Peptide Suboptimal Conformation Sampling for the Prediction of Protein-Peptide Interactions.

The blind identification of candidate patches of interaction on the protein surface is a difficult task that can hardly be accomplished without a heuristic or the use of simplified representations to speed up the search. The PEP-SiteFinder protocol performs a systematic blind search on the protein surface using a rigid docking procedure applied to a limited set of peptide suboptimal conformations expected to approximate satisfactorily the conformation of the peptide in interaction. All steps rely on a coarse-grained representation of the protein and the peptide. While simple, such a protocol can help to infer useful information, assuming a critical analysis of the results. Moreover, such a protocol can be extended to a semi-flexible protocol where the suboptimal conformations are directly folded in the vicinity of the receptor.

An integrative approach to the study of filamentous oligomeric assemblies, with application to RecA.

Oligomeric macromolecules in the cell self-organize into a wide variety of geometrical motifs such as helices, rings or linear filaments. The recombinase proteins involved in homologous recombination present many such assembly motifs. Here, we examine in particular the polymorphic characteristics of RecA, the most studied member of the recombinase family, using an integrative approach that relates local modes of monomer/monomer association to the global architecture of their screw-type organization. In our approach, local modes of association are sampled via docking or Monte Carlo simulations. This enables shedding new light on fiber morphologies that may be adopted by the RecA protein. Two distinct RecA helical morphologies, the so-called "extended" and "compressed" forms, are known to play a role in homologous recombination. We investigate the variability within each form in terms of helical parameters and steric accessibility. We also address possible helical discontinuities in RecA filaments due to multiple monomer-monomer association modes. By relating local interface organization to global filament morphology, the strategies developed here to study RecA self-assembly are particularly well suited to other DNA-binding proteins and to filamentous protein assemblies in general.

PEP-SiteFinder: a tool for the blind identification of peptide binding sites on protein surfaces.

Peptide-protein interactions are important to many processes of life, particularly for signal transmission or regulatory mechanisms. When no information is known about the interaction between a protein and a peptide, it is of interest to propose candidate sites of interaction at the protein surface, to assist the design of biological experiments to probe the interaction, or to serve as a starting point for more focused in silico approaches. PEP-SiteFinder is a tool that will, given the structure of a protein and the sequence of a peptide, identify protein residues predicted to be at peptide-protein interface. PEP-SiteFinder relies on the 3D de novo generation of peptide conformations given its sequence. These conformations then undergo a fast blind rigid docking on the complete protein surface, and we have found, as the result of a benchmark over 41 complexes, that the best poses overlap to some extent the experimental patch of interaction for close to 90% complexes. In addition, PEP-SiteFinder also returns a propensity index we have found informative about the confidence of the prediction. The PEP-SiteFinder web server is available at http://bioserv.rpbs.univ-paris-diderot.fr/PEP-SiteFinder.

ATTRACT and PTools: open source programs for protein-protein docking.

The prediction of the structure of protein-protein complexes based on structures or structural models of isolated partners is of increasing importance for structural biology and bioinformatics. The ATTRACT program can be used to perform systematic docking searches based on docking energy minimization. It is part of the object-oriented PTools library written in Python and C++. The library contains various routines to manipulate protein structures, to prepare and perform docking searches as well as analyzing docking results. It also intended to facilitate further methodological developments in the area of macromolecular docking that can be easily integrated. Here, we describe the application of PTools to perform systematic docking searches and to analyze the results. In addition, the possibility to perform multi-component docking will also be presented.

SA-Mot: a web server for the identification of motifs of interest extracted from protein loops.

The detection of functional motifs is an important step for the determination of protein functions. We present here a new web server SA-Mot (Structural Alphabet Motif) for the extraction and location of structural motifs of interest from protein loops. Contrary to other methods, SA-Mot does not focus only on functional motifs, but it extracts recurrent and conserved structural motifs involved in structural redundancy of loops. SA-Mot uses the structural word notion to extract all structural motifs from uni-dimensional sequences corresponding to loop structures. Then, SA-Mot provides a description of these structural motifs using statistics computed in the loop data set and in SCOP superfamily, sequence and structural parameters. SA-Mot results correspond to an interactive table listing all structural motifs extracted from a target structure and their associated descriptors. Using this information, the users can easily locate loop regions that are important for the protein folding and function. The SA-Mot web server is available at http://sa-mot.mti.univ-paris-diderot.fr.

Accounting for large amplitude protein deformation during in silico macromolecular docking.

Rapid progress of theoretical methods and computer calculation resources has turned in silico methods into a conceivable tool to predict the 3D structure of macromolecular assemblages, starting from the structure of their separate elements. Still, some classes of complexes represent a real challenge for macromolecular docking methods. In these complexes, protein parts like loops or domains undergo large amplitude deformations upon association, thus remodeling the surface accessible to the partner protein or DNA. We discuss the problems linked with managing such rearrangements in docking methods and we review strategies that are presently being explored, as well as their limitations and success.

Modeling the early stage of DNA sequence recognition within RecA nucleoprotein filaments.

Homologous recombination is a fundamental process enabling the repair of double-strand breaks with a high degree of fidelity. In prokaryotes, it is carried out by RecA nucleofilaments formed on single-stranded DNA (ssDNA). These filaments incorporate genomic sequences that are homologous to the ssDNA and exchange the homologous strands. Due to the highly dynamic character of this process and its rapid propagation along the filament, the sequence recognition and strand exchange mechanism remains unknown at the structural level. The recently published structure of the RecA/DNA filament active for recombination (Chen et al., Mechanism of homologous recombination from the RecA-ssDNA/dsDNA structure, Nature 2008, 453, 489) provides a starting point for new exploration of the system. Here, we investigate the possible geometries of association of the early encounter complex between RecA/ssDNA filament and double-stranded DNA (dsDNA). Due to the huge size of the system and its dense packing, we use a reduced representation for protein and DNA together with state-of-the-art molecular modeling methods, including systematic docking and virtual reality simulations. The results indicate that it is possible for the double-stranded DNA to access the RecA-bound ssDNA while initially retaining its Watson-Crick pairing. They emphasize the importance of RecA L2 loop mobility for both recognition and strand exchange.

PTools: an opensource molecular docking library.

BACKGROUND: Macromolecular docking is a challenging field of bioinformatics. Developing new algorithms is a slow process generally involving routine tasks that should be found in a robust library and not programmed from scratch for every new software application. RESULTS: We present an object-oriented Python/C++ library to help the development of new docking methods. This library contains low-level routines like PDB-format manipulation functions as well as high-level tools for docking and analyzing results. We also illustrate the ease of use of this library with the detailed implementation of a 3-body docking procedure. CONCLUSION: The PTools library can handle molecules at coarse-grained or atomic resolution and allows users to rapidly develop new software. The library is already in use for protein-protein and protein-DNA docking with the ATTRACT program and for simulation analysis. This library is freely available under the GNU GPL license, together with detailed documentation.