The selected bioactive compounds, which conformed to the Lipinski rule of five (Table ), were subjected to molecular dynamics (MD) simulation for 100 ns in the Desmond package (Figure ). The Root Mean Square Deviation (RMSD) analysis helps to estimate how stable a compound is in the binding pocket of a protein. In addition, it calculates the average change of displacement of the protein-ligand complex during the simulation. In this study (Figure ), the RMSD values for all four ligands are stable and < 4 Å during the 100 ns simulation trajectories. (+) -Catechin (Cianidanol) displayed a stable value of 0.4 Å to 1.6 Å at 0 ns to 75 ns, followed by a slight elevation which became stable at 85 ns to 100 ns. Arbutin revealed stability from 0.45 Å to 2.8 Å from 0 ns to 100 ns with a short-lived fluctuation to 3.3 Å. Resveratrol displays from 0.45 Å to 1.8 Å from 0 ns to 25 ns, fluctuated and became stable at 1Å to 1.65 Å from 25 ns to 100 ns. Sinapic acid shows stability from 1.2 Å to 2.4 Å from 20 ns to 100 ns. Essentially, the four ligands showed better RMSD values than Sotorasib, as they were more stable and had lesser fluctuations. The Cα atoms in the PDE6D docked with the ligands in this study showed mean deviation <4 Å which is acceptable for small globular proteins.