Scoring optimisation of unbound protein–protein docking including protein binding site predictions

The prediction of the structure of the protein–protein complex is of great importance to better understand molecular recognition processes. During systematic protein–protein docking, the surface of a protein molecule is scanned for putative binding sites of a partner protein. The possibility to include external data based on either experiments or bioinformatic predictions on putative binding sites during docking has been systematically explored. The external data were included during docking with a coarse‐grained protein model and on the basis of force field weights to bias the docking search towards a predicted or known binding region. The approach was tested on a large set of protein partners in unbound conformations. The significant improvement of the docking performance was found if reliable data on the native binding sites were available. This was possible even if data for single key amino acids at a binding interface are included. In case of binding site predictions with limited accuracy, only modest improvement compared with unbiased docking was found. The optimisation of the protocol to bias the search towards predicted binding sites was found to further improve the docking performance resulting in approximately 40% acceptable solutions within the top 10 docking predictions compared with 22% in case of unbiased docking of unbound protein structures. Copyright © 2011 John Wiley & Sons, Ltd.

[1]  Zhiping Weng,et al.  ZRANK: Reranking protein docking predictions with an optimized energy function , 2007, Proteins.

[2]  M. Schroeder,et al.  Using protein binding site prediction to improve protein docking. , 2008, Gene.

[3]  Yaoqi Zhou,et al.  Consensus scoring for enriching near‐native structures from protein–protein docking decoys , 2009, Proteins.

[4]  Alexandre M J J Bonvin,et al.  Strengths and weaknesses of data‐driven docking in critical assessment of prediction of interactions , 2010, Proteins.

[5]  Alexandre M J J Bonvin,et al.  Flexible protein-protein docking. , 2006, Current opinion in structural biology.

[6]  Alexandre M J J Bonvin,et al.  How proteins get in touch: interface prediction in the study of biomolecular complexes. , 2008, Current protein & peptide science.

[7]  Alexandre M. J. J. Bonvin,et al.  CPORT: A Consensus Interface Predictor and Its Performance in Prediction-Driven Docking with HADDOCK , 2011, PloS one.

[8]  Martin Zacharias,et al.  Binding site prediction and improved scoring during flexible protein–protein docking with ATTRACT , 2010, Proteins.

[9]  R. Raz,et al.  ProMate: a structure based prediction program to identify the location of protein-protein binding sites. , 2004, Journal of molecular biology.

[10]  M. Zacharias,et al.  Accounting for global protein deformability during protein-protein and protein-ligand docking. , 2005, Biochimica et biophysica acta.

[11]  S. Wodak,et al.  Docking and scoring protein complexes: CAPRI 3rd Edition , 2007, Proteins.

[12]  Martin Zacharias,et al.  Energy minimization in low‐frequency normal modes to efficiently allow for global flexibility during systematic protein–protein docking , 2008, Proteins.

[13]  Carles Pons,et al.  Present and future challenges and limitations in protein–protein docking , 2010, Proteins.

[14]  Huan-Xiang Zhou,et al.  meta-PPISP: a meta web server for protein-protein interaction site prediction , 2007, Bioinform..

[15]  C. Dominguez,et al.  HADDOCK: a protein-protein docking approach based on biochemical or biophysical information. , 2003, Journal of the American Chemical Society.

[16]  Z. Weng,et al.  Protein–protein docking benchmark 2.0: An update , 2005, Proteins.

[17]  Alexandre M. J. J. Bonvin,et al.  Data-driven Docking: Using External Information to Spark the Biomolecular Rendez-vous , 2010 .

[18]  Gideon Schreiber,et al.  A novel method for scoring of docked protein complexes using predicted protein-protein binding sites. , 2004, Protein engineering, design & selection : PEDS.

[19]  Yaoqi Zhou,et al.  Docking prediction using biological information, ZDOCK sampling technique, and clustering guided by the DFIRE statistical energy function , 2005, Proteins.

[20]  Miriam Eisenstein,et al.  Combining interface core and whole interface descriptors in postscan processing of protein‐protein docking models , 2009, Proteins.

[21]  Miriam Eisenstein,et al.  Weighted geometric docking: Incorporating external information in the rotation‐translation scan , 2003, Proteins.

[22]  Zhiping Weng,et al.  A combination of rescoring and refinement significantly improves protein docking performance , 2008, Proteins.

[23]  Song Liu,et al.  Protein binding site prediction using an empirical scoring function , 2006, Nucleic acids research.

[24]  A. Bonvin,et al.  WHISCY: What information does surface conservation yield? Application to data‐driven docking , 2006, Proteins.

[25]  Martin Zacharias,et al.  Protein–protein docking with a reduced protein model accounting for side‐chain flexibility , 2003, Protein science : a publication of the Protein Society.

[26]  Martin Zacharias,et al.  Accounting for conformational changes during protein-protein docking. , 2010, Current opinion in structural biology.

[27]  Tammy M. K. Cheng,et al.  pyDock: Electrostatics and desolvation for effective scoring of rigid‐body protein–protein docking , 2007, Proteins.

[28]  Huan-Xiang Zhou,et al.  Prediction of interface residues in protein–protein complexes by a consensus neural network method: Test against NMR data , 2005, Proteins.

[29]  Pedro Alexandrino Fernandes,et al.  Protein–protein docking dealing with the unknown , 2009, J. Comput. Chem..