DeepBindBC is a deep learning based binary classifier for identifying native-like protein-ligand complexes
Extract pocket by known ligand(optional)
(Needed when user is not sure how to prepare protein pocket information)Submit a job
(One receptor against multiple ligand with known pocket, the protein name should be ????.pdb,the pocket name should be ????_pocket.pdb.) (The output summary file is summary_all.txt, column 1 is ligand name with its conformation id, column 2 is DeepBindBC's predicted possiblity value, column 3 is vina docking score)Submit a job
Fast finding out the type of ligands that prefer to binding with the given protein with known pocket (One receptor against 100 representative ligands from cluster of a FDA approved drug dataset, the protein name should be ????.pdb,the pocket name should be ????_pocket.pdb, and they should put in a folder named receptor and zipped, exactly as the following example) (The output summary file is summary_all.txt, column 1 is ligand name with its conformation id, column 2 is DeepBindBC's predicted possiblity value, column 3 is vina docking score)References
- A DEEP LEARNING METHOD AS A CORE COMPONENT OF VIRTUAL SCEENING PIPELINE WITH ITS APPLICATION IN PANCREATIC ALPHA-AMYLASE, Haiping Zhang, Tingting Zhang, Konda Mani Saravanan, Linbu Liao, Hao Wu, Haishan Zhang, Huiling Zhang, Yi Pan, Xuli Wu*, Yanjie Wei* (submitted)