Abstract
Abstract
Endometriosis is a gynecological disorder, characterized by debilitating pain and commonly associated with infertility. Medical therapies are often ineffective, with 25–34% of patients exhibit no or poor response, and many experiencing intolerable side effects that limit long term use. P300 is a critical histone acetyltransferase that promotes inflammation and invasion through epigenetic modulation of immune cells, and upregulation of pro-inflammatory gene expression. In this study, we aimed to identify potential inhibitors of p300 for treating endometriosis using computational drug repurposing. We performed a molecular docking-based virtual screening of 2,083 Food and Drug Administration (FDA) approved drugs against the crystal structure of p300 ligand-binding domain, followed by molecular dynamics (MD) simulations and Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA) analysis to further assess the stability and the binding interactions of the top-ranked drugs. Three compounds, Naldemedine, Bictegravir and Zavegepant, exhibited favorable docking affinities and interaction profiles. Further evaluation using 300 ns molecular dynamics simulations and MM-PBSA analyses demonstrated that Bictegravir exhibited the most favorable binding in complex with p300. Lastly, these findings underscore the potential of bioinformatics approaches in providing valuable resources and novel perspective on therapeutic strategies that are often overlooked in the context of endometriosis.