The DOI matches its Crossref record.
Chemical screening methods to identify ligands that promote protein stability, protein crystallization, and structure determination
Abstract
The 3D structures of human therapeutic targets are enabling for drug discovery. However, their purification and crystallization remain rate determining. In individual cases, ligands have been used to increase the success rate of protein purification and crystallization, but the broad applicability of this approach is unknown. We implemented two screening platforms, based on either fluorimetry or static light scattering, to measure the increase in protein thermal stability upon binding of a ligand without the need to monitor enzyme activity. In total, 221 different proteins from humans and human parasites were screened against one or both of two sorts of small-molecule libraries. The first library comprised different salts, pH conditions, and commonly found small molecules and was applicable to all proteins. The second comprised compounds specific for protein families of particular interest (e.g., protein kinases). In 20 cases, including nine unique human protein kinases, a small molecule was identified that stabilized the proteins and promoted structure determination. The methods are cost-effective, can be implemented in any laboratory, promise to increase the success rates of purifying and crystallizing human proteins significantly, and identify new ligands for these proteins.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Monitoring Drug Target Engagement in Cells and Tissues Using the Cellular Thermal Shift Assay
Molina, D. M., Jafari, R., Ignatushchenko, M., Seki, T., Larsson, E. A., Dan, C., Sreekumar, L., Cao, Y., & Nordlund, P. (2013) · Science · doi:10.1126/science.1233606 · Cited by 2,261
Self-citationTracking cancer drugs in living cells by thermal profiling of the proteome
Savitski, M. M., Reinhard, F. B. M., Franken, H., Werner, T., Savitski, M. F., Eberhard, D., Molina, D. M., Jafari, R., Dovega, R. B., Klaeger, S., et al. (2014) · Science · doi:10.1126/science.1255784 · Cited by 1,187
Self-citationSmall molecule inhibition of the KRAS–PDEδ interaction impairs oncogenic KRAS signalling
Zimmermann, G., Papke, B., Ismail, S., Vartak, N., Chandra, A., Hoffmann, M., Hahn, S. A., Triola, G., Wittinghofer, A., Bastiaens, P. I. H., et al. (2013) · Nature · doi:10.1038/nature12205 · Cited by 596
Proteome Integral Solubility Alteration: A High-Throughput Proteomics Assay for Target Deconvolution
Gaetani, M., Sabatier, P., Saei, A. A., Beusch, C. M., Yang, Z., Lundström, S. L., & Zubarev, R. A. (2019) · Journal of Proteome Research · doi:10.1021/acs.jproteome.9b00500 · Cited by 287
Harriman, G., Greenwood, J., Bhat, S., Huang, X., Wang, R., Paul, D., Tong, L., Saha, A. K., Westlin, W. F., Kapeller, R., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1520686113 · Cited by 287
ROR nuclear receptors: Structures, related diseases, and drug discovery
Zhang, Y., Luo, X.-Y., Wu, D.-H., & Xu, Y. (2015) · Acta Pharmacologica Sinica · doi:10.1038/aps.2014.120 · Cited by 151
Lorca, G. L., Ezersky, A., Lunin, V. V., Walker, J. R., Altamentova, S., Evdokimova, E., Vedadi, M., Bochkarev, A., & Savchenko, A. (2007) · Journal of Biological Chemistry · doi:10.1074/jbc.m610838200 · Cited by 87
Self-citationJackson, T. W., Scheibly, C. M., Polera, M. E., & Belcher, S. M. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.1c01200 · Cited by 87
Chemical denaturation as a tool in the formulation optimization of biologics
Freire, E., Schön, A., Hutchins, B. M., & Brown, R. K. (2013) · Drug Discovery Today · doi:10.1016/j.drudis.2013.06.005 · Cited by 66
On the Mechanism of Action of SJ-172550 in Inhibiting the Interaction of MDM4 and p53
Bista, M., Smithson, D., Pecak, A., Salinas, G., Pustelny, K., Min, J., Pirog, A., Finch, K., Zdzalik, M., Waddell, B., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037518 · Cited by 58
Kadriu, E., Qin, S., Prezioso, S. M., & Christendat, D. (2026) · Microbiological Research · doi:10.1016/j.micres.2025.128382 · Cited by 2
Metadata
- Authors
- Vedadi, M., Niesen, F. H., Allali-Hassani, A., Fedorov, O. Y., Finerty, P. J., Wasney, G. A., Yeung, R., Arrowsmith, C., Ball, L. J., Berglund, H., Hui, R., Marsden, B. D., Nordlund, P., Sundstrom, M., Weigelt, J., & Edwards, A. M.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2006-10-24
- Volume
- 103
- Issue
- 43
- Pages
- 15835-15840
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2039377812
- Cited by
- 589
- References
- 0
- FWCI
- 18.01
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
