Azetidinimines as a novel series of non-covalent broad-spectrum inhibitors of β-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 β-lactamases which render most β-lactam antibiotics useless. Herein, we report the development of a series of imino-analogues of β-lactams (namely azetidinimines) as efficient non-covalent inhibitors of β-lactamases. Despite the structural and mechanistic differences between serine-β-lactamases KPC-2 and OXA-48 and metallo-β-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.

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.

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.

SAMPL6: calculation of macroscopic pK values from ab initio quantum mechanical free energies.

Macroscopic pK values were calculated for all compounds in the SAMPL6 blind prediction challenge, based on quantum chemical calculations with a continuum solvation model and a linear correction derived from a small training set. Microscopic pK values were derived from the gas-phase free energy difference between protonated and deprotonated forms together with the Conductor-like Polarizable Continuum Solvation Model and the experimental solvation free energy of the proton. pH-dependent microstate free energies were obtained from the microscopic pKs with a maximum likelihood estimator and appropriately summed to yield macroscopic pK values or microstate populations as function of pH.

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.

Molecular docking performance evaluated on the D3R Grand Challenge 2015 drug-like ligand datasets.

The D3R Grand Challenge 2015 was focused on two protein targets: Heat Shock Protein 90 (HSP90) and Mitogen-Activated Protein Kinase Kinase Kinase Kinase 4 (MAP4K4). We used a protocol involving a preliminary analysis of the available data in PDB and PubChem BioAssay, and then a docking/scoring step using more computationally demanding parameters that were required to provide more reliable predictions. We could evidence that different docking software and scoring functions can behave differently on individual ligand datasets, and that the flexibility of specific binding site residues is a crucial element to provide good predictions.

Blind Pose Prediction, Scoring, and Affinity Ranking of the CSAR 2014 Dataset.

The 2014 CSAR Benchmark Exercise was focused on three protein targets: coagulation factor Xa, spleen tyrosine kinase, and bacterial tRNA methyltransferase. Our protocol involved a preliminary analysis of the structural information available in the Protein Data Bank for the protein targets, which allowed the identification of the most appropriate docking software and scoring functions to be used for the rescoring of several docking conformations datasets, as well as for pose prediction and affinity ranking. The two key points of this study were (i) the prior evaluation of molecular modeling tools that are most adapted for each target and (ii) the increased search efficiency during the docking process to better explore the conformational space of big and flexible ligands.

Allosteric activation of Bordetella pertussis adenylyl cyclase by calmodulin: molecular dynamics and mutagenesis studies.

Adenylyl cyclase (AC) toxin is an essential toxin that allows Bordetella pertussis to invade eukaryotic cells, where it is activated after binding to calmodulin (CaM). Based on the crystal structure of the AC catalytic domain in complex with the C-terminal half of CaM (C-CaM), our previous molecular dynamics simulations (Selwa, E., Laine, E.

Temperature-accelerated molecular dynamics gives insights into globular conformations sampled in the free state of the AC catalytic domain.

The catalytic domain of the adenyl cyclase (AC) toxin from Bordetella pertussis is activated by interaction with calmodulin (CaM), resulting in cAMP overproduction in the infected cell. In the X-ray crystallographic structure of the complex between AC and the C terminal lobe of CaM, the toxin displays a markedly elongated shape. As for the structure of the isolated protein, experimental results support the hypothesis that more globular conformations are sampled, but information at atomic resolution is still lacking.

Characterization of a membrane-active peptide from the Bordetella pertussis CyaA toxin.

Bordetella pertussis, the pathogenic bacteria responsible for whooping cough, secretes several virulence factors, among which is the adenylate cyclase toxin (CyaA) that plays a crucial role in the early stages of human respiratory tract colonization. CyaA invades target cells by translocating its catalytic domain directly across the plasma membrane and overproduces cAMP, leading to cell death. The molecular process leading to the translocation of the catalytic domain remains largely unknown.

Differential role of calmodulin and calcium ions in the stabilization of the catalytic domain of adenyl cyclase CyaA from Bordetella pertussis.

The catalytic adenyl cyclase (AC) domain of the protein CyaA from Bordetella pertussis is activated by interaction with the C terminal lobe of calmodulin (C-CaM). The AC/C-CaM complex displays an elongated shape, but hydrodynamics measurements on the isolated AC domain allowed to characterize the shape of the protein as spherical. Here, we study by molecular dynamics simulations the complexes between AC and the apo and Ca(2+)-loaded C-CaM, as well as the isolated AC, to characterize the features of AC conformational variability and of AC/C-CaM interaction.