DynamicBind Protein Dynamic Complex Structure Prediction Dataset

This dataset is from the paperDynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model"The training and test sets of the paper were used to predict the dynamic docking of proteins. This paper was published by Zheng Shuangjia's research group at Shanghai Jiao Tong University in collaboration with StarPharmaceuticals, Sun Yat-sen University School of Pharmacy and Rice University in the United States. The research team proposed a geometric deep generative model DynamicBind designed for protein "dynamic docking", which can effectively adjust the protein conformation from the initial AlphaFold prediction to a holographic-like state, providing a new research paradigm based on deep learning that considers the dynamic changes of proteins for drug development in the post-AlphaFold era.

The original data used in the paper comes from a public dataset PDbbind2020The research data and processed training data generated in this study are available for download on this page.