Inverse Conformational Selection in Lipid-Protein Binding.

Interest in lipid interactions with proteins and other biomolecules is emerging not only in fundamental biochemistry but also in the field of nanobiotechnology where lipids are commonly used, for example, in carriers of mRNA vaccines. The outward-facing components of cellular membranes and lipid nanoparticles, the lipid headgroups, regulate membrane interactions with approaching substances, such as proteins, drugs, RNA, or viruses. Because lipid headgroup conformational ensembles have not been experimentally determined in physiologically relevant conditions, an essential question about their interactions with other biomolecules remains unanswered: Do headgroups exchange between a few rigid structures, or fluctuate freely across a practically continuous spectrum of conformations? Here, we combine solid-state NMR experiments and molecular dynamics simulations from the NMRlipids Project to resolve the conformational ensembles of headgroups of four key lipid types in various biologically relevant conditions. We find that lipid headgroups sample a wide range of overlapping conformations in both neutral and charged cellular membranes, and that differences in the headgroup chemistry manifest only in probability distributions of conformations. Furthermore, the analysis of 894 protein-bound lipid structures from the Protein Data Bank suggests that lipids can bind to proteins in a wide range of conformations, which are not limited by the headgroup chemistry. We propose that lipids can select a suitable headgroup conformation from the wide range available to them to fit the various binding sites in proteins. The proposed inverse conformational selection model will extend also to lipid binding to targets other than proteins, such as drugs, RNA, and viruses.

Irreversible covalent modification of type I dehydroquinase with a stable Schiff base.

The irreversible inhibition of type I dehydroquinase (DHQ1), the third enzyme of the shikimic acid pathway, is investigated by structural, biochemical and computational studies. Two epoxides, which are mimetics of the natural substrate, were designed as irreversible inhibitors of the DHQ1 enzyme and to study the binding requirements of the linkage to the enzyme. The epoxide with the S configuration caused the covalent modification of the protein whereas no reaction was obtained with its epimer. The first crystal structure of DHQ1 from Salmonella typhi covalently modified by the S epoxide, which is reported at 1.4 Å, revealed that the modified ligand is surprisingly covalently attached to the essential Lys170 by the formation of a stable Schiff base. The experimental and molecular dynamics simulation studies reported here highlight the huge importance of the conformation of the C3 carbon of the ligand for covalent linkage to this type of aldolase I enzyme, revealed the key role played by the essential His143 as a Lewis acid in this process and show the need for a neatly closed active site for catalysis.

Mechanistic insight into the reaction catalysed by bacterial type II dehydroquinases.

DHQ2 (type II dehydroquinase), which is an essential enzyme in Helicobacter pylori and Mycobacterium tuberculosis and does not have any counterpart in humans, is recognized to be an attractive target for the development of new antibacterial agents. Computational and biochemical studies that help understand in atomic detail the catalytic mechanism of these bacterial enzymes are reported in the present paper. A previously unknown key role of certain conserved residues of these enzymes, as well as the structural changes responsible for triggering the release of the product from the active site, were identified. Asp89*/Asp88* from a neighbouring enzyme subunit proved to be the residue responsible for the deprotonation of the essential tyrosine to afford the catalytic tyrosinate, which triggers the enzymatic process. The essentiality of this residue is supported by results from site-directed mutagenesis. For H. pylori DHQ2, this reaction takes place through the assistance of a water molecule, whereas for M. tuberculosis DHQ2, the tyrosine is directly deprotonated by the aspartate residue. The participation of a water molecule in this deprotonation reaction is supported by solvent isotope effects and proton inventory studies. MD simulation studies provide details of the required motions for the catalytic turnover, which provides a complete overview of the catalytic cycle. The product is expelled from the active site by the essential arginine residue and after a large conformational change of a loop containing two conserved arginine residues (Arg109/Arg108 and Arg113/Arg112), which reveals a previously unknown key role for these residues. The present study highlights the key role of the aspartate residue whose blockage could be useful in the rational design of inhibitors and the mechanistic differences between both enzymes.

Insights into substrate binding and catalysis in bacterial type I dehydroquinase.

Structural, biochemical and computational studies to study substrate binding and the role of the conserved residues of the DHQ1 (type I dehydroquinase) enzyme active site are reported in the present paper. The crystal structure of DHQ1 from Salmonella typhi in complex with (2R)-2-methyl-3-dehydroquinic acid, a substrate analogue, was solved at 1.5 Å. The present study reveals a previously unknown key role for conserved Glu46, Phe145 and Met205 and Gln236, Pro234 and Ala233 residues, with the latter three being located in the flexible substrate-covering loop. Gln236 was shown to be responsible for the folding of this loop and for the dramatic reduction of its flexibility, which triggers active site closure. Glu46 was found to be key in bringing the substrate close to the lysine/histidine catalytic pocket to initiate catalysis. The present study could be useful in the rational design of inhibitors of this challenging and recognized target for the development of novel herbicides and antimicrobial agents.

Synthesis of 3-alkyl enol mimics inhibitors of type II dehydroquinase: factors influencing their inhibition potency.

Several 3-alkylaryl mimics of the enol intermediate in the reaction catalyzed by type II dehydroquinase were synthesized to investigate the effect on the inhibition potency of replacing the oxygen atom in the side chain by a carbon atom. The length and the rigidity of the spacer was also studied. The inhibitory properties of the reported compounds against type II dehydroquinase from Mycobacterium tuberculosis and Helicobacter pylori are also reported. The binding modes of these analogs in the active site of both enzymes were studied by molecular docking using GOLD 5.0 and dynamic simulations studies.

Macromolecular assembly and membrane activity of antimicrobial D,L-α-Cyclic peptides.

Antimicrobial peptides are viewed as a promising alternative to conventional antibiotics, as their activity through membrane targeting makes them less prone to resistance development. Among them, antimicrobial D,L-α-cyclic peptides (CPs) have been proposed as an alternative, specially due to their cyclic nature and to the presence of D-α-amino acids that increases their resistance to proteases. In present work, second generation D,L-α-cyclic peptides with proven antimicrobial activity are shown to form complex macromolecular assemblies in the presence of membranes. We addressed the CPs:membrane interactions through a combination of experimental techniques (DSC and ATR-FTIR) with coarse-grained molecular dynamics (CG-MD) simulations, aiming at understanding their interactions, macromolecular assemblies and eventually unveil their mechanism of action. DSC shows that the interaction depends heavily on the negatively charge content of the membrane and on lipid/peptide ratio, suggesting different mechanisms for the different peptides and lipid systems. CG-MD proved that CPs can self-assemble at the lipid surface as nanotubes or micellar aggregates, depending on the peptide, in agreement with ATR-FTIR results. Finally, our results shed light into possible mechanisms of action of the peptides with pending hydrocarbon tail, namely membrane extensive segregation and/or membrane disintegration through the formation of disk-like lipid/peptide aggregates.

MolTarPred: A web tool for comprehensive target prediction with reliability estimation.

Molecular target prediction can provide a starting point to understand the efficacy and side effects of phenotypic screening hits. Unfortunately, the vast majority of in silico target prediction methods are not available as web tools. Furthermore, these are limited in the number of targets that can be predicted, do not estimate which target predictions are more reliable and/or lack comprehensive retrospective validations. We present MolTarPred ( http://moltarpred.marseille.inserm.fr/), a user-friendly web tool for predicting protein targets of small organic compounds. It is powered by a large knowledge base comprising 607,659 compounds and 4,553 macromolecular targets collected from the ChEMBL database. In about 1 min, the predicted targets for the supplied molecule will be listed in a table. The chemical structures of the query molecule and the most similar compounds annotated with the predicted target will also be shown to permit visual inspection and comparison. Practical examples of the use of MolTarPred are showcased. MolTarPred is a new resource for scientists that require a more complete knowledge of the polypharmacology of a molecule. The introduction of a reliability score constitutes an attractive functionality of MolTarPred, as it permits focusing experimental confirmatory tests on the most reliable predictions, which leads to higher prospective hit rates.

Unearthing new genomic markers of drug response by improved measurement of discriminative power.

BACKGROUND: Oncology drugs are only effective in a small proportion of cancer patients. Our current ability to identify these responsive patients before treatment is still poor in most cases. Thus, there is a pressing need to discover response markers for marketed and research oncology drugs. Screening these drugs against a large panel of cancer cell lines has led to the discovery of new genomic markers of in vitro drug response. However, while the identification of such markers among thousands of candidate drug-gene associations in the data is error-prone, an appraisal of the effectiveness of such detection task is currently lacking. METHODS: Here we present a new non-parametric method to measuring the discriminative power of a drug-gene association. Unlike parametric statistical tests, the adopted non-parametric test has the advantage of not making strong assumptions about the data distorting the identification of genomic markers. Furthermore, we introduce a new benchmark to further validate these markers in vitro using more recent data not used to identify the markers. RESULTS: The application of this new methodology has led to the identification of 128 new genomic markers distributed across 61% of the analysed drugs, including 5 drugs without previously known markers, which were missed by the MANOVA test initially applied to analyse data from the Genomics of Drug Sensitivity in Cancer consortium. CONCLUSIONS: Discovering markers using more than one statistical test and testing them on independent data is unusual. We found this helpful to discard statistically significant drug-gene associations that were actually spurious correlations. This approach also revealed new, independently validated, in vitro markers of drug response such as Temsirolimus-CDKN2A (resistance) and Gemcitabine-EWS_FLI1 (sensitivity).

Predicting the Reliability of Drug-target Interaction Predictions with Maximum Coverage of Target Space.

Many computational methods to predict the macromolecular targets of small organic molecules have been presented to date. Despite progress, target prediction methods still have important limitations. For example, the most accurate methods implicitly restrict their predictions to a relatively small number of targets, are not systematically validated on drugs (whose targets are harder to predict than those of non-drug molecules) and often lack a reliability score associated with each predicted target. Here we present a systematic validation of ligand-centric target prediction methods on a set of clinical drugs. These methods exploit a knowledge-base covering 887,435 known ligand-target associations between 504,755 molecules and 4,167 targets. Based on this dataset, we provide a new estimate of the polypharmacology of drugs, which on average have 11.5 targets below IC50 10 µM. The average performance achieved across clinical drugs is remarkable (0.348 precision and 0.423 recall, with large drug-dependent variability), especially given the unusually large coverage of the target space. Furthermore, we show how a sparse ligand-target bioactivity matrix to retrospectively validate target prediction methods could underestimate prospective performance. Lastly, we present and validate a first-in-kind score capable of accurately predicting the reliability of target predictions.

Reducing the Flexibility of Type†II Dehydroquinase for Inhibition: A Fragment-Based Approach and Molecular Dynamics Study.

A multidisciplinary approach was used to identify and optimize a quinazolinedione-based ligand that would decrease the flexibility of the substrate-covering loop (catalytic loop) of the type II dehydroquinase from Helicobacter pylori. This enzyme, which is essential for the survival of this bacterium, is involved in the biosynthesis of aromatic amino acids. A computer-aided fragment-based protocol (ALTA) was first used to identify the aromatic fragments able to block the interface pocket that separates two neighboring enzyme subunits and is located at the active site entrance. Chemical modification of its non-aromatic moiety through an olefin cross-metathesis and Seebach's self-reproduction of chirality synthetic principle allowed the development of a quinazolinedione derivative that disables the catalytic loop plasticity, which is essential for the enzyme's catalytic cycle. Molecular dynamics simulations revealed that the ligand would force the catalytic loop into an inappropriate arrangement for catalysis by strong interactions with the catalytic tyrosine and by expelling the essential arginine out of the active site.

How Reliable Are Ligand-Centric Methods for Target Fishing?

Computational methods for Target Fishing (TF), also known as Target Prediction or Polypharmacology Prediction, can be used to discover new targets for small-molecule drugs. This may result in repositioning the drug in a new indication or improving our current understanding of its efficacy and side effects. While there is a substantial body of research on TF methods, there is still a need to improve their validation, which is often limited to a small part of the available targets and not easily interpretable by the user. Here we discuss how target-centric TF methods are inherently limited by the number of targets that can possibly predict (this number is by construction much larger in ligand-centric techniques). We also propose a new benchmark to validate TF methods, which is particularly suited to analyse how predictive performance varies with the query molecule. On average over approved drugs, we estimate that only five predicted targets will have to be tested to find two true targets with submicromolar potency (a strong variability in performance is however observed). In addition, we find that an approved drug has currently an average of eight known targets, which reinforces the notion that polypharmacology is a common and strong event. Furthermore, with the assistance of a control group of randomly-selected molecules, we show that the targets of approved drugs are generally harder to predict. The benchmark and a simple target prediction method to use as a performance baseline are available at http://ballester.marseille.inserm.fr/TF-benchmark.tar.gz.

Exploring the water-binding pocket of the type II dehydroquinase enzyme in the structure-based design of inhibitors.

Structural and computational studies to explore the WAT1 binding pocket in the structure-based design of inhibitors against the type II dehydroquinase (DHQ2) enzyme are reported. The crystal structures of DHQ2 from M. tuberculosis in complex with four of the reported compounds are described. The electrostatic interaction observed between the guanidinium group of the essential arginine and the carboxylate group of one of the inhibitors in the reported crystal structures supports the recently suggested role of this arginine as the residue that triggers the release of the product from the active site. The results of the structural and molecular dynamics simulation studies revealed that the inhibitory potency is favored by promoting interactions with WAT1 and the residues located within this pocket and, more importantly, by avoiding situations where the ligands occupy the WAT1 binding pocket. The new insights can be used to advantage in the structure-based design of inhibitors.

Comparative binding energy COMBINE analysis for understanding the binding determinants of type†II dehydroquinase inhibitors.

Herein we report comparative binding energy (COMBINE) analyses to derive quantitative structure-activity relationship (QSAR) models that help rationalize the determinants of binding affinity for inhibitors of type II dehydroquinase (DHQ2), the third enzyme of the shikimic acid pathway. Independent COMBINE models were derived for Helicobacter pylori and Mycobacterium tuberculosis DHQ2, which is an essential enzyme in both these pathogenic bacteria that has no counterpart in human cells. These studies quantify the importance of the hydrogen bonding interactions between the ligands and the water molecule involved in the DHQ2 reaction mechanism. They also highlight important differences in the ligand interactions with the interface pocket close to the active site that could provide guides for future inhibitor design.

Mechanistic basis of the inhibition of type II dehydroquinase by (2S)- and (2R)-2-benzyl-3-dehydroquinic acids.

The structural changes caused by the substitution of the aromatic moiety in (2S)-2-benzyl-3-dehydroquinic acids and its epimers in C2 by electron-withdrawing or electron-donating groups in type II dehydroquinase enzyme from M. tuberculosis and H. pylori has been investigated by structural and computational studies. Both compounds are reversible competitive inhibitors of this enzyme, which is essential in these pathogenic bacteria. The crystal structures of M. tuberculosis and H. pylori in complex with (2S)-2-(4-methoxy)benzyl- and (2S)-2-perfluorobenzyl-3-dehydroquinic acids have been solved at 2.0, 2.3, 2.0, and 1.9 Å, respectively. The crystal structure of M. tuberculosis in complex with (2R)-2-(benzothiophen-5-yl)methyl-3-dehydroquinic acid is also reported at 1.55 Å. These crystal structures reveal key differences in the conformation of the flexible loop of the two enzymes, a difference that depends on the presence of electron-withdrawing or electron-donating groups in the aromatic moiety of the inhibitors. This loop closes over the active site after substrate binding, and its flexibility is essential for the function of the enzyme. These differences have also been investigated by molecular dynamics simulations in an effort to understand the significant inhibition potency differences observed between some of these compounds and also to obtain more information about the possible movements of the loop. These computational studies have also allowed us to identify key structural factors of the H. pylori loop that could explain its reduced flexibility in comparison to the M. tuberculosis loop, specifically by the formation of a key salt bridge between the side chains of residues Asp18 and Arg20.

Understanding the key factors that control the inhibition of type†II dehydroquinase by (2R)-2-benzyl-3-dehydroquinic acids.

The binding mode of several substrate analogues, (2R)-2-benzyl-3-dehydroquinic acids 4, which are potent reversible competitive inhibitors of type II dehydroquinase (DHQ2), the third enzyme of the shikimic acid pathway, has been investigated by structural and computational studies. The crystal structures of Mycobacterium tuberculosis and Helicobacter pylori DHQ2 in complex with one of the most potent inhibitor, p-methoxybenzyl derivative 4 a, have been solved at 2.40 Šand 2.75 Å, respectively. This has allowed the resolution of the M. tuberculosis DHQ2 loop containing residues 20-25 for the first time. These structures show the key interactions of the aromatic ring in the active site of both enzymes and additionally reveal an important change in the conformation and flexibility of the loop that closes over substrate binding. The loop conformation and the binding mode of compounds 4 b-d has been also studied by molecular dynamics simulations, which suggest that the benzyl group of inhibitors 4 prevent appropriate orientation of the catalytic tyrosine of the loop for proton abstraction and disrupts its basicity.