Skip to main content
SpringerLink
Log in
Book cover

Modeling Peptide-Protein Interactions pp 37–47Cite as

Template-Based Prediction of Protein-Peptide Interactions by Using GalaxyPepDock

  • Protocol
  • First Online:

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1561))

Abstract

We introduce a web server called GalaxyPepDock that predicts protein-peptide interactions based on templates. With the continuously increasing size of the protein structure database, the probability of finding related proteins for templates is increasing. GalaxyPepDock takes a protein structure and a peptide sequence as input and returns protein-peptide complex structures as output. Templates for protein-peptide complex structures are selected from the structure database considering similarity to the target protein structure and to putative protein-peptide interactions as estimated by protein structure alignment and peptide sequence alignment. Complex structures are then built from the template structures by template-based modeling. By further structure refinement that performs energy-based optimization, structural aspects that are missing in the template structures or that are not compatible with the given protein and peptide are refined. During the refinement, flexibilities of both protein and peptide induced by binding are considered. The atomistic protein-peptide interactions predicted by GalaxyPepDock can offer important clues for designing new peptides with desired binding properties.

This is a preview of subscription content, log in via an institution.

Protocol
USD   49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Springer Nature is developing a new tool to find and evaluate Protocols. Learn more

References

  1. London N, Raveh B, Schueler-Furman O (2013) Peptide docking and structure-based characterization of peptide binding: from knowledge to know-how. Current opinion in structural biology 23(6):894–902. doi:10.1016/j.sbi.2013.07.006

    Article  CAS  PubMed  Google Scholar 

  2. Petsalaki E, Russell RB (2008) Peptide-mediated interactions in biological systems: new discoveries and applications. Current opinion in biotechnology 19(4):344–350. doi:10.1016/j.copbio.2008.06.004

    Article  CAS  PubMed  Google Scholar 

  3. Yan C, Zou X (2015) Predicting peptide binding sites on protein surfaces by clustering chemical interactions. Journal of computational chemistry 36(1):49–61. doi:10.1002/jcc.23771

    Article  CAS  PubMed  Google Scholar 

  4. Yang Y, Ludwig RL, Jensen JP, Pierre SA, Medaglia MV, Davydov IV, Safiran YJ, Oberoi P, Kenten JH, Phillips AC, Weissman AM, Vousden KH (2005) Small molecule inhibitors of HDM2 ubiquitin ligase activity stabilize and activate p53 in cells. Cancer cell 7(6):547–559. doi:10.1016/j.ccr.2005.04.029

    Article  CAS  PubMed  Google Scholar 

  5. Soni V, Cahir-McFarland E, Kieff E (2007) LMP1 TRAFficking activates growth and survival pathways. Advances in experimental medicine and biology 597:173–187. doi:10.1007/978-0-387-70630-6_14

    Article  PubMed  Google Scholar 

  6. Raveh B, London N, Zimmerman L, Schueler-Furman O (2011) Rosetta FlexPepDock ab-initio: simultaneous folding, docking and refinement of peptides onto their receptors. PloS one 6(4), e18934. doi:10.1371/journal.pone.0018934

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. London N, Raveh B, Cohen E, Fathi G, Schueler-Furman O (2011) Rosetta FlexPepDock web server—high resolution modeling of peptide-protein interactions. Nucleic acids research 39(Web Server issue):W249–W253. doi:10.1093/nar/gkr431

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Donsky E, Wolfson HJ (2011) PepCrawler: a fast RRT-based algorithm for high-resolution refinement and binding affinity estimation of peptide inhibitors. Bioinformatics 27(20):2836–2842. doi:10.1093/bioinformatics/btr498

    Article  CAS  PubMed  Google Scholar 

  9. Saladin A, Rey J, Thevenet P, Zacharias M, Moroy G, Tuffery P (2014) PEP-SiteFinder: a tool for the blind identification of peptide binding sites on protein surfaces. Nucleic acids research 42(Web Server issue):W221–W226. doi:10.1093/nar/gku404

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Kurcinski M, Jamroz M, Blaszczyk M, Kolinski A, Kmiecik S (2015) CABS-dock web server for the flexible docking of peptides to proteins without prior knowledge of the binding site. Nucleic acids research 43(Web Server issue):W419–W424. doi:10.1093/nar/gkv456

    Article  PubMed  PubMed Central  Google Scholar 

  11. Thevenet P, Shen Y, Maupetit J, Guyon F, Derreumaux P, Tuffery P (2012) PEP-FOLD: an updated de novo structure prediction server for both linear and disulfide bonded cyclic peptides. Nucleic acids research 40(Web Server issue):W288–W293. doi:10.1093/nar/gks419

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Zacharias M (2005) ATTRACT: protein-protein docking in CAPRI using a reduced protein model. Proteins 60(2):252–256. doi:10.1002/prot.20566

    Article  CAS  PubMed  Google Scholar 

  13. Trabuco LG, Lise S, Petsalaki E, Russell RB (2012) PepSite: prediction of peptide-binding sites from protein surfaces. Nucleic acids research 40(Web Server issue):W423–W427. doi:10.1093/nar/gks398

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. London N, Movshovitz-Attias D, Schueler-Furman O (2010) The structural basis of peptide-protein binding strategies. Structure 18(2):188–199. doi:10.1016/j.str.2009.11.012

    Article  CAS  PubMed  Google Scholar 

  15. Lee H, Heo L, Lee MS, Seok C (2015) GalaxyPepDock: a protein-peptide docking tool based on interaction similarity and energy optimization. Nucleic acids research 43(W1):W431–W435. doi:10.1093/nar/gkv495

    Article  PubMed  PubMed Central  Google Scholar 

  16. Ko J, Park H, Heo L, Seok C (2012) GalaxyWEB server for protein structure prediction and refinement. Nucleic acids research 40(Web Server issue):W294–W297. doi:10.1093/nar/gks493

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Lensink MF, Wodak SJ (2013) Docking, scoring, and affinity prediction in CAPRI. Proteins 81(12):2082–2095. doi:10.1002/prot.24428

    Article  CAS  PubMed  Google Scholar 

  18. Das AA, Sharma OP, Kumar MS, Krishna R, Mathur PP (2013) PepBind: a comprehensive database and computational tool for analysis of protein-peptide interactions. Genomics, proteomics & bioinformatics 11(4):241–246. doi:10.1016/j.gpb.2013.03.002

    Article  Google Scholar 

  19. Zhang Y, Skolnick J (2004) Scoring function for automated assessment of protein structure template quality. Proteins 57(4):702–710. doi:10.1002/prot.20264

    Article  CAS  PubMed  Google Scholar 

  20. Ko J, Park H, Seok C (2012) GalaxyTBM: template-based modeling by building a reliable core and refining unreliable local regions. BMC bioinformatics 13:198. doi:10.1186/1471-2105-13-198

    Article  PubMed  PubMed Central  Google Scholar 

  21. Heo L, Park H, Seok C (2013) GalaxyRefine: protein structure refinement driven by side-chain repacking. Nucleic acids research 41(Web Server issue):W384–W388. doi:10.1093/nar/gkt458

    Article  PubMed  PubMed Central  Google Scholar 

  22. Qi S, O'Hayre M, Gutkind JS, Hurley JH (2014) Structural and biochemical basis for ubiquitin ligase recruitment by arrestin-related domain-containing protein-3 (ARRDC3). The Journal of biological chemistry 289(8):4743–4752. doi:10.1074/jbc.M113.527473

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgment

This work was supported by National Research Foundation of Korea grants funded by the Ministry of Science, ICT & Future Planning (No. 2013R1A2A1A09012229).

Author information

Authors and Affiliations

  1. Department of Chemistry, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 151-747, Republic of Korea

    Hasup Lee & Chaok Seok

Authors
  1. Hasup Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chaok Seok
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chaok Seok .

Editor information

Editors and Affiliations

  1. Microbiology and Molecular Genetics, Hebrew University Hadassah Medical School, Jerusalem, Israel

    Ora Schueler-Furman

  2. Organic Chemistry, The Weizmann Institute of Science, Rehovot, Israel

    Nir London

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media LLC

About this protocol

Cite this protocol

Lee, H., Seok, C. (2017). Template-Based Prediction of Protein-Peptide Interactions by Using GalaxyPepDock. In: Schueler-Furman, O., London, N. (eds) Modeling Peptide-Protein Interactions. Methods in Molecular Biology, vol 1561. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6798-8_4

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-6798-8_4

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6796-4

  • Online ISBN: 978-1-4939-6798-8

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation