VORFFIP-driven dock: V-D2OCK, a fast and accurate protein docking strategy

PLoS One. 2015 Mar 12;10(3):e0118107. doi: 10.1371/journal.pone.0118107. eCollection 2015.


The experimental determination of the structure of protein complexes cannot keep pace with the generation of interactomic data, hence resulting in an ever-expanding gap. As the structural details of protein complexes are central to a full understanding of the function and dynamics of the cell machinery, alternative strategies are needed to circumvent the bottleneck in structure determination. Computational protein docking is a valid and valuable approach to model the structure of protein complexes. In this work, we describe a novel computational strategy to predict the structure of protein complexes based on data-driven docking: VORFFIP-driven dock (V-D2OCK). This new approach makes use of our newly described method to predict functional sites in protein structures, VORFFIP, to define the region to be sampled during docking and structural clustering to reduce the number of models to be examined by users. V-D2OCK has been benchmarked using a validated and diverse set of protein complexes and compared to a state-of-art docking method. The speed and accuracy compared to contemporary tools justifies the potential use of VD2OCK for high-throughput, genome-wide, protein docking. Finally, we have developed a web interface that allows users to browser and visualize V-D2OCK predictions from the convenience of their web-browsers.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Binding Sites
  • Humans
  • Models, Molecular
  • Molecular Docking Simulation / methods*
  • Protein Binding
  • Protein Conformation
  • Protein Multimerization
  • Proteins / chemistry*
  • Proteins / metabolism*
  • User-Computer Interface
  • Web Browser


  • Proteins

Grants and funding

This work was supported by Research Councils UK (RCUK) under the RCUK Academic Fellowship program (NFF) and a PhD scholarship awarded by the University of Leeds (JS). BO acknowledges support from the Spanish Ministry of Economy and Competitiveness; grant number BIO2011-22568 and MAML a PhD scholarship awarded by the Generalitat of Catalonia (FI-DGR2012). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.