The PDBbind database: collection of binding affinities for protein-ligand complexes with known three-dimensional structures.
By Renxiao Wang, Xueliang Fang, Yipin Lu, Shaomeng Wang. 2004
1,058 citations recorded by the source corpus.
Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology, Evaluation & Benchmarks, Computational Chemistry & Drug Discovery
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In Computational Theory and Mathematics
- Stephen H. Bryant
- Evan E. Bolton
- Sunghwan Kim
- Yang Zhang
- Jianyi Yang
- Ron O. Dror
- Jian Zhang
- Jiyao Wang
In Materials Chemistry
- Jianyi Yang
- Yang Zhang
- Ambrish Roy
- Evan E. Bolton
- Stephen H. Bryant
- Ron O. Dror
- Stephan Eismann
- Raphael J. L. Townshend
In Molecular Biology
- Yang Zhang
- Jianyi Yang
- Ambrish Roy
- Stephen H. Bryant
- Evan E. Bolton
- Ron O. Dror
- Jens Meiler
- Robin Pearce
In Evaluation & Benchmarks
- Giulio Rastelli
- Luca Pinzi
- F. Silva-Jr
- Paula Jofily
- Russ B. Altman
- Raphael J. L. Townshend
- Stephan Eismann
- Rafael Gómez‐Bombarelli
In Computational Chemistry & Drug Discovery
- Ron O. Dror
- Stephan Eismann
- Raphael J. L. Townshend
- Brandon M. Anderson
- Jens Meiler
- Gerhard Klebe
- F. Silva-Jr
- Paula Jofily
Citations in the corpus
- BindingDB: a web-accessible database of experimentally determined protein–ligand binding affinities (2006, background): “Thus, BindingDB’s data collection differs significantly from those of databases which only collect affinities for protein–ligand complexes in the PDB, notably BindingMOAD (10) which holds 1400 data, PDBBind (11,12) with 1600 data, and AffinDB (13) with 750 data.”
- Computational Methods in Drug Discovery (2014, methodology): “For example, the PDB has over 81,000 protein structures, whereas data bases such as PDBBIND (Wang et al., 2004) and protein ligand data base house 5,671 and 129 (as of 2003) ligand-protein cocrystal structures, respectively.”
- PharmMapper server: a web server for potential drug target identification using pharmacophore mapping approach (2010, methodology): “DrugBank hosts a complete list of known targets with appropriate annotations, while BindingDB and PDBBind provide public, web-accessible databases of measured binding affinities, focusing chiefly on the interactions of those proteins considered to be drug targets with small or drug-like molecules.”
- Deep learning with feature embedding for compound-protein interaction prediction (2016, background): “1 Performance evaluation on compound-protein interactions Databases like ChEMBL [36], BindingDB [48] and PDBbind-CN [49] [50] [51] have collected a large amount of binding profiles (e.”
- A Review of Deep Learning Methods for Antibodies (2020, methodology): “Updated annually, the PDBbind database currently contains solved structures for 2594 protein–protein complexes extracted from the PDB, along with binding affinity data for each complex [56].”