The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Comprehensive analysis of loops at protein-protein interfaces for macrocycle design
Open accessAbstract
Inhibiting protein-protein interactions (PPIs) with synthetic molecules remains a frontier of chemical biology. Many PPIs have been successfully targeted by mimicking α-helices at interfaces, but most PPIs are mediated by non-helical, non-strand peptide loops. We sought to comprehensively identify and analyze these loop-mediated PPIs by writing and implementing LoopFinder, a customizable program that can identify loop-mediated PPIs within all protein-protein complexes in the Protein Data Bank. Comprehensive analysis of the entire set of 25,005 interface loops revealed common structural motifs and unique features that distinguish loop-mediated PPIs from other PPIs. “Hot loops,” named in analogy to protein hot spots, were identified as loops with favorable properties for mimicry using synthetic molecules. The hot loops and their binding partners represent new and promising PPIs for the development of macrocycle and constrained peptide inhibitors.
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Cites
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
Unraveling hot spots in binding interfaces: progress and challenges
DeLano, W. L. (2002) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(02)00283-x · Cited by 767
Hot spots—A review of the protein–protein interface determinant amino‐acid residues
Moreira, I. S., Fernandes, P. A., & Ramos, M. J. (2007) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.21396 · Cited by 760 · cited 1×
“41 Using this approach, computational alanine scans of protein-protein complexes have yielded a wide range of information about the different roles specific residues play at PPI interfaces.”
Structure of the Keap1:Nrf2 interface provides mechanistic insight into Nrf2 signaling
Lo, S., Li, X., Henzl, M. T., Beamer, L. J., & Hannink, M. (2006) · The EMBO Journal · doi:10.1038/sj.emboj.7601243 · Cited by 604
Hong, D. S., Kurzrock, R., Supko, J. G., He, X., Naing, A., Wheler, J., Lawrence, D., Eder, J. P., Meyer, C. J., Ferguson, D. A., et al. (2012) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-11-2703 · Cited by 236
Systematic Analysis of Helical Protein Interfaces Reveals Targets for Synthetic Inhibitors
Jochim, A. L., & Arora, P. S. (2010) · ACS Chemical Biology · doi:10.1021/cb1001747 · Cited by 191
Hancock, R., Schaap, M., Pfister, H., & Wells, G. (2013) · Organic & Biomolecular Chemistry · doi:10.1039/c3ob40249e · Cited by 91
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Small-Molecule Inhibitors of Protein-Protein Interactions: Progressing toward the Reality
Arkin, M. R., Tang, Y., & Wells, J. A. (2014) · Chemistry & Biology · doi:10.1016/j.chembiol.2014.09.001 · Cited by 1,065
Macromolecular modeling and design in Rosetta: recent methods and frameworks
Leman, J. K., Weitzner, B. D., Lewis, S. M., Adolf-Bryfogle, J., Alam, N., Alford, R. F., Aprahamian, M., Baker, D., Barlow, K. A., Barth, P., et al. (2020) · Nature Methods · doi:10.1038/s41592-020-0848-2 · Cited by 888
Pelay‐Gimeno, M., Glas, A., Koch, O., & Grossmann, T. N. (2015) · Angewandte Chemie International Edition · doi:10.1002/anie.201412070 · Cited by 717
New Modalities for Challenging Targets in Drug Discovery
Valeur, E., Guéret, S. M., Adihou, H., Gopalakrishnan, R., Lemurell, M., Waldmann, H., Grossmann, T. N., & Plowright, A. T. (2017) · Angewandte Chemie International Edition · doi:10.1002/anie.201611914 · Cited by 382
Modulating protein–protein interactions: the potential of peptides
Nevola, L., & Giralt, E. (2015) · Chemical Communications · doi:10.1039/c4cc08565e · Cited by 289
Metadata
- Authors
- Gavenonis, J., Sheneman, B. A., Siegert, T. R., Eshelman, M. R., & Kritzer, J. A.
- Venue
- Nature Chemical Biology
- Published
- 2014-07-20
- Volume
- 10
- Issue
- 9
- Pages
- 716-722
- ISSN
- 1552-4450 (ISSN-L)
- 1552-4469
- OpenAlex
- W2041026060
- Cited by
- 198
- References
- 7
- FWCI
- 8.03
- Type
- journal article
- Language
- en
- Open access
- green
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