## 3 Results and Discussion
### Molecular Docking Studies  
Receptor-ligand molecular docking studies were conducted using Autodock Vina and FireDock. It has been shown that investigating binding affinity using multiple docking methods improves the reliability of results [54]. The purpose of these studies was to determine the optimal binding affinity upon docking of each of the peptides and peptide-polyphenyl conjugates with ER-\(\alpha\), EGFR, and PPAR-\(\alpha\). Binding affinities obtained from Autodock Vina between peptides or peptide-conjugates and receptors are shown in Table 4, while those obtained from FireDock are shown in Supplementary Information Table S1. From the data obtained from Autodock Vina, for ER-\(\alpha\), RMAMut1 (rosmarinic acid conjugated to Mutation 1 peptide); CGAMut4 (chlorogenic acid conjugated to Mutation 4 peptide), and GLAMut4 (galidic acid conjugated to Mutation 4 peptide) were found to have the highest binding affinities. According to FireDock results, the highest global energies were found to be for GLAMut4, followed by CGAMut2 (carnosic acid conjugated to Mutation 2 peptide) and CGAMut3 (chlorogenic acid conjugated to Mutation 3 peptide). These results indicate that conjugating with certain polyphenols likely increases the binding affinity of the ligands toward ER-\(\alpha\). For PPAR-\(\alpha\), the binding affinities were found to be relatively lower than the results obtained for ER-\(\alpha\). This is plausible due to differences in the binding pockets and their interactions with each of the ligands. Nevertheless, the highest binding affinity for PPAR-\(\alpha\) according to Autodock Vina was seen for RMAMut1, followed closely by GLAMut3 and RMAPep. Based on FireDock results, the highest global energy was found to be for CGAMut1, followed by CGAMut3 and GLAMut1. For the EGFR receptor, based on Autodock Vina results, the highest binding affinity was observed for pep at \(-9.5\) kcal/mol, though this was lower than that observed for the ER-\(\alpha\) (\(-10.0\) kcal/mol). The second-highest binding affinity was observed for RMAMut1, followed by CGAMut3. As per FireDock results, the highest global binding energy was found to be for RMAMut4 followed by CGAMut3 and GLAMut3. For PPAR-\(\alpha\), the point mutation of Tyr in position 1 to Phe improved binding affinity from \(-8.9\) kcal/mol to \(-9.1\) kcal/mol according to Autodock Vina results, whereas very marginal reduction was observed according to FireDock (\(-49.68\) to \(-49.55\) kcal/mol), indicating that Mut1 may potentially exhibit high binding affinity for PPAR-\(\alpha\). Mut4 and Mut3 exhibited the second and third highest global binding energy according to FireDock and a high binding affinity according to Autodock Vina as well, indicating that these peptides may have a fairly high binding affinity with PPAR-\(\alpha\). Thus, while there were some similarities in the results obtained from FireDock and AutoDock Vina, the results overall showed a selection of different compounds for each of the receptors. Given the variance in results based on the individual analysis of global energy as seen in  
Figure 1: Binding pocket analysis based on POCASA results (i) ER\(\alpha\); (ii) PPAR-\(\alpha\); (iii) EGFR. Shaded blue regions indicate binding pockets. the case of FireDock or estimate of free binding energy (kcal/mol), as seen in Autodock Vina, it is indicative that the software had dissimilarities between best proposed candidates. This is likely due to differences in the docking algorithms [55]. FireDock provides results from the global binding energy and takes into account electrostatic, Van der Waals, H-bond, and atomic contact energies. Autodock Vina uses a combination of knowledge-based and empirical scoring functions and is the summation of \(\Delta\)G gauss, \(\Delta\)Grepulsion, \(\Delta\)GHbond, \(\Delta\)Ghydrophobic, and \(\Delta\)Gtors, which is proportional to the number of rotatable bonds [56].