The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Latest developments in molecular docking: 2010–2011 in review
Abstract
The aim of docking is to accurately predict the structure of a ligand within the constraints of a receptor binding site and to correctly estimate the strength of binding. We discuss, in detail, methodological developments that occurred in the docking field in 2010 and 2011, with a particular focus on the more difficult, and sometimes controversial, aspects of this promising computational discipline. The main developments in docking in this period, covered in this review, are receptor flexibility, solvation, fragment docking, postprocessing, docking into homology models, and docking comparisons. Several new, or at least newly invigorated, advances occurred in areas such as nonlinear scoring functions, using machine‐learning approaches. This review is strongly focused on docking advances in the context of drug design, specifically in virtual screening and fragment‐based drug design. Where appropriate, we refer readers to exemplar case studies. Copyright © 2013 John Wiley & Sons, Ltd.
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Trott, O., & Olson, A. J. (2010) · Journal of Computational Chemistry · doi:10.1002/jcc.21334 · Cited by 38,412
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
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
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
Systematic exploitation of multiple receptor conformations for virtual ligand screening.
Bottegoni, G., Rocchia, W., Rueda, M., Abagyan, R., & Cavalli, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018845 · Cited by 96
New Aryl Hydrocarbon Receptor Homology Model Targeted To Improve Docking Reliability
Motto, I., Bordogna, A., Soshilov, A. A., Denison, M. S., & Bonati, L. (2011) · Journal of Chemical Information and Modeling · doi:10.1021/ci2001617 · Cited by 80
Robust scoring functions for protein-ligand interactions with quantum chemical charge models.
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Wei, D., Zheng, H., Su, N., Deng, M., & Lai, L. (2010) · Journal of Chemical Information and Modeling · doi:10.1021/ci900463u · Cited by 22 · cited 1×
“[189] Speci fi cally, they used two parameters for describing the binding energy landscape: (i) energy gap (the difference between the binding energy of the native binding mode and the average binding energy of other binding modes), which accounts for the thermodynamic stability of binding; and (ii)…”
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Cited by
Wang, Z., Sun, H., Yao, X., Li, D., Xu, L., Li, Y., Tian, S., & Hou, T. (2016) · Physical Chemistry Chemical Physics · doi:10.1039/c6cp01555g · Cited by 946
Key Topics in Molecular Docking for Drug Design
Torres, P. H. M., Sodero, A. C. R., Jofily, P., & Silva-Jr, F. P. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20184574 · Cited by 641
Ramírez, D., & Caballero, J. (2018) · Molecules · doi:10.3390/molecules23051038 · Cited by 624
Guedes, I. A., Pereira, F. S. S., & Dardenne, L. E. (2018) · Frontiers in Pharmacology · doi:10.3389/fphar.2018.01089 · Cited by 331
Oncogenic protein interfaces: small molecules, big challenges
Nero, T. L., Morton, C. J., Holien, J. K., Wielens, J., & Parker, M. W. (2014) · Nature Reviews Cancer · doi:10.1038/nrc3690 · Cited by 312
Metadata
- Authors
- Yuriev, E., & Ramsland, P. A.
- Venue
- Journal of Molecular Recognition
- Publisher
- Wiley
- Published
- 2013-03-25
- Volume
- 26
- Issue
- 5
- Pages
- 215-239
- ISSN
- 0952-3499 (ISSN-L)
- 1099-1352
- OpenAlex
- W2112213938
- Cited by
- 344
- References
- 8
- FWCI
- 41.42
- Type
- journal article
- Language
- en
- Open access
- closed
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