The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Virtual ligand screening: strategies, perspectives and limitations
Open accessAbstract
In contrast to high-throughput screening, in virtual ligand screening (VS), compounds are selected using computer programs to predict their binding to a target receptor. A key prerequisite is knowledge about the spatial and energetic criteria responsible for protein–ligand binding. The concepts and prerequisites to perform VS are summarized here, and explanations are sought for the enduring limitations of the technology. Target selection, analysis and preparation are discussed, as well as considerations about the compilation of candidate ligand libraries. The tools and strategies of a VS campaign, and the accuracy of scoring and ranking of the results, are also considered.
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Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(00)00129-0 · Cited by 18,139
Friesner, R. A., Banks, J. L., Murphy, R. B., Halgren, T. A., Klicic, J. J., Mainz, D. T., Repasky, M. P., Knoll, E. H., Shelley, M., Perry, J. K., et al. (2004) · Journal of Medicinal Chemistry · doi:10.1021/jm0306430 · Cited by 10,057
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
ZINC − A Free Database of Commercially Available Compounds for Virtual Screening
Irwin, J. J., & Shoichet, B. K. (2005) · Journal of Chemical Information and Modeling · doi:10.1021/ci049714+ · Cited by 4,058
Hopkins, A. L., & Groom, C. R. (2002) · Nature Reviews Drug Discovery · doi:10.1038/nrd892 · Cited by 3,305
Principles of docking: An overview of search algorithms and a guide to scoring functions
Halperin, I., Ma, B., Wolfson, H., & Nussinov, R. (2002) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10115 · Cited by 1,294
Comparative evaluation of 11 scoring functions for molecular docking.
Wang, R., Lu, Y., & Wang, S. (2003) · Journal of Medicinal Chemistry · doi:10.1021/jm0203783 · Cited by 849
Implications of protein flexibility for drug discovery
Teague, S. J. (2003) · Nature Reviews Drug Discovery · doi:10.1038/nrd1129 · Cited by 755
Charifson, P. S., Corkery, J. J., Murcko, M. A., & Walters, W. P. (1999) · Journal of Medicinal Chemistry · doi:10.1021/jm990352k · Cited by 698
Comparative evaluation of eight docking tools for docking and virtual screening accuracy
Kellenberger, E., Rodrigo, J., Muller, P., & Rognan, D. (2004) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.20149 · Cited by 577
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Enumeration of 166 Billion Organic Small Molecules in the Chemical Universe Database GDB-17
Ruddigkeit, L., van Deursen, R., Blum, L. C., & Reymond, J.-L. (2012) · Journal of Chemical Information and Modeling · doi:10.1021/ci300415d · Cited by 1,505
Halogen atoms in the modern medicinal chemistry: hints for the drug design
Hernandes, M., Cavalcanti, S. M., Moreira, D. R., de Azevedo Junior, W., & Leite, A. C. (2010) · Current Drug Targets · doi:10.2174/138945010790711996 · Cited by 723
Computer-aided drug discovery and development (CADDD): in silico-chemico-biological approach
Kapetanovic, I. M. (2008) · Chemico-Biological Interactions · doi:10.1016/j.cbi.2006.12.006 · Cited by 662
Efficient Drug Lead Discovery and Optimization
Jorgensen, W. L. (2009) · Accounts of Chemical Research · doi:10.1021/ar800236t · Cited by 649
Moitessier, N., Englebienne, P., Lee, D., Lawandi, J., & Corbeil, C. R. (2008) · British Journal of Pharmacology · doi:10.1038/sj.bjp.0707515 · Cited by 514
Metadata
- Authors
- Klebe, G.
- Venue
- Drug Discovery Today
- Publisher
- Elsevier BV
- Published
- 2006-07
- Volume
- 11
- Issue
- 13-14
- Pages
- 580-594
- ISSN
- 1359-6446 (ISSN-L)
- OpenAlex
- W2015461838
- Cited by
- 664
- References
- 11
- FWCI
- 43.39
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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