IAP-CFDock: Iterative Anchor Prediction and Coarse-to-Fine Protein-Ligand Blind Docking

Protein-ligand blind docking refers to predicting the docking conformation of a ligand with a complete protein, which is crucial for drug discovery. However, the large size of complete proteins, coupled with the complexity of their structures, makes this task highly challenging. To address these issues, we propose a novel blind docking framework, IAP-CFDock, which consists of three stages: Iterative Anchor Prediction, Coarse Docking, and Fine-Grained Docking. To enable high-accuracy anchor prediction, we design an efficient protein-ligand interaction network, termed the AP Layer. Experimental results show that the anchor prediction mechanism exhibits strong robustness, high accuracy, and flexibility. Comprehensive comparisons across multiple data sets and experimental settings demonstrate that IAP-CFDock achieves superior docking accuracy and generalization capability while maintaining high inference efficiency. Furthermore, we investigate the docking performance of various blind docking methods across different ligand sizes. Finally, extensive ablation studies validate the effectiveness of each component in IAP-CFDock and highlight its strong potential for further improvement.