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The Usage of ACCLUSTER for Peptide Binding Site Prediction

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Modeling Peptide-Protein Interactions

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

Abstract

Peptides mediate up to 40 % of protein–protein interactions in a variety of cellular processes and are also attractive drug candidates. Thus, predicting peptide binding sites on the given protein structure is of great importance for mechanistic investigation of protein–peptide interactions and peptide therapeutics development. In this chapter, we describe the usage of our web server, referred to as ACCLUSTER, for peptide binding site prediction for a given protein structure. ACCLUSTER is freely available for users without registration at http://zougrouptoolkit.missouri.edu/accluster.

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References

  1. Petsalaki E, Russell RB (2008) Peptide-mediated interactions in biological systems: new discoveries and applications. Curr Opin Biotechnol 19:344–350

    Article  CAS  PubMed  Google Scholar 

  2. Wells JA, McClendon CL (2007) Reaching for high-hanging fruit in drug discovery at protein-protein interfaces. Nature 450:1001–1009

    Article  CAS  PubMed  Google Scholar 

  3. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat T, Weissig H, Shindyalov IN, Bourne PE (2000) The Protein Data Bank. Nucleic Acids Res 28:235–242

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Yan C, Zou X (2015) Predicting peptide binding sites on protein surfaces by clustering chemical interactions. J Comput Chem 36:49–61

    Article  CAS  PubMed  Google Scholar 

  5. Chen R, Li L, Weng, Z (2003) ZDOCK: an initial-stage protein-docking algorithm. Proteins 52:80–87

    Article  CAS  PubMed  Google Scholar 

  6. Pierce BG, Hourai Y, Weng, Z (2011) Accelerating protein docking in ZDOCK using an advanced 3D convolution library. PLoS One 6:e24657

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Huang S-Y, Zou X (2008) An iterative knowledge-based scoring function for protein-protein recognition. Proteins 72:557–579

    Article  CAS  PubMed  Google Scholar 

  8. Ester M, Kriegel HP, Sander J, Xu, X (1996) A density-based algorithm for discovering clusters in large spatial databases with noise. In: Proceedings of KDD, vol 96, pp 226–231

    Google Scholar 

  9. Rego N, Koes, D (2014) 3Dmol.js: molecular visualization with WebGL. Bioinformatics 31:1322–1324. doi:10.1093/bioinformatics/btu829

    Article  PubMed  PubMed Central  Google Scholar 

  10. Sheng Y, Saridakis V, Sarkari F, Duan S, Wu T, Arrowsmith CH, Frappier, L (2006) Molecular recognition of p53 and MDM2 by USP7/HAUSP. Nat Struct Mol Biol 13:285–291

    Article  CAS  PubMed  Google Scholar 

  11. Hu M, Gu L, Li M, Jeffrey PD, Gu W, Shi, Y (2006) Structural basis of competitive recognition of p53 and MDM2 by HAUSP/USP7: implications for the regulation of the p53–MDM2 pathway. PLoS Biol 4:e27

    Article  PubMed  PubMed Central  Google Scholar 

  12. Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, Ferrin TE (2004) UCSF chimera–a visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work is supported by NSF CAREER Award DBI-0953839 and the NIH R01GM109980 (Xiaoqin Zou). The computations were performed on the high performance computing infrastructure supported by NSF CNS-1429294 (PI: Chi-Ren Shyu) and the HPC resources supported by the University of Missouri Bioinformatics Consortium (UMBC).

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Correspondence to Xiaoqin Zou .

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Yan, C., Xu, X., Zou, X. (2017). The Usage of ACCLUSTER for Peptide Binding Site Prediction. 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_1

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  • DOI: https://doi.org/10.1007/978-1-4939-6798-8_1

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6796-4

  • Online ISBN: 978-1-4939-6798-8

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