Jessica Andreani

Bio: Jessica Andreani is an academic researcher from Université Paris-Saclay. The author has contributed to research in topics: Homologous recombination & Macromolecular docking. The author has an hindex of 15, co-authored 36 publications receiving 755 citations. Previous affiliations of Jessica Andreani include University of Paris-Sud & French Alternative Energies and Atomic Energy Commission.

InterEvScore: a novel coarse-grained interface scoring function using a multi-body statistical potential coupled to evolution.

Abstract: Motivation: Structural prediction of protein interactions currently remains a challenging but fundamental goal. In particular, progress in scoring functions is critical for the efficient discrimination of nearnative interfaces among large sets of decoys. Many functions have been developed using knowledge-based potentials, but few make use of multi-body interactions or evolutionary information, although multiresidue interactions are crucial for protein–protein binding and protein interfaces undergo significant selection pressure to maintain their interactions. Results: This article presents InterEvScore, a novel scoring function using a coarse-grained statistical potential including two- and threebody interactions, which provides each residue with the opportunity to contribute in its most favorable local structural environment. Combination of this potential with evolutionary information considerably improves scoring results on the 54 test cases from the widely used protein docking benchmark for which evolutionary information can be collected. We analyze how our way to include evolutionary information gradually increases the discriminative power of InterEvScore. Comparison with several previously published scoring functions (ZDOCK, ZRANK and SPIDER) shows the significant progress brought by InterEvScore. Availability: http://biodev.cea.fr/interevol/interevscore Contact: guerois@cea.fr Supplementary information: Supplementary data are available at Bioinformatics online.

A structural model of the active ribosome-bound membrane protein insertase YidC

Abstract: The integration of most membrane proteins into the cytoplasmic membrane of bacteria occurs co-translationally. The universally conserved YidC protein mediates this process either individually as a membrane protein insertase, or in concert with the SecY complex. Here, we present a structural model of YidC based on evolutionary co-variation analysis, lipid-versus-protein-exposure and molecular dynamics simulations. The model suggests a distinctive arrangement of the conserved five transmembrane domains and a helical hairpin between transmembrane segment 2 (TM2) and TM3 on the cytoplasmic membrane surface. The model was used for docking into a cryo-electron microscopy reconstruction of a translating YidC-ribosome complex carrying the YidC substrate FOc. This structure reveals how a single copy of YidC interacts with the ribosome at the ribosomal tunnel exit and identifies a site for membrane protein insertion at the YidC protein-lipid interface. Together, these data suggest a mechanism for the co-translational mode of YidC-mediated membrane protein insertion.

A meiotic XPF-ERCC1-like complex recognizes joint molecule recombination intermediates to promote crossover formation.

Abstract: Meiotic crossover formation requires the stabilization of early recombination intermediates by a set of proteins and occurs within the environment of the chromosome axis, a structure important for the regulation of meiotic recombination events. The molecular mechanisms underlying and connecting crossover recombination and axis localization are elusive. Here, we identified the ZZS (Zip2-Zip4-Spo16) complex, required for crossover formation, which carries two distinct activities: one provided by Zip4, which acts as hub through physical interactions with components of the chromosome axis and the crossover machinery, and the other carried by Zip2 and Spo16, which preferentially bind branched DNA molecules in vitro. We found that Zip2 and Spo16 share structural similarities to the structure-specific XPF-ERCC1 nuclease, although it lacks endonuclease activity. The XPF domain of Zip2 is required for crossover formation, suggesting that, together with Spo16, it has a noncatalytic DNA recognition function. Our results suggest that the ZZS complex shepherds recombination intermediates toward crossovers as a dynamic structural module that connects recombination events to the chromosome axis. The identification of the ZZS complex improves our understanding of the various activities required for crossover implementation and is likely applicable to other organisms, including mammals.

InterEvDock: a docking server to predict the structure of protein-protein interactions using evolutionary information.

Abstract: The structural modeling of protein-protein interactions is key in understanding how cell machineries cross-talk with each other. Molecular docking simulations provide efficient means to explore how two unbound protein structures interact. InterEvDock is a server for protein docking based on a free rigid-body docking strategy. A systematic rigid-body docking search is performed using the FRODOCK program and the resulting models are re-scored with InterEvScore and SOAP-PP statistical potentials. The InterEvScore potential was specifically designed to integrate co-evolutionary information in the docking process. InterEvDock server is thus particularly well suited in case homologous sequences are available for both binding partners. The server returns 10 structures of the most likely consensus models together with 10 predicted residues most likely involved in the interface. In 91% of all complexes tested in the benchmark, at least one residue out of the 10 predicted is involved in the interface, providing useful guidelines for mutagenesis. InterEvDock is able to identify a correct model among the top10 models for 49% of the rigid-body cases with evolutionary information, making it a unique and efficient tool to explore structural interactomes under an evolutionary perspective. The InterEvDock web interface is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock/.

The ClusPro web server for protein-protein docking.

Abstract: The ClusPro server (https://cluspro.org) is a widely used tool for protein-protein docking. The server provides a simple home page for basic use, requiring only two files in Protein Data Bank (PDB) format. However, ClusPro also offers a number of advanced options to modify the search; these include the removal of unstructured protein regions, application of attraction or repulsion, accounting for pairwise distance restraints, construction of homo-multimers, consideration of small-angle X-ray scattering (SAXS) data, and location of heparin-binding sites. Six different energy functions can be used, depending on the type of protein. Docking with each energy parameter set results in ten models defined by centers of highly populated clusters of low-energy docked structures. This protocol describes the use of the various options, the construction of auxiliary restraints files, the selection of the energy parameters, and the analysis of the results. Although the server is heavily used, runs are generally completed in <4 h.

Scalable molecular dynamics on CPU and GPU architectures with NAMD.

Abstract: NAMDis a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

End-Point Binding Free Energy Calculation with MM/PBSA and MM/GBSA: Strategies and Applications in Drug Design

Abstract: Molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics generalized Born surface area (MM/GBSA) are arguably very popular methods for binding free energy prediction since they are more accurate than most scoring functions of molecular docking and less computationally demanding than alchemical free energy methods. MM/PBSA and MM/GBSA have been widely used in biomolecular studies such as protein folding, protein-ligand binding, protein-protein interaction, etc. In this review, methods to adjust the polar solvation energy and to improve the performance of MM/PBSA and MM/GBSA calculations are reviewed and discussed. The latest applications of MM/GBSA and MM/PBSA in drug design are also presented. This review intends to provide readers with guidance for practically applying MM/PBSA and MM/GBSA in drug design and related research fields.

Coarse-Grained Protein Models and Their Applications

Abstract: The traditional computational modeling of protein structure, dynamics, and interactions remains difficult for many protein systems. It is mostly due to the size of protein conformational spaces and required simulation time scales that are still too large to be studied in atomistic detail. Lowering the level of protein representation from all-atom to coarse-grained opens up new possibilities for studying protein systems. In this review we provide an overview of coarse-grained models focusing on their design, including choices of representation, models of energy functions, sampling of conformational space, and applications in the modeling of protein structure, dynamics, and interactions. A more detailed description is given for applications of coarse-grained models suitable for efficient combinations with all-atom simulations in multiscale modeling strategies.

HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy.

Abstract: Protein-protein and protein-DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein-protein and protein-DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10-20 min for a docking run. Tested on the cases with weakly homologous complexes of <30% sequence identity from five docking benchmarks, the HDOCK pipeline tied with template-based modeling on the protein-protein and protein-DNA benchmarks and performed better than template-based modeling on the three protein-RNA benchmarks when the top 10 predictions were considered. The performance of HDOCK became better when more predictions were considered. Combining the results of HDOCK and template-based modeling by ranking first of the template-based model further improved the predictive power of the server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/.