EROS-DOCK: Protein-Protein Docking Using Exhaustive Branch-and-Bound Rotational Search

International audienceMotivation: Protein-protein docking algorithms aim to predict the 3D structure of a binary complex using the structures of the individual proteins. This typically involves searching and scoring in a six-dimensional space. Many docking algorithms use FFT techniques to exhaustively cover the search space and to accelerate the scoring calculation. However, FFT docking results often depend on the initial protein orientations with respect to the Fourier sampling grid. Furthermore, Fourier-transforming a physics-base force field can involve a serious loss of precision.Results: Here, we present EROS-DOCK, an algorithm to rigidly dock two proteins using a series of exhaustive 3D rotational searches in which non-clashing orientations are scored using the ATTRACT coarse-grained force field model. The rotational space is represented as a quaternion "π-ball", which is systematically subdivided in a "branch-and-bound" manner, allowing efficient pruning of rotations that will give steric clashes. The algorithm was tested on 173 Docking Benchmark complexes, and results were compared with those of ATTRACT and ZDOCK. According to the CAPRI quality criteria, EROS-DOCK typcially gives more acceptable or medium quality solutions than ATTRACT and ZDOCK.Availability: The EROS-DOCK program is available for download at http://erosdock.loria.fr

Accelerating Protein Docking Calculations using the ATTRACT Coarse­-Grained Force Field and 3D Rotation Maps

International audienceProtein­protein docking algorithms aim to predict how two proteins interact with each other to form a complex. Docking algorithms need to fulfil two main tasks: (1) sampling the possible relative positions of the two proteins and (2) computing the interaction energy at each position. Although the docking problem has been studied for over 25 years, doing this accurately and thoroughly remains a computationally expensive task. We are therefore developing a new algorithm to face the protein docking problem in a novel and efficient way. We are interested in performing an exhaustive search of the rigid­body docking space, where the positioning of the two proteins is not driven by any prior knowledge (e.g. from homology), while still using an accurate force field interaction energy model. In order to reduce the O(N^2) cost of atomistic force­field models, we use a coarse­grained (CG) bead model taken from ATTRACT [1]. However, a naive energy calculation for every trial orientation would still cost O(N^2) energy evaluations in the number of beads. We are therefore developing a method to detect the locations of all possible clashes before performing any energy calculations, thus allowing us to avoid calculating energies for many millions of useless trial orientations. Based on a preliminary study of protein­protein interfaces in complexes from the Protein Docking Benchmark [2], we found that a large number of interfaces contain at least one pair of CG beads at almost their optimal distance. Therefore, our idea is to perform a series of restricted docking searches in which one surface bead from each docking partner is placed in contact at the coordinate origin. This leaves a 3D rotational search, in which ligand may rotate around a fixed receptor. Of course, a full docking search requires all possible pairs of surface beads to be placed together. However, within each rotational sub­problem, we can exploit the fact that rotations do not change any distances from the origin. Thus, we can pre­calculate a "3D rotational map" of all of the rotations that will cause the beads to clash. We can then restrict the remaining rotational search and energy calculation to a small region near the forbidden rotations in the clash map

Using Restraints in EROS-Dock Improves Model Quality in Pairwise and Multicomponent Protein Docking

International audienceProtein docking algorithms aim to predict the 3D structure of a protein complex from the structures of its separated components. In the past, most docking algorithms focused on docking pairs of proteins to form dimeric complexes. However, attention is now turning towards the more difficult problem of using docking methods to predict the structures of multi-component complexes. In both cases, however, the constituent proteins often change conformation upon complex formation, and this can cause many algorithms to fail to detect near-native binding orientations due to the high number of atomic steric clashes in the list of candidate solutions. An increasingly popular way to retain more near-native orientations is to define one or more restraints that serve to modulate or override the effect of steric clashes. Here, we present an updated version of our “EROS-DOCK” docking algorithm which has been extended to dock arbitrary dimeric and trimeric complexes, and to allow the user to define residue-residue or atom-atom interaction restraints. Our results show that using even just one residue-residue restraint in each interaction interface is sufficient to increase the number of cases with acceptable solutions within the top 10 from 51 to 121 out of 173 pairwise docking cases, and to successfully dock 8 out of 11 trimeric complexes

EROS: A Protein Docking Algorithm Using a Quaternion Pi-Ball Representation for Exhaustive and Accelerated Exploration of 3D Rotational Space

International audienceProteins are involved in many essential cellular processes of living organisms. Proteins form macro complexes joining themselves to other proteins to carry out these processes. Therefore, to know the 3D structures of such complexes is of biomedical interest. Protein­protein docking algorithms aim to predict how two proteins interact with each other to form a 3D complex. Docking algorithms need to fulfill two main tasks: (1) sampling all the possible relative positions of the two proteins and (2) computing the interaction energy at each position to find the minimum energy (= the best solution). Obtaining the interaction energy is a computationally expensive task. We are developing a new algorithm based on the ATTRACT coarse­grained force­field [1] and using a quaternion Pi-­ball representation to accelerate the search of the 3D rotational space