## 4 Discussion
An experiment into molecular coupling with the targeted protein ER\(\alpha\) (PDB ID: 3 ERT) included the selection of 83 naturally occurringbioactive chemicals from _Croton bonplandianum_ together with a control drug. Olaparib (CID-23725625), as a control drug, developed a binding affinity of \(-7.9\) kcal/mol. Table 4 shows the binding affinity values of 2,3-oxidosqualene (CID-5366020), 5,8,11-eicosatriynoic acid, trimethylsilyl ester (CID-91696396), 1-Monolinolein (CID-250006068), and 2, 4-Diertert-butylphenol (CID-7311) among the natural bioactive compounds selected from _Croton bonplandianum_. These values are \(-8.6\) kcal/mol, \(-8.2\) kcal/mol, \(-8.2\) kcal/mol, and \(-7.8\) kcal/mol, respectively. In the subsequent step, Maestro post-docking visualization tool was utilized to analyze the 2D protein-ligand interaction visualization. The state-of-the-art visualizer program BIOVIA Discovery Studio (v19.1.0.18287) also assisted in creating images of the docked receptor-ligand interactions (Figure 1). Furthermore, dynamic trajectory analysis performance data, also known as molecular dynamic simulation (MDS), can aid in facilitating the development of novel therapeutics [60; 61; 62]. In this experiment, we performed 100 ns MDS using the given physiological and physicochemical parameters by utilizing the Desmond Application, a Schrodinger package program. This simulation trajectory was also utilized to analyze the RMSD, RMSF, Rg, hydrogen bond number, and SASA perfectly [63]. The reliability of the protein structure was evaluated, and conformational variations were identified using the alpha carbon and backbone of the selected 3 ERT model protein; the lower value denotes the more stable molecule. The significant structural stability of the protein-ligands combined structures is frequently indicated by RMSD values less than 3.5. Our study's findings demonstrated that the RMSD values of the protein-ligand interactions fell within an appropriate range, specifically the average mean value of 3.5, suggesting a more effective docking position and proving that the protein-ligand structure did not exhibit severe fluctuations during the 100 ns molecular dynamics simulation study (Figure 2). RMSF is essential for monitoring local protein modifications since it computes the mean change seen among the atoms and assesses the displacement of an individual atom with respect to the reference structure. To assess the impact of attaching specific ligand molecules to residue positions, we need to measure the alteration in the flexibility of the protein structure. An RMSF graph shows how typical protein fluctuations are a sign of changes at the residue level. The RMSF allows one to calculate typical protein fluctuations from a constant reference point. Figure 3 shows the RMSF for the protein's C-alpha atoms. The structural stability was evaluated by determining the total number of intermolecular bonds formed between the macromolecule and its ligand compounds. All the selected ligand compounds have a greater number of intramolecular bonds and a more stable conformation than the control drug olaparib (CID-23725625). Along with measuring the size shifts of the drug-like compounds, the solvent-accessible surface area (SASA) of the protein ligands was calculated [64]. Structural instability is a result of hydrophobic amino acid residues being close to the water molecule, which raises the SASA value [65]. The presence of hydrophobic amino acid residues near water molecules induces structural instability, leading to an increase in the SASA value (Figure 5). Validation data for MolSA and PSA demonstrated that each ligand molecule exhibits greater significance compared to the control drug (Figures 6 and 7). Moreover, Rg measurement provides additional insights into the folding properties of the protein and can evaluate the compactness of the protein molecule [66]. Furthermore, a high Rg value indicates slackpacking, while a low Rg value indicates tight packing [67].