where α is a weighting factor, 𝛾 is the focusing parameter and 𝒑 𝒕 is an estimate of the probability for the true class, typically given by the number of correct poses over the total number of poses in the training set. Minimizing 𝑳𝒐𝒔𝒔 𝒏 enables the model to correctly predict the likelihood of binding pose. 𝑳𝒐𝒔𝒔 𝒈 and 𝒘 𝟏 are the loss function and weight for graph-level task, respectively, where 𝑳𝒐𝒔𝒔 𝒈 corresponds to the root mean square error (RMSE) :