scPDB-Enhanced: An expansion of scPDB including all experimentally observed binding sites
Abstract
Overview The scPDB is one of the most widely used datasets for training ligand binding site (LBS) predictors. However, it has a significant limitation: it includes only one ligand per structure, usually focusing on the primary orthosteric site and omitting other valid binding cavities. To overcome this, we cross-referenced scPDB entries with AHoJ-DB to identify all ligands, and thus all binding sites, experimentally observed across all available conformations of a given protein. By aggregating these observations, we provide a ground truth that includes sites often missed in the original dataset. Files Description 1. scPDB-sites.csv A list of individual binding sites. Each row represents a single site identified in a specific protein structure. Format: PDB_ID;Chain;Ligand_Name;Residue_Indices Example: 1uh5;B;NAD;104 105 106 110 111 112 131 134 167 168 169 170 215 ... Note: Ligand_Name=UNKNOWN denotes binding sites from the original scPDB dataset. The residue indices labelling is auth (i.e., auth_seq_id) 2. scPDB-train.csv The primary file for model training. This file merges all identified binding sites for each unique protein and maps them directly onto the primary sequence. Format: PDB_ID;Chain;Binding_Residues;Full_Sequence Note: Binding residues are listed as ResidueType + Index (e.g., G8) The residue indices use 0-based indexing, allowing for direct indexing into the sequence string (e.g., an index of 8 refers to the 9th position in the sequence). Example: 1uh5;B;G8 I9 G10 G14 Y15 ...;NEDICFIAGIGDTNGYGWGIAKEL...
Fields of Study & Subjects
Computational Drug Discovery Methods
Protein Structure and Dynamics
Machine Learning in Bioinformatics
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 1 January 2026
- Document type
- Dataset