The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A new test set for validating predictions of protein–ligand interaction
Abstract
We present a large test set of protein–ligand complexes for the purpose of validating algorithms that rely on the prediction of protein–ligand interactions. The set consists of 305 complexes with protonation states assigned by manual inspection. The following checks have been carried out to identify unsuitable entries in this set: (1) assessing the involvement of crystallographically related protein units in ligand binding; (2) identification of bad clashes between protein side chains and ligand; and (3) assessment of structural errors, and/or inconsistency of ligand placement with crystal structure electron density. In addition, the set has been pruned to assure diversity in terms of protein–ligand structures, and subsets are supplied for different protein‐structure resolution ranges. A classification of the set by protein type is available. As an illustration, validation results are shown for GOLD and SuperStar. GOLD is a program that performs flexible protein–ligand docking, and SuperStar is used for the prediction of favorable interaction sites in proteins. The new CCDC/Astex test set is freely available to the scientific community (http://www.ccdc.cam.ac.uk). Proteins 2002;49:457–471. © 2002 Wiley‐Liss, Inc.
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Development and validation of a genetic algorithm for flexible docking 1 1Edited by F. E. Cohen
Jones, G., Willett, P., Glen, R. C., Leach, A. R., & Taylor, R. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0897 · Cited by 6,763
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Kellenberger, E., Rodrigo, J., Muller, P., & Rognan, D. (2004) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.20149 · Cited by 577
Molecular complexes at a glance: automated generation of two-dimensional complex diagrams
Stierand, K., Maaß, P. C., & Rarey, M. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl150 · Cited by 423
Modeling water molecules in protein-ligand docking using GOLD.
Verdonk, M. L., Chessari, G., Cole, J. C., Hartshorn, M. J., Murray, C. W., Nissink, J. W. M., Taylor, R. D., & Taylor, R. (2005) · Journal of Medicinal Chemistry · doi:10.1021/jm050543p · Cited by 393
Self-citationDamm-Ganamet, K. L., Smith, R. D., Dunbar, J. B., Stuckey, J. A., & Carlson, H. A. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci400025f · Cited by 133
Predicting the accuracy of protein–ligand docking on homology models
Bordogna, A., Pandini, A., & Bonati, L. (2011) · Journal of Computational Chemistry · doi:10.1002/jcc.21601 · Cited by 107
Scoring Functions for Protein–Ligand Interactions
Sotriffer, C. (2012) · Protein‐Ligand Interactions · doi:10.1002/9783527645947.ch12 · Cited by 16
The Basis for Target‐Based Virtual Screening: Protein Structures
Cole, J. C., Korb, O., Olsson, T. S. G., & Liebeschuetz, J. (2011) · Methods and principles in medicinal chemistry · doi:10.1002/9783527633326.ch4 · Cited by 9
Metadata
- Authors
- Nissink, J. W. M., Murray, C., Hartshorn, M., Verdonk, M. L., Cole, J. C., & Taylor, R.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2002-10-08
- Volume
- 49
- Issue
- 4
- Pages
- 457-471
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2138473864
- Cited by
- 425
- References
- 1
- FWCI
- 20.87
- Type
- journal article
- Language
- en
- Open access
- closed
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