The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.
The FTMap family of web servers for determining and characterizing ligand-binding hot spots of proteins
Open accessAbstract
FTMap is a computational mapping server that identifies binding hot spots of macromolecules—i.e., regions of the surface with major contributions to the ligand-binding free energy. To use FTMap, users submit a protein, DNA or RNA structure in PDB (Protein Data Bank) format. FTMap samples billions of positions of small organic molecules used as probes, and it scores the probe poses using a detailed energy expression. Regions that bind clusters of multiple probe types identify the binding hot spots in good agreement with experimental data. FTMap serves as the basis for other servers, namely FTSite, which is used to predict ligand-binding sites, FTFlex, which is used to account for side chain flexibility, FTMap/param, used to parameterize additional probes and FTDyn, for mapping ensembles of protein structures. Applications include determining the druggability of proteins, identifying ligand moieties that are most important for binding, finding the most bound-like conformation in ensembles of unliganded protein structures and providing input for fragment-based drug design. FTMap is more accurate than classical mapping methods such as GRID and MCSS, and it is much faster than the more-recent approaches to protein mapping based on mixed molecular dynamics. By using 16 probe molecules, the FTMap server finds the hot spots of an average-size protein in <1 h. As FTFlex performs mapping for all low-energy conformers of side chains in the binding site, its completion time is proportionately longer.
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Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196
Development and testing of a general amber force field
Wang, J., Wolf, R. M., Caldwell, J. W., Kollman, P. A., & Case, D. A. (2004) · Journal of Computational Chemistry · doi:10.1002/jcc.20035 · Cited by 19,506
CHARMM: A program for macromolecular energy, minimization, and dynamics calculations
Brooks, B. R., Bruccoleri, R. E., Olafson, B. D., States, D. J., Swaminathan, S., & Karplus, M. (1983) · Journal of Computational Chemistry · doi:10.1002/jcc.540040211 · Cited by 14,944
Automatic atom type and bond type perception in molecular mechanical calculations
Wang, J., Wang, W., Kollman, P. A., & Case, D. A. (2006) · Journal of Molecular Graphics and Modelling · doi:10.1016/j.jmgm.2005.12.005 · Cited by 5,477
Jakalian, A., Jack, D. B., & Bayly, C. I. (2002) · Journal of Computational Chemistry · doi:10.1002/jcc.10128 · Cited by 3,426
Goodford, P. J. (1985) · Journal of Medicinal Chemistry · doi:10.1021/jm00145a002 · Cited by 2,634
Anatomy of hot spots in protein interfaces
Bogan, A. A., & Thorn, K. S. (1998) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.1843 · Cited by 1,988
A Hot Spot of Binding Energy in a Hormone-Receptor Interface
Clackson, T., & Wells, J. A. (1995) · Science · doi:10.1126/science.7529940 · Cited by 1,983
Identifying and Characterizing Binding Sites and Assessing Druggability
Halgren, T. A. (2009) · Journal of Chemical Information and Modeling · doi:10.1021/ci800324m · Cited by 1,759
Guerois, R., Nielsen, J. E., & Serrano, L. (2002) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)00442-4 · Cited by 1,728 · cited 1×
“A variety of computational methods have been developed for the prediction of hot spot residues 7,51–54 , originally defined as those in the protein-protein interface that give rise to a substantial drop in binding affinity when mutated to alanine.”
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Predicting Protein–Protein Interactions from the Molecular to the Proteome Level
Keskin, O., Tuncbag, N., & Gursoy, A. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00683 · Cited by 369
Targeting protein–protein interactions, a wide open field for drug design
Bakail, M., & Ochsenbein, F. (2016) · Comptes Rendus. Chimie · doi:10.1016/j.crci.2015.12.004 · Cited by 117
Covalent targeting of acquired cysteines in cancer
Visscher, M., Arkin, M. R., & Dansen, T. B. (2016) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2015.11.004 · Cited by 95
Structure-based prediction of protein allostery
Greener, J. G., & Sternberg, M. J. (2018) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2017.10.002 · Cited by 91
Liu, X., Taylor, R. D., Griffin, L., Coker, S.-F., Adams, R., Ceska, T., Shi, J., Lawson, A. D. G., & Baker, T. (2017) · Scientific Reports · doi:10.1038/srep41306 · Cited by 39
Metadata
- Authors
- Kozakov, D., Grove, L. E., Hall, D. R., Bohnuud, T., Mottarella, S. E., Luo, L., Xia, B., Beglov, D., & Vajda, S.
- Venue
- Nature Protocols
- Published
- 2015-04-09
- Volume
- 10
- Issue
- 5
- Pages
- 733-755
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- OpenAlex
- W2062051632
- Cited by
- 648
- References
- 83
- FWCI
- 45.25
- Type
- journal article
- Language
- en
- Open access
- green
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