The in silico toxicity assessment suggests a favorable safety profile for PMMA and MMA, but clinical reports sometimes highlight adverse reactions (e.g., residual monomer leaching). How do you reconcile your computational results with these clinical observations? Are there specific experimental conditions or patient factors that might explain this discrepancy?
You selected receptors like RANKL and BMPs based on their roles in bone metabolism, but the oral environment involves dynamic interactions with immune cells, bacteria, and mechanical stress. How confident are you that these targets fully capture PMMA’s biocompatibility in vivo, particularly in scenarios like chronic inflammation or biofilm formation?
Your pharmacophore analysis identifies carbonyl and hydroxyl groups as key for interactions, but PMMA’s performance in dentistry also depends on mechanical properties. How do these molecular insights translate into practical material design, especially for load-bearing interim restorations?
Your MD simulations ran for 100 ns, which is relatively short for polymer degradation or chronic exposure scenarios. How might longer timescales or repeated stress cycles (e.g., chewing forces) affect your conclusions about PMMA’s stability?
How do your docking scores and binding affinities for PMMA compare to other common dental materials (e.g., bis-acryl composites)? Without such comparisons, it’s hard to gauge whether PMMA is truly optimal or just one of many viable options.
You mention BPA derivatives as a concern in PMMA production, but your toxicity screening didn’t flag them. Could this be due to limitations in the in silico tools used? How would you address potential endocrine-disrupting effects in practice?
Biocompatibility can vary based on patient genetics or oral microbiome differences. Do your models account for such variability, or are they based on “average” conditions that might not reflect all clinical cases?