title: Protein-protein docking with F(2)Dock 2.0 and GB-rerank.
abstract: BACKGROUND
  Computational simulation of protein-protein docking can expedite the process of molecular modeling and drug discovery. This paper reports on our new F(2) Dock protocol which improves the state of the art in initial stage rigid body exhaustive docking search, scoring and ranking by introducing improvements in the shape-complementarity and electrostatics affinity functions, a new knowledge-based interface propensity term with FFT formulation, a set of novel knowledge-based filters and finally a solvation energy (GBSA) based reranking technique. Our algorithms are based on highly efficient data structures including the dynamic packing grids and octrees which significantly speed up the computations and also provide guaranteed bounds on approximation error.
  
  
  RESULTS
  The improved affinity functions show superior performance compared to their traditional counterparts in finding correct docking poses at higher ranks. We found that the new filters and the GBSA based reranking individually and in combination significantly improve the accuracy of docking predictions with only minor increase in computation time. We compared F(2) Dock 2.0 with ZDock 3.0.2 and found improvements over it, specifically among 176 complexes in ZLab Benchmark 4.0, F(2) Dock 2.0 finds a near-native solution as the top prediction for 22 complexes; where ZDock 3.0.2 does so for 13 complexes. F(2) Dock 2.0 finds a near-native solution within the top 1000 predictions for 106 complexes as opposed to 104 complexes for ZDock 3.0.2. However, there are 17 and 15 complexes where F(2) Dock 2.0 finds a solution but ZDock 3.0.2 does not and vice versa; which indicates that the two docking protocols can also complement each other.
  
  
  BACKGROUND
  The docking protocol has been implemented as a server with a graphical client (TexMol) which allows the user to manage multiple docking jobs, and visualize the docked poses and interfaces. Both the server and client are available for download. Server: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dock.shtml. Client: http://www.cs.utexas.edu/~bajaj/cvc/software/f2dockclient.shtml.
authors.affiliation: Department of Computer Science, Institute of Computational Engineering and Sciences, University of Texas at Austin, Austin, TX, USA.
authors.forename: Rezaul
authors.initials: R
authors.lastname: Chowdhury
authors.forename: Muhibur
authors.initials: M
authors.lastname: Rasheed
authors.forename: Donald
authors.initials: D
authors.lastname: Keidel
authors.forename: Maysam
authors.initials: M
authors.lastname: Moussalem
authors.forename: Arthur
authors.initials: A
authors.lastname: Olson
authors.forename: Michel
authors.initials: M
authors.lastname: Sanner
authors.forename: Chandrajit
authors.initials: C
authors.lastname: Bajaj
mesh_terms: D000465:Algorithms; D000936:Antigen-Antibody Complex / Q000276:immunology; D019295:Computational Biology / Q000379:methods*; D004791:Enzyme Inhibitors / Q000378:metabolism; D005583:Fourier Analysis; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods*; D013379:Substrate Specificity; D013997:Time Factors
chemical_list: D000936:Antigen-Antibody Complex; D004791:Enzyme Inhibitors