Artificial intelligence-based behavioral analysis of protein in a nanoscale cubic space on a Si substrate

Special behaviors of proteins have been exploited and used for biomedical devices and biosensors; fundamentally, the behavior of proteins on solid surfaces is fascinating. However, no comprehensive understanding has been garnered from current studies. In our study, the behavior of tetrapeptides in active sites of papain in a nanoscale cubic space on a solid surface was analyzed using a synergistic combination of artificial intelligence and computer simulations. After identifying suitable tetrapeptides, half of them were deemed not suitable for free papain adsorption. A nanoscale cubic space enabled novel functions of those proteins to be captured. Additionally, the decision tree identified attributes that governed suitability. The decision tree would be an effective tool to comprehend the big picture of the complex behavior.