Bioinformatics Advance Access originally published online on January 19, 2009
Bioinformatics 2009 25(5):615-620; doi:10.1093/bioinformatics/btp035
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The protein–small-molecule database, a non-redundant structural resource for the analysis of protein-ligand binding
1Department of Computer Science and 2Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada
*To whom correspondence should be addressed.
| Abstract |
|---|
Motivation: An enabling resource for drug discovery and protein function prediction is a large, accurate and actively maintained collection of protein/small-molecule complex structures. Models of binding are typically constructed from these structural libraries by generalizing the observed interaction patterns. Consequently, the quality of the model is dependent on the quality of the structural library. An ideal library should be non-biased and comprehensive, contain high-resolution structures and be actively maintained.
Results: We present a new protein/small-molecule database (the PSMDB) that offers a non-redundant set of holo PDB complexes. The database was designed to allow frequent updates through a fully automated process without manual annotation or filtering. Our method of database construction addresses redundancy at both the protein and the small-molecule level. By efficiently handling structures with covalently bound ligands, we allow our database to include a larger number of structures than previous methods. Multiple versions of the database are available at our web site, including structures of split complexes—the proteins without their binding ligands and the non-covalently bound ligands within their native coordinate frame.
Availability: http://compbio.cs.toronto.edu/psmdb
Contact: izharw{at}cs.toronto.edu; lilien{at}cs.toronto.edu
Associate Editor: Burkhard Rost
Received on November 17, 2008; revised on January 8, 2009; accepted on January 13, 2009
This article has been cited by other articles:
![]() |
I. Wallach and R. H. Lilien Prediction of sub-cavity binding preferences using an adaptive physicochemical structure representation Bioinformatics, June 15, 2009; 25(12): i296 - i304. [Abstract] [Full Text] [PDF] |
||||
