Benchmarking AI-Based Co-Folding and Docking Models for Predicting Structures of Orthosteric and Allosteric Ligand–Protein Complexes

This Zenodo archive provides the datasets, model prediction outputs, evaluation results, figures, and scripts used in the study “Benchmarking AI-Based Co-Folding and Docking Models for Predicting Structures of Orthosteric and Allosteric Ligand–Protein Complexes: Decoding the Allosteric Blind Spot Using a Landscape-Guided Interpretable AI Framework.” The archive mirrors the directory structure required by the analysis pipeline and contains two datasets: an Orthosteric (Main) Dataset derived from the DynamicBind benchmark and an Allosteric Dataset derived from the Dunbrack Lab’s KinCoRe resource. All results reported in the manuscript are derived from these datasets. Protein and ligand structures are not included in this archive. All structures are publicly available from the RCSB Protein Data Bank and can be automatically downloaded using the provided scripts.