revealed the common interactions which shall further help scientists to find out the new target sites and lead compounds for novel coronavirus 2019-nCoV.

This work has been funded by the Department of Science & Technology, New Delhi, under a DST-INSPIRE Fellowship [IF180179] awarded to one of the authors (VK). The authors are thankful to DST and DBT, Ministry of Science & Technology, New Delhi for continuous financial support to the Bioinformatics Centre, Himachal Pradesh University, Shimla (India).

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