Detection and Characterization of VIM-52, a New Variant of VIM-1 from a Klebsiella pneumoniae Clinical Isolate.

Over the last two decades, antimicrobial resistance has become a global health problem. In Gram-negative bacteria, metallo-ß-lactamases (MBLs), which inactivate virtually all ß-lactams, increasingly contribute to this phenomenon. The aim of this study is to characterize VIM-52, a His224Arg variant of VIM-1, identified in a Klebsiella pneumoniae clinical isolate. VIM-52 conferred lower MICs to cefepime and ceftazidime compared to VIM-1. These results were confirmed by steady-state kinetic measurements, where VIM-52 yielded a lower activity toward ceftazidime and cefepime but not against carbapenems. Residue 224 is part of the L10 loop (residues 221 to 241), which borders the active site. As Arg 224 and Ser 228 both play an important and interrelated role in enzymatic activity, stability, and substrate specificity for the MBLs, targeted mutagenesis at both positions was performed and further confirmed their crucial role for substrate specificity.

Blinded evaluation of cathepsin S inhibitors from the D3RGC3 dataset using molecular docking and free energy calculations.

During the last few years, we have developed a docking protocol involving two steps: (i) the choice of the most appropriate docking software and parameters for the system of interest using structural and functional information available in public databases (PDB, ChEMBL, PubChem Assay, BindingDB, etc.); (ii) the docking of ligand dataset to provide a prediction for the binding modes and ranking of ligands. We applied this protocol to the D3R Grand Challenge 3 dataset containing cathepsin S (CatS) inhibitors. Considering the size and conformational flexibility of ligands, the docking calculations afforded reasonable overall pose predictions, which are however dependent on the specific nature of each ligand. As expected, the correct ranking of docking poses is still challenging. Post-processing of docking poses with molecular dynamics simulations in explicit solvent provided a significantly better prediction, whereas free energy calculations on a subset of compounds brought no significant improvement in the ranking prediction compared with the direct ranking obtained from the scoring function.

Performance evaluation of molecular docking and free energy calculations protocols using the D3R Grand Challenge 4 dataset.

Using the D3R Grand Challenge 4 dataset containing Beta-secretase 1 (BACE) and Cathepsin S (CatS) inhibitors, we have evaluated the performance of our in-house docking workflow that involves in the first step the selection of the most suitable docking software for the system of interest based on structural and functional information available in public databases, followed by the docking of the dataset to predict the binding modes and ranking of ligands. The macrocyclic nature of the BACE ligands brought additional challenges, which were dealt with by a careful preparation of the three-dimensional input structures for ligands. This provided top-performing predictions for BACE, in contrast with CatS, where the predictions in the absence of guiding constraints provided poor results. These results highlight the importance of previous structural knowledge that is needed for correct predictions on some challenging targets. After the end of the challenge, we also carried out free energy calculations (i.e. in a non-blinded manner) for CatS using the pmx software and several force fields (AMBER, Charmm). Using knowledge-based starting pose construction allowed reaching remarkable accuracy for the CatS free energy estimates. Interestingly, we show that the use of a consensus result, by averaging the results from different force fields, increases the prediction accuracy.

Blinded evaluation of farnesoid X receptor (FXR) ligands binding using molecular docking and free energy calculations.

Our participation to the D3R Grand Challenge 2 involved a protocol in two steps, with an initial analysis of the available structural data from the PDB allowing the selection of the most appropriate combination of docking software and scoring function. Subsequent docking calculations showed that the pose prediction can be carried out with a certain precision, but this is dependent on the specific nature of the ligands. The correct ranking of docking poses is still a problem and cannot be successful in the absence of good pose predictions. Our free energy calculations on two different subsets provided contrasted results, which might have the origin in non-optimal force field parameters associated with the sulfonamide chemical moiety.

A refined picture of the native amine dehydrogenase family revealed by extensive biodiversity screening.

Native amine dehydrogenases offer sustainable access to chiral amines, so the search for scaffolds capable of converting more diverse carbonyl compounds is required to reach the full potential of this alternative to conventional synthetic reductive aminations. Here we report a multidisciplinary strategy combining bioinformatics, chemoinformatics and biocatalysis to extensively screen billions of sequences in silico and to efficiently find native amine dehydrogenases features using computational approaches. In this way, we achieve a comprehensive overview of the initial native amine dehydrogenase family, extending it from 2,011 to 17,959 sequences, and identify native amine dehydrogenases with non-reported substrate spectra, including hindered carbonyls and ethyl ketones, and accepting methylamine and cyclopropylamine as amine donor. We also present preliminary model-based structural information to inform the design of potential (R)-selective amine dehydrogenases, as native amine dehydrogenases are mostly (S)-selective. This integrated strategy paves the way for expanding the resource of other enzyme families and in highlighting enzymes with original features.

Azetidinimines as a novel series of non-covalent broad-spectrum inhibitors of ß-lactamases with submicromolar activities against carbapenemases KPC-2 (class A), NDM-1 (class B) and OXA-48 (class D).

The occurrence of resistances in Gram negative bacteria is steadily increasing to reach extremely worrying levels and one of the main causes of resistance is the massive spread of very efficient ß-lactamases which render most ß-lactam antibiotics useless. Herein, we report the development of a series of imino-analogues of ß-lactams (namely azetidinimines) as efficient non-covalent inhibitors of ß-lactamases. Despite the structural and mechanistic differences between serine-ß-lactamases KPC-2 and OXA-48 and metallo-ß-lactamase NDM-1, all three enzymes can be inhibited at a submicromolar level by compound 7dfm, which can also repotentiate imipenem against a resistant strain of Escherichia coli expressing NDM-1. We show that 7dfm can efficiently inhibit not only the three main clinically-relevant carbapenemases of Ambler classes A (KPC-2), B (NDM-1) and D (OXA-48) with Ki's below 0.3 µM, but also the cephalosporinase CMY-2 (class C, 86% inhibition at 10 µM). Our results pave the way for the development of a new structurally original family of non-covalent broad-spectrum inhibitors of ß-lactamases.

Genetic, Biochemical, and Structural Characterization of CMY-136 ß-Lactamase, a Peculiar CMY-2 Variant.

With the widespread use and abuse of antibiotics for the past decades, antimicrobial resistance poses a serious threat to public health nowadays. ß-Lactams are the most used antibiotics, and ß-lactamases are the most widespread resistance mechanism. Class C ß-lactamases, also known as cephalosporinases, usually do not hydrolyze the latest and most potent ß-lactams, expanded spectrum cephalosporins and carbapenems. However, the recent emergence of extended-spectrum AmpC cephalosporinases, their resistance to inhibition by classic ß-lactamase inhibitors, and the fact that they can contribute to carbapenem resistance when paired with impermeability mechanisms, means that these enzymes may still prove worrisome in the future. Here we report and characterize the CMY-136 ß-lactamase, a Y221H point mutant derivative of CMY-2. CMY-136 confers an increased level of resistance to ticarcillin, cefuroxime, cefotaxime, and ceftolozane/tazobactam. It is also capable of hydrolyzing ticarcillin and cloxacillin, which act as inhibitors of CMY-2. X-ray crystallography and modeling experiments suggest that the hydrolytic profile alterations seem to be the result of an increased flexibility and altered conformation of the Ω-loop, caused by the Y221H mutation.