Ilenia Giangreco

Design, Synthesis, and Biological Evaluation of Coumarin Derivatives Tethered to an Edrophonium‐like Fragment as Highly Potent and Selective Dual Binding Site Acetylcholinesterase Inhibitors

A large series of substituted coumarins linked through an appropriate spacer to 3‐hydroxy‐N,N‐dimethylanilino or 3‐hydroxy‐N,N,N‐trialkylbenzaminium moieties were synthesized and evaluated as acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitors. The highest AChE inhibitory potency in the 3‐hydroxy‐N,N‐dimethylanilino series was observed with a 6,7‐dimethoxy‐3‐substituted coumarin derivative, which, along with an outstanding affinity (IC50=0.236 nM) exhibits excellent AChE/BChE selectivity (SI>300 000). Most of the synthesized 3‐hydroxy‐N,N,N‐trialkylbenzaminium salts display an AChE affinity in the sub‐nanomolar to picomolar range along with excellent AChE/BChE selectivities (SI values up to 138 333). The combined use of docking and molecular dynamics simulations permitted us to shed light on the observed structure–affinity and structure–selectivity relationships, to detect two possible alternative binding modes, and to assess the critical role of π–π stacking interactions in the AChE peripheral binding site.

Improving quantitative structure-activity relationships through multiobjective optimization.

A multiobjective optimization algorithm was proposed for the automated integration of structure- and ligand-based molecular design. Driven by a genetic algorithm, the herein proposed approach enabled the detection of a number of trade-off QSAR models accounting simultaneously for two independent objectives. The first was biased toward best regressions among docking scores and biological affinities; the second minimized the atom displacements from a properly established crystal-based binding topology. Based on the concept of dominance, 3D QSAR equivalent models profiled the Pareto frontier and were, thus, designated as nondominated solutions of the search space. K-means clustering was, then, operated to select a representative subset of the available trade-off models. These were effectively subjected to GRID/GOLPE analyses for quantitatively featuring molecular determinants of ligand binding affinity. More specifically, it was demonstrated that a) diverse binding conformations occurred on the basis of the ligand ability to profitably contact different part of protein binding site; b) enzyme selectivity was better approached and interpreted by combining diverse equivalent models; and c) trade-off models were successful and even better than docking virtual screening, in retrieving at high sensitivity active hits from a large pool of chemically similar decoys. The approach was tested on a large series, very well-known to QSAR practitioners, of 3-amidinophenylalanine inhibitors of thrombin and trypsin, two serine proteases having rather different biological actions despite a high sequence similarity.

Strategies of multi-objective optimization in drug discovery and development.

Introduction: Drug discovery and development is a typical multi-objective problem and its successes or failures depend on the simultaneous control of numerous, often conflicting, molecular and pharmacological properties. Multi-objective optimization strategies represent a new approach to capture the occurrence of varying optimal solutions based on trade-offs among the objectives taken into account. In view of this, multi-objective optimization aims to discover a set of satisfactory compromises that may in turn be used to find the global optimal solution by optimizing numerous dependent properties simultaneously. Areas covered: The authors review the potential of multi-objective strategies in a number of fields including: drug library design; substructure mining; the derivation of quantitative structure–activity relationship models; ranking of docking poses. The authors also discuss the potential of multi-objective strategies in controlling competing properties for absorption, distribution, metabolism and elimination/toxicity optimization. Expert opinion: It is very clear to those who work in drug discovery and development that the success of rational drug design is largely dependent on the control of a number of, often conflicting, objectives. Therefore, multi-objective optimization methods, which have recently been introduced to the field of molecular discovery, represent the ultimate frontier in chemoinformatics. The widespread use of these multi-objective techniques has provided new opportunities in medicinal chemistry as seen through its use in a number of applications for chemoinformatics both within academia and the pharmaceutical industry.

Insights into the Complex Formed by Matrix Metalloproteinase-2 and Alloxan Inhibitors: Molecular Dynamics Simulations and Free Energy Calculations

Matrix metalloproteinases (MMP) are well-known biological targets implicated in tumour progression, homeostatic regulation, innate immunity, impaired delivery of pro-apoptotic ligands, and the release and cleavage of cell-surface receptors. Hence, the development of potent and selective inhibitors targeting these enzymes continues to be eagerly sought. In this paper, a number of alloxan-based compounds, initially conceived to bias other therapeutically relevant enzymes, were rationally modified and successfully repurposed to inhibit MMP-2 (also named gelatinase A) in the nanomolar range. Importantly, the alloxan core makes its debut as zinc binding group since it ensures a stable tetrahedral coordination of the catalytic zinc ion in concert with the three histidines of the HExxHxxGxxH metzincin signature motif, further stabilized by a hydrogen bond with the glutamate residue belonging to the same motif. The molecular decoration of the alloxan core with a biphenyl privileged structure allowed to sample the deep S1′ specificity pocket of MMP-2 and to relate the high affinity towards this enzyme with the chance of forming a hydrogen bond network with the backbone of Leu116 and Asn147 and the side chains of Tyr144, Thr145 and Arg149 at the bottom of the pocket. The effect of even slight structural changes in determining the interaction at the S1′ subsite of MMP-2 as well as the nature and strength of the binding is elucidated via molecular dynamics simulations and free energy calculations. Among the herein presented compounds, the highest affinity (pIC50 = 7.06) is found for BAM, a compound exhibiting also selectivity (>20) towards MMP-2, as compared to MMP-9, the other member of the gelatinases.

Pharmacophore binding motifs for nicotinamide adenine dinucleotide analogues across multiple protein families: a detailed contact-based analysis of the interaction between proteins and NAD(P) cofactors.

We have analyzed the protein-binding pharmacophore of NAD and its close analogues in all protein-ligand structures available in the RCSB database as of February 2012; this analysis has then been used to assess the novelty of structures emerging after that date. We show that proteins have evolved diverse pharmacophore motifs for binding the adenine moiety, fewer, but still diverse, motifs for nicotinamide, and a very limited set of motifs for binding the pyrophosphate linker. Our exhaustive analysis includes a pharmacophore contact analysis for over 1900 protein-ligand structures containing NAD analogues; we have benchmarked this set of contacts against nearly 27 000 protein-ligand structures to demonstrate that the diversity of interactions seen with NAD is very similar to that seen for all other ligands. Hence, variation in binding motifs for NAD is not distinct from that observed for other ligands and they show significant variation across protein families.

An extensive and diverse set of molecular overlays for the validation of pharmacophore programs.

The pharmacophore hypothesis plays a central role in both the design and optimization of drug-like ligands. Pharmacophore patterns are invoked to explain the binding affinity of ligands and to enable the design of chemically distinct scaffolds that show affinity for a protein target of interest. The importance of pharmacophores in rationalizing ligand affinity has led to numerous algorithms that seek to overlay ligands based on their pharmacophoric features. All such algorithms must be validated with respect to known ligand overlays, usually by extracting ligand overlay sets from the Protein Data Bank (PDB). This validation step creates the problem of which of the known overlays to select and from which proteins. The large number of structures and protein families in the PDB makes it difficult to establish a definitive overlay set; as a result, validation studies have rarely employed the same data sets. We have therefore undertaken an exhaustive analysis of the RCSB PDB to identify 121 distinct ligand overlay sets. We have defined a robust protein overlay protocol, which is free from subjective interpretation over which residues to include, and we have analyzed each overlay set on the basis of whether they provide evidence for the pharmacophore hypothesis. Our final data set spans a broad range of structural types and degrees of difficulty and includes overlays that any algorithm should be able to reproduce, as well as some for which there is very weak evidence for a conserved pharmacophore at all. We provide this set in the hope that it will prove definitive, at least until the PDB is greatly enriched with further structures or with radically different protein folds and families. Upon publication, the data set will be available for free download from the Web site of the Cambridge Crystallographic Data Centre.

Discovery of a Potent and Selective Hetero-Bivalent AChE Inhibitor via Bioisosteric Replacement

Scaffold hopping of known active compounds is becoming a successful strategy for the development of new molecular series. [1, 2] This strategy is based on the assumption that the same biological activity can be exerted by newly designed compounds that maintain some essential features of the template but are structurally different otherwise. [3] Playing a central role in modern medicinal chemistry, scaffold hopping is based on the concept of molecular similarity and thus involves the use of techniques such as shape matching, pharmacophore and similarity searching, fragment and bioisosteric replacement. [4] At present, many examples of successful scaffold hopping are known. A milestone in this field has been the identification of GABA-receptor antagonists based on the 1,4-benzodiazepine molecular scaffold. After its discovery in the Fifties, many attempts were undertaken to improve both pharmacokinetic and pharmacodynamic profiles of benzodiazepines initially by exploring various substituents and later by scaffold hopping to identify completely new core structures. Compounds with a novel scaffold different from that of benzodiazepines are Zopiclone, Zolpidem and Zaleplon. [5] Among other drugs dis

Assessment of a Cambridge Structural Database-driven overlay program.

We recently published an improved methodology for overlaying multiple flexible ligands and an extensive data set for validating pharmacophore programs. Here, we combine these two developments and present evidence of the effectiveness of the new overlay methodology at predicting correct superimpositions for systems with varying levels of complexity. The overlay program was able to generate correct predictions for 95%, 73%, and 39% of systems classified as easy, moderate, and hard, respectively.