FireDock: a web server for fast interaction refinement in molecular docking†

Structural details of protein–protein interactions are invaluable for understanding and deciphering biological mechanisms. Computational docking methods aim to predict the structure of a protein–protein complex given the structures of its single components. Protein flexibility and the absence of robust scoring functions pose a great challenge in the docking field. Due to these difficulties most of the docking methods involve a two-tier approach: coarse global search for feasible orientations that treats proteins as rigid bodies, followed by an accurate refinement stage that aims to introduce flexibility into the process. The FireDock web server, presented here, is the first web server for flexible refinement and scoring of protein–protein docking solutions. It includes optimization of side-chain conformations and rigid-body orientation and allows a high-throughput refinement. The server provides a user-friendly interface and a 3D visualization of the results. A docking protocol consisting of a global search by PatchDock and a refinement by FireDock was extensively tested. The protocol was successful in refining and scoring docking solution candidates for cases taken from docking benchmarks. We provide an option for using this protocol by automatic redirection of PatchDock candidate solutions to the FireDock web server for refinement. The FireDock web server is available at http://bioinfo3d.cs.tau.ac.il/FireDock/

A new protein-protein docking scoring function based on interface residue properties.

International audienceMOTIVATION: Protein-protein complexes are known to play key roles in many cellular processes. However, they are often not accessible to experimental study because of their low stability and difficulty to produce the proteins and assemble them in native conformation. Thus, docking algorithms have been developed to provide an in silico approach of the problem. A protein-protein docking procedure traditionally consists of two successive tasks: a search algorithm generates a large number of candidate solutions, and then a scoring function is used to rank them. RESULTS: To address the second step, we developed a scoring function based on a Voronoï tessellation of the protein three-dimensional structure. We showed that the Voronoï representation may be used to describe in a simplified but useful manner, the geometric and physico-chemical complementarities of two molecular surfaces. We measured a set of parameters on native protein-protein complexes and on decoys, and used them as attributes in several statistical learning procedures: a logistic function, Support Vector Machines (SVM), and a genetic algorithm. For the later, we used ROGER, a genetic algorithm designed to optimize the area under the receiver operating characteristics curve. To further test the scores derived with ROGER, we ranked models generated by two different docking algorithms on targets of a blind prediction experiment, improving in almost all cases the rank of native-like solutions. AVAILABILITY: http://genomics.eu.org/spip/-Bioinformatics-tools

Identification of the protein kinase A regulatory R(I)α-catalytic subunit interface by amide H/(2)H exchange and protein docking

An important goal after structural genomics is to build up the structures of higher-order protein–protein complexes from structures of the individual subunits. Often structures of higher order complexes are difficult to obtain by crystallography. We have used an alternative approach in which the structures of the individual catalytic (C) subunit and R(I)α regulatory (R) subunit of PKA were first subjected to computational docking, and the top 100,000 solutions were subsequently filtered based on amide hydrogen/deuterium (H/(2)H) exchange interface protection data. The resulting set of filtered solutions forms an ensemble of structures in which, besides the inhibitor peptide binding site, a flat interface between the C-terminal lobe of the C-subunit and the A- and B-helices of R(I)α is uniquely identified. This holoenzyme structure satisfies all previous experimental data on the complex and allows prediction of new contacts between the two subunits

Recent advances in computer-aided drug design

10.1093/bib/bbp023Briefings in Bioinformatics105579-59