Can self‐inhibitory peptides be derived from the interfaces of globular protein–protein interactions?
Open accessAbstract
In this study, we assess on a large scale the possibility of deriving self‐inhibitory peptides from protein domains with globular architectures. Such inhibitory peptides would inhibit interactions of their origin domain by mimicking its mode of binding to cognate partners, and could serve as promising leads for rational design of inhibitory drugs. For our large‐scale analysis, we analyzed short linear segments that were cut out of protein interfaces in silico in complex structures of protein–protein docking Benchmark 3.0 and CAPRI targets from rounds 1–19. Our results suggest that more than 50% of these globular interactions are dominated by one short linear segment at the domain interface, which provides more than half of the original interaction energy. Importantly, in many cases the derived peptides show strong energetic preference for their original binding mode independently of the context of their original domain, as we demonstrate by extensive computational peptide docking experiments. As an in depth case study, we computationally design a candidate peptide to inhibit the EphB4–EphrinB2 interaction based on a short peptide derived from the G‐H loop in EphrinB2. Altogether, we provide an elaborate framework for the in silico selection of candidate inhibitory molecules for protein–protein interactions. Such candidate molecules can be readily subjected to wet‐laboratory experiments and provide highly promising starting points for subsequent drug design. Proteins 2010. © 2010 Wiley‐Liss, Inc.
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
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
There are three different classes of PPI: short continuous peptide epitopes, secondary structural epitopes, and tertiary structural epitopes.
“Generally, there are three different classes of PPI: short continuous peptide epitopes, secondary structural epitopes, and tertiary structural epitopes.”
From The design and development of covalent protein-protein interaction inhibitors for cancer treatment (2020) · cites this paper as [28]
Secondary structural epitopes can bind as single unit, for example, a single face of an α-helix binding to a hydrophobic groove of complementary residues.
“Secondary structural epitopes can bind as single unit, for example, a single face of an α-helix binding to a hydrophobic groove of complementary residues (Fig. 2b) [27, 28].”
From The design and development of covalent protein-protein interaction inhibitors for cancer treatment (2020) · cites this paper as [28]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Intrinsically unstructured proteins and their functions
Dyson, H. J., & Wright, P. E. (2005) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1589 · Cited by 3,871 · see citing works
Principles of protein-protein interactions
Jones, S., & Thornton, J. M. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.1.13 · Cited by 2,684 · see citing works
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 1,987 · see citing works
The atomic structure of protein-protein recognition sites 1 1Edited by A. R. Fersht
Conte, L. L., Chothia, C., & Janin, J. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.2439 · Cited by 1,967 · see citing works
Reaching for high-hanging fruit in drug discovery at protein–protein interfaces
Wells, J. A., & McClendon, C. L. (2007) · Nature · doi:10.1038/nature06526 · Cited by 1,963 · see citing works
Protein Structure Prediction Using Rosetta
Rohl, C. A., Strauss, C. E. M., Misura, K. M. S., & Baker, D. A. (2004) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/s0076-6879(04)83004-0 · Cited by 1,711 · see citing works
Synthetic therapeutic peptides: science and market
Vlieghe, P., Lisowski, V., Martínez, J., & Khrestchatisky, M. (2009) · Drug Discovery Today · doi:10.1016/j.drudis.2009.10.009 · Cited by 1,487 · see citing works
Structure of Bcl-x <sub>L</sub> -Bak Peptide Complex: Recognition Between Regulators of Apoptosis
Sattler, M., Liang, H., Nettesheim, D., Meadows, R. P., Harlan, J. E., Eberstadt, M., Yoon, H. S., Shuker, S. B., Chang, B. S., Minn, A. J., et al. (1997) · Science · doi:10.1126/science.275.5302.983 · Cited by 1,476 · see citing works
Assembly of Cell Regulatory Systems Through Protein Interaction Domains
Pawson, T. J., & Nash, P. (2003) · Science · doi:10.1126/science.1083653 · Cited by 1,403 · see citing works
Coupling of folding and binding for unstructured proteins
Dyson, H. J., & Wright, P. E. (2002) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(02)00289-0 · Cited by 1,327 · see citing works
Macromolecular Modeling with Rosetta
Das, R., & Baker, D. A. (2008) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.77.062906.171838 · Cited by 995 · see citing works
Peptoids: a modular approach to drug discovery.
Simon, R. J., Kania, R. S., Zuckermann, R. N., Huebner, V. D., Jewell, D. A., Banville, S. C., Ng, S., Wang, L., Rosenberg, S., & Marlowe, C. K. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.20.9367 · Cited by 956 · see citing works
Characterization of Molecular Recognition Features, MoRFs, and Their Binding Partners
Vacic, V., Oldfield, C. J., Mohan, A., Predrag Radivojac, A., Cortese, M. S., Uversky, V. N., & Dunker, A. K. (2007) · Journal of Proteome Research · doi:10.1021/pr0701411 · Cited by 483 · see citing works
Sub-angstrom modeling of complexes between flexible peptides and globular proteins
Raveh, B., London, N., & Schueler‐Furman, O. (2010) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22716 · Cited by 423 · see citing works
Self-citationThe Structural Basis of Peptide-Protein Binding Strategies
London, N., Movshovitz‐Attias, D., & Schueler‐Furman, O. (2010) · Structure · doi:10.1016/j.str.2009.11.012 · Cited by 417 · see citing works
Self-citationMolecular Mechanism of the Interaction between MDM2 and p53
Schön, O., Friedler, A., Bycroft, M., Freund, S. M. V., & Fersht, A. R. (2002) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)00852-5 · Cited by 349 · see citing works
Peptide-mediated interactions in biological systems: new discoveries and applications
Petsalaki, E., & Russell, R. B. (2008) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2008.06.004 · Cited by 287 · see citing works
Protein–protein docking benchmark version 3.0
Hwang, H., Pierce, B. G., Mintseris, J., Janin, J., & Weng, Z. (2008) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22106 · Cited by 256 · see citing works
Crystal structure of a complex between anthrax toxin and its host cell receptor
Santelli, E., Bankston, L. A., Leppla, S. H., & Liddington, R. (2004) · Nature · doi:10.1038/nature02763 · Cited by 248 · see citing works
Interplay between EphB4 on tumor cells and vascular ephrin-B2 regulates tumor growth
Hooten, N. N., Lu, M., Freeman, A. L., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0401381101 · Cited by 246 · see citing works
Brunner, H. R., Gavras, H. P., Laragh, J. H., et al. (1973) · The Lancet · doi:10.1016/s0140-6736(73)92657-3 · Cited by 242 · see citing works
The modular architecture of protein–protein binding interfaces
Reichmann, D., Rahat, O., Albeck, S., Meged, R., Dym, O., & Schreiber, G. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407280102 · Cited by 239 · see citing works
Peptide drug modifications to enhance bioavailability and blood-brain barrier permeability
WITT, K. A., Gillespie, T. J., Huber, J. D., Egleton, R. D., & Davis, T. P. (2001) · Peptides · doi:10.1016/s0196-9781(01)00537-x · Cited by 229 · see citing works
Structure of the Ubiquitin Hydrolase UCH-L3 Complexed with a Suicide Substrate
Misaghi, S., Galardy, P. J., Meester, W. J. N., Ovaa, H., Ploegh, H. L., & Gaudet, R. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m410770200 · Cited by 193 · see citing works
Arkin, M. R., & Whitty, A. (2009) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2009.05.125 · Cited by 190 · see citing works
Targeting protein–protein interactions: Lessons from p53/MDM2
Murray, J. K., & Gellman, S. H. (2007) · Biopolymers · doi:10.1002/bip.20741 · Cited by 186 · see citing works
Assessing predictions of protein–protein interaction: The CAPRI experiment
Janin, J. (2005) · Protein Science · doi:10.1110/ps.041081905 · Cited by 179 · see citing works
Antes, I. (2009) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.22629 · Cited by 166 · see citing works
Kertesz, N. L., Krasnoperov, V. G., Reddy, R. K., et al. (2005) · Blood · doi:10.1182/blood-2005-04-1655 · Cited by 164 · see citing works
Targeting protein–protein interactions by rational design: mimicry of protein surfaces
Fletcher, S., & Hamilton, A. D. (2006) · Journal of The Royal Society Interface · doi:10.1098/rsif.2006.0115 · Cited by 164 · see citing works
Zhou, H. (2004) · Accounts of Chemical Research · doi:10.1021/ar0302282 · Cited by 159 · see citing works
Design and Structure of Peptide and Peptidomimetic Antagonists of Protein- Protein Interaction
Sillerud, L. O., & Larson, R. A. (2005) · Current Protein and Peptide Science · doi:10.2174/1389203053545462 · Cited by 129 · see citing works
Coexpression of ephrin‐Bs and their receptors in colon carcinoma
Liu, W., Ahmad, S. A., Jung, Y. D., et al. (2002) · Cancer · doi:10.1002/cncr.10122 · Cited by 125 · see citing works
PepX: a structural database of non-redundant protein–peptide complexes
Vanhee, P., Reumers, J., Stricher, F., et al. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp893 · Cited by 112 · see citing works
Backbone flexibility in computational protein design
Mandell, D. J., & Kortemme, T. (2009) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2009.07.006 · Cited by 106 · see citing works
Peptidic modulators of protein‐protein interactions: Progress and challenges in computational design
Rubinstein, M., & Niv, M. Y. (2009) · Biopolymers · doi:10.1002/bip.21164 · Cited by 101 · see citing works
Chrencik, J., Brooun, A., Kraus, M. L., Recht, M. I., Kolatkar, A. R., Han, G. W., Seifert, J. M., Widmer, H., Auer, M., & Kühn, P. (2006) · Journal of Biological Chemistry · doi:10.1074/jbc.m605766200 · Cited by 97 · see citing works
Molecular Basis for Bacterial Class I Release Factor Methylation by PrmC
Graille, M., Heurgué‐Hamard, V., Champ, S., et al. (2005) · Molecular Cell · doi:10.1016/j.molcel.2005.10.025 · Cited by 92 · see citing works
Binding Hot Spots in the TEM1–BLIP Interface in Light of its Modular Architecture
Reichmann, D., Cohen, M., Abramovich, R., Dym, O., Lim, D., Strynadka, N. C. J., & Schreiber, G. (2006) · Journal of Molecular Biology · doi:10.1016/j.jmb.2006.09.076 · Cited by 92 · see citing works
Ab initio prediction of peptide‐MHC binding geometry for diverse class I MHC allotypes
Bordner, A. J., & Abagyan, R. A. (2006) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20831 · Cited by 76 · see citing works
Niv, M. Y., & Weinstein, H. (2005) · Journal of the American Chemical Society · doi:10.1021/ja054195s · Cited by 70 · see citing works
Chen, S. W., Regenmortel, M. H. V. V., & Pellequer, J. (2009) · Current Medicinal Chemistry · doi:10.2174/092986709787581914 · Cited by 68 · see citing works
Hashemzadeh, M., Furukawa, M., Goldsberry, S., et al. (2008) · PubMed · Cited by 64 · see citing works
Berclaz, G., Karamitopoulou, E., Mazzucchelli, L., et al. (2003) · Annals of Oncology · doi:10.1093/annonc/mdg072 · Cited by 56 · see citing works
Peptide binding to MHC class I and II proteins: New avenues from new methods
Yaneva, R., Schneeweiß, C., Zacharias, M., et al. (2009) · Molecular Immunology · doi:10.1016/j.molimm.2009.10.008 · Cited by 50 · see citing works
A Peptide Antagonist of the TLR4–MD2 Interaction
Slivka, P. F., Shridhar, M., Lee, G., Sammond, D. W., Hutchinson, M. R., Martinko, A. J., Buchanan, M. M., Sholar, P. W., Kearney, J. J., Harrison, J. A., et al. (2009) · ChemBioChem · doi:10.1002/cbic.200800769 · Cited by 50 · see citing works
Computational protein design: structure, function and combinatorial diversity
Kang, S.-G., & Saven, J. G. (2007) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2007.05.006 · Cited by 44 · see citing works
Peptide segments in protein-protein interfaces
Pal, A., Chakrabarti, P., Bahadur, R. P., Rodier, F., & Janin, J. (2007) · Journal of Biosciences · doi:10.1007/s12038-007-0010-7 · Cited by 40 · see citing works
Peptides as Signaling Inhibitors for Mammalian MAP Kinase Cascades
Gaestel, M., & Kracht, M. (2009) · Current Pharmaceutical Design · doi:10.2174/138161209788682299 · Cited by 25 · see citing works
Targeting Rho GTPases by Peptidic Structures
Marchioni, F., & Zheng, Y. (2009) · Current Pharmaceutical Design · doi:10.2174/138161209788682334 · Cited by 22 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
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 · see citing works
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 · see citing works
Self-citationModulators of Protein–Protein Interactions
Milroy, L.-G., Grossmann, T. N., Hennig, S., Brunsveld, L., & Ottmann, C. (2014) · Chemical Reviews · doi:10.1021/cr400698c · Cited by 497 · see citing works
Glas, A., Bier, D., Hahne, G., Rademacher, C., Ottmann, C., & Grossmann, T. N. (2014) · Angewandte Chemie International Edition · doi:10.1002/anie.201310082 · Cited by 145 · see citing works
The design and development of covalent protein-protein interaction inhibitors for cancer treatment
Cheng, S.-S., Yang, G.-J., Wang, W., Leung, C.-H., & Ma, D.-L. (2020) · Journal of Hematology & Oncology · doi:10.1186/s13045-020-00850-0 · Cited by 98 · see citing works
- Authors
- London, N., Raveh, B., Movshovitz‐Attias, D., & Schueler‐Furman, O.
- Affiliations
- Hebrew University of Jerusalem (IL)
- Tel Aviv University (IL)
- Corresponding author
- Schueler‐Furman, Ora
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2010-06
- Volume
- 78
- Issue
- 15
- Pages
- 3140-3149
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- PMC
- PMC2952690
- OpenAlex
- W2109604654
- Cited by
- 164
- References
- 50
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 6 · 2023: 10 · 2022: 12 · 2021: 10 · 2020: 19 · 2019: 10 · 2018: 11 · 2017: 14 · 2016: 8 · 2015: 10 · 2014: 15 · 2013: 10 · 2012: 7
- FWCI
- 3.52
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proteins Structure Function and Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (R21DA026950)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chemical Synthesis and Analysis
- Keywords
- protein-protein interaction, protein interfaces, peptidomimetics, protein-peptide docking, interaction energy
- MeSH terms
- Animals, Binding Sites, Computer Simulation, Humans, Models, Chemical, Models, Molecular, Peptides, Protein Binding, Protein Conformation, Proteins, Software, Thermodynamics, Protein Interaction Mapping, Mice, Protein Interaction Domains and Motifs, Protein Stability
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