Identification of phytochemical as a dual inhibitor of PI3K and mTOR: a structure-based computational approach

Abstract

Breast cancer is a common form of cancer that affects both men and women. One of the most common types of genomic flaws in cancer is the aberrations in the PI3K/AKT/mTOR pathway. The benefit of dual targeting PI3K as well as mTOR is that the kinase-positive feedback loops are more effectively inhibited. Therefore, in the current study, structure-based models like molecular docking, MM-GBSA, Qikprop, induced fit docking, simulated molecular dynamics (MD), and thermal MM-GBSA were used to identify the phytochemicals from the zinc 15 database, which may inhibit PI3K and mTOR. After docking the phytochemicals with PI3K (PDB 4FA6), ten ligands based on the docking score were selected, among which salvianolic acid C had the highest docking score. Hence, salvianolic acid A was also docked. All the ligands taken showed a binding energy of greater than - 30 kcal/mol. The predicted ADME showed that the ligands have druggable properties. By performing MD of the top five ligands and salvianolic acid A, it was found that ZINC000059728582, ZINC000257545754, ZINC000253532301, and salvianolic acid A form a stable complex with PI3K protein, among which ZINC000014690026 showed interaction with Val 882 for more than 89% of the time. Salvianolic acid A is already proven to suppress tumor growth in acute myeloid leukemia by inhibiting PI3K/AKT pathway, but the exact protein target is unknown. Therefore, the present study identifies new molecules and provides evidence for salvianolic acid A for dual inhibition. Further experiments must be performed both in vitro and in vivo to support the predictions of these computational tools.

Keywords: Molecular dynamics; PI3K/mTOR pathway; Salvianolic acid A; Structure-based computational approach.

Fig. 1

Superimposition of docked (blue) and co-crystallized ligand (green) pose of -2-amino-8-cyclopentyl-4-methyl-6-(1H-pyrazol-4-yl) pyrido[2,3-d] pyrimidin-7(8H)-one of PDB 4FA6 for validating of docking protocol, the observed RMSD was 0.2101

Fig. 2

3D poses of ligands with the protein used for MD simulation showing the hydrogen bond (yellow dotted line), Pi–Pi stacking (blue dotted line), Pi–cation (green dotted line), and salt bridge (lavender dotted line)

Fig. 3

RMSD plots of protein and ligand after MD simulation for 100 ns

Fig. 4

2D interaction diagram with protein–ligand contacts for 100 ns MD simulation in which green represents H-bonds, pink represents an Ionic bond, blue represents a water bridge, and gray represents hydrophobic interaction

Fig. 4

2D interaction diagram with protein–ligand contacts for 100 ns MD simulation in which green represents H-bonds, pink represents an Ionic bond, blue represents a water bridge, and gray represents hydrophobic interaction

Fig. 5

Ligand-binding energy of top five ligands and salvianolic acid A obtained from every 10th frame of 1002 frames after running 100 ns MD simulation