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Integrating statistical pair potentials into protein complex prediction.

Publication ,  Journal Article
Mintseris, J; Pierce, B; Wiehe, K; Anderson, R; Chen, R; Weng, Z
Published in: Proteins
November 15, 2007

The biophysical study of protein-protein interactions and docking has important implications in our understanding of most complex cellular signaling processes. Most computational approaches to protein docking involve a tradeoff between the level of detail incorporated into the model and computational power required to properly handle that level of detail. In this work, we seek to optimize that balance by showing that we can reduce the complexity of model representation and thus make the computation tractable with minimal loss of predictive performance. We also introduce a pair-wise statistical potential suitable for docking that builds on previous work and show that this potential can be incorporated into our fast fourier transform-based docking algorithm ZDOCK. We use the Protein Docking Benchmark to illustrate the improved performance of this potential compared with less detailed other scoring functions. Furthermore, we show that the new potential performs well on antibody-antigen complexes, with most predictions clustering around the Complementarity Determining Regions of antibodies without any manual intervention.

Duke Scholars

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Published In

Proteins

DOI

EISSN

1097-0134

Publication Date

November 15, 2007

Volume

69

Issue

3

Start / End Page

511 / 520

Location

United States

Related Subject Headings

  • Proteins
  • Protein Conformation
  • Protein Binding
  • Muramidase
  • Models, Statistical
  • Models, Molecular
  • Models, Chemical
  • Immunoglobulin Fab Fragments
  • Bioinformatics
  • Antigen-Antibody Complex
 

Citation

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Mintseris, J., Pierce, B., Wiehe, K., Anderson, R., Chen, R., & Weng, Z. (2007). Integrating statistical pair potentials into protein complex prediction. Proteins, 69(3), 511–520. https://doi.org/10.1002/prot.21502
Mintseris, Julian, Brian Pierce, Kevin Wiehe, Robert Anderson, Rong Chen, and Zhiping Weng. “Integrating statistical pair potentials into protein complex prediction.Proteins 69, no. 3 (November 15, 2007): 511–20. https://doi.org/10.1002/prot.21502.
Mintseris J, Pierce B, Wiehe K, Anderson R, Chen R, Weng Z. Integrating statistical pair potentials into protein complex prediction. Proteins. 2007 Nov 15;69(3):511–20.
Mintseris, Julian, et al. “Integrating statistical pair potentials into protein complex prediction.Proteins, vol. 69, no. 3, Nov. 2007, pp. 511–20. Pubmed, doi:10.1002/prot.21502.
Mintseris J, Pierce B, Wiehe K, Anderson R, Chen R, Weng Z. Integrating statistical pair potentials into protein complex prediction. Proteins. 2007 Nov 15;69(3):511–520.
Journal cover image

Published In

Proteins

DOI

EISSN

1097-0134

Publication Date

November 15, 2007

Volume

69

Issue

3

Start / End Page

511 / 520

Location

United States

Related Subject Headings

  • Proteins
  • Protein Conformation
  • Protein Binding
  • Muramidase
  • Models, Statistical
  • Models, Molecular
  • Models, Chemical
  • Immunoglobulin Fab Fragments
  • Bioinformatics
  • Antigen-Antibody Complex