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One of the main challenges in the early stages of drug discovery is the computational assessment of protein-ligand binding affinity. Machine learning techniques can contribute to predicting this type of interaction. We may apply these techniques following two approaches. First, using the experimental structures for which affinity data is available. Second, using protein-ligand docking simulations. In this review, we describe recently published machine learning models based on crystal structures for which binding affinity and thermodyna