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.

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 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.

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

Macroscopic pKa 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 pKa 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 pKas with a maximum likelihood estimator and appropriately summed to yield macroscopic pKa values or microstate populations as function of pH. We assessed the accuracy of three approaches to calculate the microscopic pKas: direct use of the quantum mechanical free energy differences and correction of the direct values for short-comings in the QM solvation model with two different linear models that we independently derived from a small training set of 38 compounds with known pKa. The predictions that were corrected with the linear models had much better accuracy [root-mean-square error (RMSE) 2.04 and 1.95 pKa units] than the direct calculation (RMSE 3.74). Statistical measures indicate that some systematic errors remain, likely due to differences in the SAMPL6 data set and the small training set with respect to their interactions with water. Overall, the current approach provides a viable physics-based route to estimate macroscopic pKa values for novel compounds with reasonable 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.

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., and Malliavin, T. (2012) Differential role of calmodulin and calcium ions in the stabilization of the catalytic domain of adenyl cyclase CyaA from Bordetella pertussis. Proteins 80, 1028­1040) suggested that three residues (i.e. Arg(338), Asn(347), and Asp(360)) might be important for stabilizing the AC/CaM interaction. These residues belong to a loop-helix-loop motif at the C-terminal end of AC, which is located at the interface between CaM and the AC catalytic loop. In the present study, we conducted the in silico and in vitro characterization of three AC variants, where one (Asn(347); ACm1A), two (Arg(338) and Asp(360); ACm2A), or three residues (Arg(338), Asn(347), and Asp(360); ACm3A) were substituted with Ala. Biochemical studies showed that the affinities of ACm1A and ACm2A for CaM were not affected significantly, whereas that of ACm3A was reduced dramatically. To understand the effects of these modifications, molecular dynamics simulations were performed based on the modified proteins. The molecular dynamics trajectories recorded for the ACm3AC-CaM complex showed that the calcium-binding loops of C-CaM exhibited large fluctuations, which could be related to the weakened interaction between ACm3A and its activator. Overall, our results suggest that the loop-helix-loop motif at the C-terminal end of AC is crucial during CaM binding for stabilizing the AC catalytic loop in an active configuration.

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. Here, we use temperature-accelerated molecular dynamics (TAMD) simulations to generate putative all-atom models of globular conformations sampled by CaM-free AC. As collective variables, we use centers of mass coordinates of groups of residues selected from the analysis of standard molecular dynamics (MD) simulations. Results show that TAMD allows extended conformational sampling and generates AC conformations that are more globular than in the complexed state. These structures are then refined via energy minimization and further unrestrained MD simulations to optimize inter-domain packing interactions, thus resulting in the identification of a set of hydrogen bonds present in the globular conformations.

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. We have previously shown that the catalytic domain per se, AC384, encompassing residues 1-384 of CyaA, did not interact with lipid bilayer, whereas a longer polypeptide, AC489, spanning residues 1-489, binds to membranes and permeabilizes vesicles. Moreover, deletion of residues 375-485 within CyaA abrogated the translocation of the catalytic domain into target cells. Here, we further identified within this region a peptidic segment that exhibits membrane interaction properties. A synthetic peptide, P454, corresponding to this sequence (residues 454-485 of CyaA) was characterized by various biophysical approaches. We found that P454 (i) binds to membranes containing anionic lipids, (ii) adopts an α-helical structure oriented in plane with respect to the lipid bilayer, and (iii) permeabilizes vesicles. We propose that the region encompassing the helix 454-485 of CyaA may insert into target cell membrane and induce a local destabilization of the lipid bilayer, thus favoring the translocation of the catalytic domain across the plasma membrane.

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. The removal of calcium ions from C-CaM increases the AC flexibility, but the removal of C-CaM induces a dramatic drift of the AC conformation. Isolated AC conformations show a general tendency to become less elongated, as the two protein extremities (regions SA and CB) tend to get closer. An analysis of the energetic influences between the C-CaM and the AC regions shows a simple influence scheme, in agreement with the high affinity of AC to CaM. In this scheme, a single influence is observed from C-CaM to the region CA of the AC domain. This influence is correlated to the presence of hydrogen bonds involving residues from C-CaM, and from regions CA, C-terminal tail, and catalytic loop of AC. This study reveals a C-CaM/AC interaction picture where C-CaM stabilizes AC by a steric hindrance on the conformational drift of SA, whereas the Ca(2+) ions allow further stabilization by the establishment of a hydrogen bond network extending from C-CaM to the AC catalytic loop.