Recently-there-has-been-an-increasing-focus-on-the-application-of-machine-learning-to-improve-protein-ligand-docking-methods-such-as-the-construction-of-scoring-functions-and-the-prediction-of-binding-poses-Various-machine-learning-methods-and-hypoth

In recent times, there has been a growing interest in the use of machine learning techniques to enhance protein-ligand docking methods, including the development of scoring functions and the prediction of binding poses. Researchers are exploring different machine learning algorithms and hypotheses to model protein-ligand docking, with deep learning models based on neural networks demonstrating significant potential in this area. To ensure the reliability and objectivity of these proposed protein-ligand docking systems, it is crucial to subject them to rigorous evaluation on an impartial benchmark platform, utilizing distinct datasets for both calibration and validation.