The article introduces Deep Predictor of Binding Specificity (DeepPBS), a geometric deep-learning model designed to predict protein-DNA binding specificity from protein-DNA structures. DeepPBS can be applied to both experimental and predicted structures, and it provides interpretable protein heavy atom importance scores for interface residues. The model has been validated through mutagenesis experiments and has shown promising performance in predicting binding specificity for designed proteins targeting specific DNA sequences. DeepPBS offers a foundation for advancing our understanding of molecular interactions and guiding experimental designs and synthetic biology. The model captures the physicochemical and geometric contexts of protein-DNA interactions, allowing it to predict binding specificity across different protein families. DeepPBS can also be used to analyze molecular simulation trajectories and improve the design of protein-DNA complexes. The article discusses the limitations and future potential of DeepPBS, highlighting its role in computational studies of molecular interactions and synthetic biology.The article introduces Deep Predictor of Binding Specificity (DeepPBS), a geometric deep-learning model designed to predict protein-DNA binding specificity from protein-DNA structures. DeepPBS can be applied to both experimental and predicted structures, and it provides interpretable protein heavy atom importance scores for interface residues. The model has been validated through mutagenesis experiments and has shown promising performance in predicting binding specificity for designed proteins targeting specific DNA sequences. DeepPBS offers a foundation for advancing our understanding of molecular interactions and guiding experimental designs and synthetic biology. The model captures the physicochemical and geometric contexts of protein-DNA interactions, allowing it to predict binding specificity across different protein families. DeepPBS can also be used to analyze molecular simulation trajectories and improve the design of protein-DNA complexes. The article discusses the limitations and future potential of DeepPBS, highlighting its role in computational studies of molecular interactions and synthetic biology.