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This study utilizes machine learning techniques to identify potential natural inhibitors for Non-Small Cell Lung Cancer (NSCLC) by targeting the NTRK protein. The Random Forest model achieved a high accuracy of 93.12%, screening 9000 chemicals and discovering 65 potential inhibitors, with molecular dynamics simulations confirming their stable interactions with NTRK. The research emphasizes the importance of integrating computational and experimental methods in drug discovery, highlighting the promise of mac

Author

jha.vicky.06082003

Language

EN