Multitarget-Directed Ligands Combining Cholinesterase and Monoamine Oxidase Inhibition with Histamine H3 R Antagonism for Neurodegenerative Diseases.

The therapy of complex neurodegenerative diseases requires the development of multitarget-directed drugs (MTDs). Novel indole derivatives with inhibitory activity towards acetyl/butyrylcholinesterases and monoamine oxidases A/B as well as the histamine H3 receptor (H3R) were obtained by optimization of the neuroprotectant ASS234 by incorporating generally accepted H3R pharmacophore motifs. These small-molecule hits demonstrated balanced activities at the targets, mostly in the nanomolar concentration range. Additional in vitro studies showed antioxidative neuroprotective effects as well as the ability to penetrate the blood-brain barrier. With this promising in vitro profile, contilisant (at 1 mg kg-1 i.p.) also significantly improved lipopolysaccharide-induced cognitive deficits.

Thermodynamic properties of leukotriene A4 hydrolase inhibitors.

The leukotriene A4 hydrolase (LTA4H) is a bifunctional enzyme, containing a peptidase and a hydrolase activity both activities having opposing functions regulating inflammatory response. The hydrolase activity is responsible for the conversion of leukotriene A4 to pro-inflammatory leukotriene B4, and hence, selective inhibitors of the hydrolase activity are of high pharmacological interest. Here we present the thermodynamic characterization of structurally distinct inhibitors of the LTA4H that occupy different regions of the binding site using different biophysical methods. An in silico method for the determination of stabilized water molecules in the binding site of the apo structure of LTA4H is used to interpret the measured thermodynamic data and provided insights for design of novel LTA4H inhibitors.

Computer-Assisted Discovery and Structural Optimization of a Novel Retinoid X Receptor Agonist Chemotype.

As universal heterodimer partners of many nuclear receptors, the retinoid X receptors (RXRs) constitute key transcription factors. They regulate cell proliferation, differentiation, inflammation, and metabolic homeostasis and have recently been proposed as potential drug targets for neurodegenerative and inflammatory diseases. Owing to the hydrophobic nature of RXR ligand binding sites, available synthetic RXR ligands are lipophilic, and their structural diversity is limited. Here, we disclose the computer-assisted discovery of a novel RXR agonist chemotype and its systematic optimization toward potent RXR modulators. We have developed a nanomolar RXR agonist with high selectivity among nuclear receptors and superior physicochemical properties compared to classical rexinoids that appears suitable for in vivo applications and as lead for future RXR-targeting medicinal chemistry.

Tuning Nuclear Receptor Selectivity of Wy14,643 towards Selective Retinoid X Receptor Modulation.

The fatty acid sensing nuclear receptor families retinoid X receptors (RXRs) and peroxisome proliferator-activated receptors (PPARs) hold therapeutic potential in neurodegeneration. Valuable pleiotropic activities of Wy14,643 in models of such conditions exceed its known PPAR agonistic profile. Here, we characterize the compound as an RXR agonist explaining the pleiotropic effects and report its systematic structure-activity relationship analysis with the discovery of specific molecular determinants driving activity on PPARs and RXRs. We have designed close analogues of the drug comprising selective and dual agonism on RXRs and PPARs that may serve as superior pharmacological tools to study the role and interplay of the nuclear receptors in various pathologies. A systematically optimized high potency RXR agonist revealed activity in vivo and active concentrations in brain. With its lack of RXR/liver X receptor-mediated side effects and superior profile compared to classical rexinoids, it establishes a new class of innovative RXR modulators to overcome key challenges in RXR targeting drug discovery.

A Diverse Benchmark Based on 3D Matched Molecular Pairs for Validating Scoring Functions.

The prediction of protein-ligand interactions and their corresponding binding free energy is a challenging task in structure-based drug design and related applications. Docking and scoring is broadly used to propose the binding mode and underlying interactions as well as to provide a measure for ligand affinity or differentiate between active and inactive ligands. Various studies have revealed that most docking software packages reliably predict the binding mode, although scoring remains a challenge. Here, a diverse benchmark data set of 99 matched molecular pairs (3D-MMPs) with experimentally determined X-ray structures and corresponding binding affinities is introduced. This data set was used to study the predictive power of 13 commonly used scoring functions to demonstrate the applicability of the 3D-MMP data set as a valuable tool for benchmarking scoring functions.

Local structure and stacking disorder of chloro(phthalocyaninato)aluminium.

Chloro(phthalocyaninato)aluminium [(C32H16N8)AlCl, Pigment Blue 79] is a molecular compound which crystallizes in a layer structure with stacking disorder. Order-disorder theory was applied to analyse and explain the stacking disorder and to determine the symmetry operations, which generate subsequent layers from a given one. Corresponding ordered structural models were constructed and optimized by force field and dispersion-corrected density functional theory methods. The superposition of the four lowest-energy stackings lead to a structure in which every second double layer looks to be ordered; in the other double layers the molecules occupy one of two lateral positions. This calculated superposition structure agrees excellently with an (incomplete) experimental structure determined from single-crystal data. From the optimized ordered models, the stacking probabilities and the preferred local arrangements were derived. Packing effects such as the distortion of the molecules depending on the arrangement of neighbouring molecules could also be determined.

Opportunities and Challenges for Fatty Acid Mimetics in Drug Discovery.

Fatty acids beyond their role as an endogenous energy source and storage are increasingly considered as signaling molecules regulating various physiological effects in metabolism and inflammation. Accordingly, the molecular targets involved in formation and physiological activities of fatty acids hold significant therapeutic potential. A number of these fatty acid targets are addressed by some of the oldest and most widely used drugs such as cyclooxygenase inhibiting NSAIDs, whereas others remain unexploited. Compounds orthosterically binding to proteins that endogenously bind fatty acids are considered as fatty acid mimetics. On the basis of their structural resemblance, fatty acid mimetics constitute a family of bioactive compounds showing specific binding thermodynamics and following similar pharmacokinetic mechanisms. This perspective systematically evaluates targets for fatty acid mimetics, investigates their common structural characteristics, and highlights demands in their discovery and design. In summary, fatty acid mimetics share particularly favorable characteristics justifying the conclusion that their therapeutic potential vastly outweighs the challenges in their design.