Virtual high-throughput screening: Potential inhibitors targeting aminopeptidase N (CD13) and PIKfyve for SARS-CoV-2

Abstract

Since the outbreak of the novel coronavirus nearly 3 years ago, the world's public health has been under constant threat. At the same time, people's travel and social interaction have also been greatly affected. The study focused on the potential host targets of SARS-CoV-2, CD13, and PIKfyve, which may be involved in viral infection and the viral/cell membrane fusion stage of SARS-CoV-2 in humans. In this study, electronic virtual high-throughput screening for CD13 and PIKfyve was conducted using Food and Drug Administration-approved compounds in ZINC database. The results showed that dihydroergotamine, Saquinavir, Olysio, Raltegravir, and Ecteinascidin had inhibitory effects on CD13. Dihydroergotamine, Sitagliptin, Olysio, Grazoprevir, and Saquinavir could inhibit PIKfyve. After 50 ns of molecular dynamics simulation, seven compounds showed stability at the active site of the target protein. Hydrogen bonds and van der Waals forces were formed with target proteins. At the same time, the seven compounds showed good binding free energy after binding to the target proteins, providing potential drug candidates for the treatment and prevention of SARS-CoV-2 and SARS-CoV-2 variants.

Keywords: CD13; PIKfyve; SARS-CoV-2; drug repurposing; potential inhibitor; virtual screening.

Graphical abstract

Figure 1

Binding energies for virtual hit compounds. The violet line shows the cut-off range for the compounds selected. (a) Binding energy of CD13 with FDA-approved compounds. (b) Binding energy of PIKfyve with FDA-approved compounds.

Figure 2

The binding model of dihydroergotamine against CD13 and PIKfyve. (a) Interactions between dihydroergotamine (green) and associated residues (purple) in the CD13 protein interface pocket (cyan) for SARS‐CoV‐2. (b) Two-dimensional interaction diagram of dihydroergotamine binding to the CD13 active site. (c) Interactions between dihydroergotamine (green) and associated residues (purple) in the PIKfyve protein interface pocket (cyan) for SARS‐CoV‐2. (d) Two-dimensional interaction diagram of dihydroergotamine binding to the PIKfyve active site. The numbers next to the dotted line indicate the interaction distance.

Figure 3

The binding model of Saquinavir against CD13 and PIKfyve. (a) Interactions between Saquinavir (green) and associated residues (purple) in the CD13 protein interface pocket (cyan) for SARS‐CoV‐2. (b) Two-dimensional interaction diagram of dihydroergotamine binding to the CD13 active site. (c) Interactions between Saquinavir (green) and associated residues (purple) in the PIKfyve protein interface pocket (cyan) for SARS‐CoV‐2. (d) Two-dimensional interaction diagram of dihydroergotamine binding to the PIKfyve active site. The numbers next to the dotted line indicate the interaction distance.

Figure 4

The binding model of Olysio against CD13 and PIKfyve. (a) Interactions between Olysio (green) and associated residues (purple) in the CD13 protein interface pocket (cyan) for SARS‐CoV‐2. (b) Two-dimensional interaction diagram of dihydroergotamine binding to the CD13 active site. (c) Interactions between Olysio (green) and associated residues (purple) in the PIKfyve protein interface pocket (cyan) for SARS‐CoV‐2. (d) Two-dimensional interaction diagram of dihydroergotamine binding to the PIKfyve active site. The numbers next to the dotted line indicate the interaction distance.

Figure 5

The binding model of Raltegravir and Ecteinascidin against CD13. (a) Interactions between Raltegravir (green) and associated residues (purple) in the CD13 protein interface pocket (cyan) for SARS‐CoV‐2. (b) Two-dimensional interaction diagram of Raltegravir binding to the CD13 active site. (c) Interactions between Ecteinascidin (green) and associated residues (purple) in the CD13 protein interface pocket (cyan) for SARS‐CoV‐2. (d) Two-dimensional interaction diagram of Ecteinascidin binding to the CD13 active site. The numbers next to the dotted line indicate the interaction distance.

Figure 6

The binding model of Sitagliptin and Grazoprevir against PIKfyve. (a) Interactions between Sitagliptin (green) and associated residues (purple) in the PIKfyve protein interface pocket (cyan) for SARS‐CoV‐2. (b) Two-dimensional interaction diagram of Sitagliptin binding to the PIKfyve active site. (c) Interactions between Grazoprevir (green) and associated residues (purple) in the PIKfyve protein interface pocket (cyan) for SARS‐CoV‐2. (d) Two-dimensional interaction diagram of Grazoprevir binding to the PIKfyve active site. The numbers next to the dotted line indicate the interaction distance.

Figure 7

MD trajectory analysis for the selected top five compound–CD13 complexes. (a) RMSD, root mean square deviation. (b) RMSF, root mean square fluctuation. (c) R _g, radius of gyration. (d) SASA, solvent accessible surface area. (e) Hydrogen bonds’ interaction between CD13 and compounds.

Figure 8

MD trajectory analysis for the selected top five compound–CD13 complexes. (a) RMSD, root mean square deviation. (b) RMSF, root mean square fluctuation. (c) R _g, radius of gyration. (d) SASA, solvent accessible surface area. (e) Hydrogen bonds interaction between CD13 and compounds.