Rescoring ensembles of protein-protein docking poses using consensus approaches

Scoring is a challenging step in protein-protein docking, where typically thousands of solutions are generated. Successful scoring is more often based on physicochemical evaluation of the generated interfaces and/or statistical potentials that reproduce known interface properties. Another route is offered by consensus-based rescoring, where the set of solutions is used to build statistics in order to identify recurrent solutions. We explore several ways to perform consensus-based rescoring on the ZDOCK decoy set for Benchmark 4. We show that the information of the interface size is critical for successful rescoring. We combine consensus-based rescoring with the ZDOCK native scoring function and show that this improves the initial results.Scoring is a challenging step in protein-protein docking, where typically thousands of solutions are generated. Successful scoring is more often based on physicochemical evaluation of the generated interfaces and/or statistical potentials that reproduce known interface properties. Another route is offered by consensus-based rescoring, where the set of solutions is used to build statistics in order to identify recurrent solutions. We explore several ways to perform consensus-based rescoring on the ZDOCK decoy set for Benchmark 4. We show that the information of the interface size is critical for successful rescoring. We combine consensus-based rescoring with the ZDOCK native scoring function and show that this improves the initial results

Targeted-antibacterial-plasmids (TAPs) combining conjugation and CRISPR/Cas systems achieve strain-specific antibacterial activity

International audienceThe global emergence of drug-resistant bacteria leads to the loss of efficacy of our antibiotics arsenal and severely limits the success of currently available treatments. Here, we developed an innovative strategy based on targeted-antibacterial-plasmids (TAPs) that use bacterial conjugation to deliver CRISPR/Cas systems exerting a strain-specific antibacterial activity. TAPs are highly versatile as they can be directed against any specific genomic or plasmid DNA using the custom algorithm (CSTB) that identifies appropriate targeting spacer sequences. We demonstrate the ability of TAPs to induce strain-selective killing by introducing lethal double strand breaks (DSBs) into the targeted genomes. TAPs directed against a plasmid-born carbapenem resistance gene efficiently resensitise the strain to the drug. This work represents an essential step toward the development of an alternative to antibiotic treatments, which could be used for in situ microbiota modification to eradicate targeted resistant and/or pathogenic bacteria without affecting other non-targeted bacterial species

The Det.Belt Server: A Tool to Visualize and Estimate Amphipathic Solvent Belts around Membrane Proteins

Detergents wrap around membrane proteins to form a belt covering the hydrophobic part of the protein serving for membrane insertion and interaction with lipids. The number of detergent monomers forming this belt is usually unknown to investigators, unless dedicated detergent quantification is undertaken, which for many projects is difficult to setup. Yet, having an approximate knowledge of the amount of detergent forming the belt is extremely useful, to better grasp the protein of interest in interaction with its direct environment rather than picturing the membrane protein “naked”. We created the Det.Belt server to dress up membrane proteins and represent in 3D the bulk made by detergent molecules wrapping in a belt. Many detergents are included in a database, allowing investigators to screen in silico the effect of different detergents around their membrane protein. The input number of detergents is changeable with fast recomputation of the belt for interactive usage. Metrics representing the belt are readily available together with scripts to render quality 3D images for publication. The Det.Belt server is a tool for biochemists to better grasp their sample

Facilitating CG Simulations with MAD: The MArtini Database Server

The MArtini Database (MAD - https://mad.ibcp.fr) is a web server designed for the sharing of structures and topologies of molecules parametrized with the Martini coarse-grained (CG) force field. MAD can also convert atomistic structures into CG structures and prepare complex systems (including proteins, lipids, etc.) for molecular dynamics (MD) simulations at the CG level. It is dedicated to the generation of input files for Martini 3, the most recent version of this popular CG force field. Specifically, the MAD server currently includes tools to submit or retrieve CG models of a wide range of molecules (lipids, carbohydrates, nanoparticles, etc.), transform atomistic protein structures into CG structures and topologies, with fine control on the process and assemble biomolecules into large systems, and deliver all files necessary to start simulations in the GROMACS MD engine