title: Functional motions modulating VanA ligand binding unraveled by self-organizing maps.
abstract: The VanA D-Ala:D-Lac ligase is a key enzyme in the emergence of high level resistance to vancomycin in Enterococcus species and methicillin-resistant Staphylococcus aureus. It catalyzes the formation of D-Ala-D-Lac instead of the vancomycin target, D-Ala-D-Ala, leading to the production of modified, low vancomycin binding affinity peptidoglycan precursors. Therefore, VanA appears as an attractive target for the design of new antibacterials to overcome resistance. The catalytic site of VanA is delimited by three domains and closed by an ω-loop upon enzymatic reaction. The aim of the present work was (i) to investigate the conformational transition of VanA associated with the opening of its ω-loop and of a part of its central domain and (ii) to relate this transition with the substrate or product binding propensities. Molecular dynamics trajectories of the VanA ligase of Enterococcus faecium with or without a disulfide bridge distant from the catalytic site revealed differences in the catalytic site conformations with a slight opening. Conformations were clustered with an original machine learning method, based on self-organizing maps (SOM), which revealed four distinct conformational basins. Several ligands related to substrates, intermediates, or products were docked to SOM representative conformations with the DOCK 6.5 program. Classification of ligand docking poses, also performed with SOM, clearly distinguished ligand functional classes: substrates, reaction intermediates, and product. This result illustrates the acuity of the SOM classification and supports the quality of the DOCK program poses. The protein-ligand interaction features for the different classes of poses will guide the search and design of novel inhibitors.
authors.affiliation: Département de Biologie Structurale et Chimie, Institut Pasteur, Unité de Bioinformatique Structurale, CNRS UMR 3825 , 25, rue du Dr Roux, 75015 Paris, France.
authors.forename: Guillaume
authors.initials: G
authors.lastname: Bouvier
authors.forename: Nathalie
authors.initials: N
authors.lastname: Duclert-Savatier
authors.forename: Nathan
authors.initials: N
authors.lastname: Desdouits
authors.forename: Djalal
authors.initials: D
authors.lastname: Meziane-Cherif
authors.forename: Arnaud
authors.initials: A
authors.lastname: Blondel
authors.forename: Patrice
authors.initials: P
authors.lastname: Courvalin
authors.forename: Michael
authors.initials: M
authors.lastname: Nilges
authors.forename: Thérèse E
authors.initials: TE
authors.lastname: Malliavin
mesh_terms: D001185:Artificial Intelligence; D001426:Bacterial Proteins / Q000737:chemistry* / Q000378:metabolism*; D019729:Carbon-Oxygen Ligases / Q000737:chemistry* / Q000378:metabolism*; D020134:Catalytic Domain; D019295:Computational Biology; D018360:Crystallography, X-Ray; D015195:Drug Design; D016984:Enterococcus faecium / Q000201:enzymology; D008024:Ligands; D008958:Models, Molecular; D056004:Molecular Dynamics Simulation; D011487:Protein Conformation; D012984:Software; D020713:Vancomycin Resistance
chemical_list: D001426:Bacterial Proteins; D008024:Ligands; C071437:VanA ligase, Bacteria; D019729:Carbon-Oxygen Ligases