Targeting p38α, p38γ, and ERα with bioactive compounds from royal jelly for anti-breast cancer activity: A comprehensive in-silico study using fingerprint analysis, molecular dynamics, MEP, and PCA.

Studying receptors that play critical roles in breast cancer continues to present various challenges. In silico computation has emerged as an effective solution to overcome these limitations by enabling the exploration of protein structure, dynamics, and function. Therefore, a comprehensive in silico approach was employed in this study, incorporating Ramachandran plot analysis, fingerprint study, active site prediction, molecular electrostatic potential (for selected molecules), a combination of molecular docking and molecular dynamics (for receptor-ligand complexes), and protein contact analysis (for receptor-ligand complexes). The results revealed that p38α, p38γ, and ERα were structurally suitable for investigation and were successfully characterized through fingerprint analysis and binding pocket prediction. The combination of docking and molecular dynamics demonstrated strong stability in the p38α-chrysin, p38γ-galangin, and ERα-naringin complexes. Hence, this study identified and characterized these three target receptors and proposed lead molecules with potential anti-breast cancer activity. However, comprehensive experimental validation at the laboratory scale remains necessary.