Towards identification of therapeutics against multi-infections and cancers causing Propionibacterium acnes: Molecular modeling and dynamics simulation investigation

Abstract

Skin conditions related to Propionibacterium acnes are a noteworthy health concern affecting millions globally. However, recent studies suggest that P. acne is also linked to other serious health conditions such as various kinds of cancer such as prostate cancer, breast cancer, and gastric cancer. The P. acnes sialidase enzyme plays an important role in the pathogenesis of this infection by supporting bacterial invasion and adhesion to the host tissues. In the current study, Medicinal Fungi Secondary Metabolites and Therapeutics (MeFSAT) consisting of 1830 compounds were put through comprehensive computational analysis to identify the strongest inhibitors that target the primary pathogenic enzyme that triggers the dermal infection. Upon analyzing docking studies, it is anticipated that most of these compounds are strongly attached to the specific protein vital for bacterial infection based on their binding score (threshold < −7 kcal/mol). The top 3 compounds were selected as MSID000006, MSID000010, and MSID000012 as strong inhibitors based on their binding score. Furthermore, every compound showed an excellent ADMET profile and adhered to Lipinski’s rule. Next, Density Functional Theory (DFT) analysis was carried out to analyze compounds’ optimized structures and electrostatic interactions with high accuracy. Subsequently, molecular dynamics simulations (MDS) were carried out to evaluate compound stability. The particular compounds showed better stability under a dynamic environment. Furthermore, principal component analysis (PCA) and hydrogen bond analysis was carried out to understand the complexity of vast datasets and the stability of the compounds respectively. Moreover, in salt bridge analysis, Asp-Arg were the most observed interactions, suggesting better electrostatic interaction and good stability. Secondary structure analysis was conducted for better comprehension of protein structure. MMPBSA/GBSA analysis was performed to calculate the free energies of simulation trajectories as MSID000006 favorable binding energy as compared to the MSID000010 and MSID000012. WaterSwap validated the MMPBSA findings by calculating the binding free energies of the compounds upon swapping the water molecule with the ligand. In the end, entropy energy was estimated to figure out the disorder in the process. The entropy results showed that MSID00006 has greater stability as compared to MSID000010 due to lesser disorder in the process. Our findings revealed the compounds MSID000006, MSID000010, and MSID000012 could play favorable roles in the management of P. acnes disease by showing their potential as strong inhibitors.