The DOI matches its Crossref record; 247 of the 247 references it cites were found in a registry or an index.
Target Identification for Small Bioactive Molecules: Finding the Needle in the Haystack
Abstract
Identification and confirmation of bioactive small‐molecule targets is a crucial, often decisive step both in academic and pharmaceutical research. Through the development and availability of several new experimental techniques, target identification is, in principle, feasible, and the number of successful examples steadily grows. However, a generic methodology that can successfully be applied in the majority of the cases has not yet been established. Herein we summarize current methods for target identification of small molecules, primarily for a chemistry audience but also the biological community, for example, the chemist or biologist attempting to identify the target of a given bioactive compound. We describe the most frequently employed experimental approaches for target identification and provide several representative examples illustrating the state‐of‐the‐art. Among the techniques currently available, protein affinity isolation using suitable small‐molecule probes (pulldown) and subsequent mass spectrometric analysis of the isolated proteins appears to be most powerful and most frequently applied. To provide guidance for rapid entry into the field and based on our own experience we propose a typical workflow for target identification, which centers on the application of chemical proteomics as the key step to generate hypotheses for potential target proteins.
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Cites
1 retracted
Selective killing of cancer cells by a small molecule targeting the stress response to ROS
Raj, L., Ide, T., Gurkar, A. U., Foley, M., Schenone, M., Li, X., Tolliday, N. J., Golub, T. R., Carr, S. A., Shamji, A. F., et al. (2011) · Nature · doi:10.1038/nature10167 · Cited by 1,030
RetractedCox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
Universal sample preparation method for proteome analysis
Wiśniewski, J. R., Zougman, A., Nagaraj, N., & Mann, M. (2009) · Nature Methods · doi:10.1038/nmeth.1322 · Cited by 8,352
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950
A novel genetic system to detect protein–protein interactions
Fields, S., & Song, O.-K. (1989) · Nature · doi:10.1038/340245a0 · Cited by 6,114
Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., & Mann, M. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m200025-mcp200 · Cited by 5,574
Lamb, J., Crawford, E. D., Peck, D., Modell, J. W., Blat, I. C., Wrobel, M. J., Lerner, J., Brunet, J.-P., Subramanian, A., Ross, K. N., et al. (2006) · Science · doi:10.1126/science.1132939 · Cited by 5,257
Quantitative analysis of complex protein mixtures using isotope-coded affinity tags
Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., & Aebersold, R. (1999) · Nature Biotechnology · doi:10.1038/13690 · Cited by 4,683
Network pharmacology: the next paradigm in drug discovery
Hopkins, A. L. (2008) · Nature Chemical Biology · doi:10.1038/nchembio.118 · Cited by 4,622
Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B., Parker, K., Hattan, S., Khainovski, N., Pillai, S., Dey, S., Daniels, S., et al. (2004) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m400129-mcp200 · Cited by 4,401
Cited by
Polypharmacology by Design: A Medicinal Chemist’s Perspective on Multitargeting Compounds
Proschak, E., Stark, H., & Merk, D. (2019) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.8b00760 · Cited by 498
What has traditional Chinese medicine delivered for modern medicine?
Wang, J., Wong, Y.-K., & Liao, F. (2018) · Expert Reviews in Molecular Medicine · doi:10.1017/erm.2018.3 · Cited by 328
Thermal profiling reveals phenylalanine hydroxylase as an off-target of panobinostat
Becher, I., Werner, T., Doce, C., Zaal, E. A., Tögel, I., Khan, C. A., Rueger, A., Muelbaier, M., Salzer, E., Berkers, C. R., et al. (2016) · Nature Chemical Biology · doi:10.1038/nchembio.2185 · Cited by 251
He, B., Hoang, T. K., Wang, T., Ferris, M., Taylor, C. M., Tian, X., Luo, M., Tran, D. Q., Zhou, J., Tatevian, N., et al. (2017) · Journal of Experimental Medicine · doi:10.1084/jem.20160961 · Cited by 196
Chemoproteomics and Chemical Probes for Target Discovery
Drewes, G., & Knapp, S. (2018) · Trends in Biotechnology · doi:10.1016/j.tibtech.2018.06.008 · Cited by 132
Metadata
- Authors
- Ziegler, S., Pries, V., Hedberg, C., & Waldmann, H.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2013-02-18
- Volume
- 52
- Issue
- 10
- Pages
- 2744-2792
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W2118812289
- Cited by
- 466
- References
- 247
- FWCI
- 22.13
- Type
- journal article
- Language
- en
- Open access
- closed
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