Marcus Wieder

Evaluating the stability of pharmacophore features using molecular dynamics simulations

Molecular dynamics simulations of twelve protein-ligand systems were used to derive a single, structure based pharmacophore model for each system. These merged models combine the information from the initial experimental structure and from all snapshots saved during the simulation. We compared the merged pharmacophore models with the corresponding PDB pharmacophore models, i.e., the static models generated from an experimental structure in the usual manner. The frequency of individual features, of feature types and the occurrence of features not present in the static model derived from the experimental structure were analyzed. We observed both pharmacophore features not visible in the traditional approach, as well as features which disappeared rapidly during the molecular dynamics simulations and which may well be artifacts of the initial PDB structure-derived pharmacophore model. Our approach helps mitigate the sensitivity of structure based pharmacophore models to the single set of coordinates present in the experimental structure. Further, the frequency with which specific features occur during the MD simulation may aid in ranking the importance of individual features.

Identification of the putative binding pocket of valerenic acid on GABAA receptors using docking studies and site-directed mutagenesis

β2/3‐subunit‐selective modulation of GABAA receptors by valerenic acid (VA) is determined by the presence of transmembrane residue β2/3N265. Currently, it is not known whether β2/3N265 is part of VAs binding pocket or is involved in the transduction pathway of VAs action. The aim of this study was to clarify the localization of VAs binding pocket on GABAA receptors.

Common Hits Approach: Combining Pharmacophore Modeling and Molecular Dynamics Simulations

We present a new approach that incorporates flexibility based on extensive MD simulations of protein-ligand complexes into structure-based pharmacophore modeling and virtual screening. The approach uses the multiple coordinate sets saved during the MD simulations and generates for each frame a pharmacophore model. Pharmacophore models with the same pharmacophore features are pooled. In this way the high number of pharmacophore models that results from the MD simulation is reduced to only a few hundred representative pharmacophore models. Virtual screening runs are performed with every representative pharmacophore model; the screening results are combined and rescored to generate a single hit-list. The score for a particular molecule is calculated based on the number of representative pharmacophore models which classified it as active. Hence, the method is called common hits approach (CHA). The steps between the MD simulation and the final hit-list are performed automatically and without user interaction. We test the performance of CHA for virtual screening using screening databases with active and inactive compounds for 40 protein-ligand systems. The results of the CHA are compared to the (i) median screening performance of all representative pharmacophore models of protein-ligand systems, as well as to the virtual screening performance of (ii) a random classifier, (iii) the pharmacophore model derived from the experimental structure in the PDB, and (iv) the representative pharmacophore model appearing most frequently during the MD simulation. For the 34 (out of 40) protein-ligand complexes, for which at least one of the approaches was able to perform better than a random classifier, the highest enrichment was achieved using CHA in 68% of the cases, compared to 12% for the PDB pharmacophore model and 20% for the representative pharmacophore model appearing most frequently. The availabilithy of diverse sets of different pharmacophore models is utilized to analyze some additional questions of interest in 3D pharmacophore-based virtual screening.

Comparing pharmacophore models derived from crystal structures and from molecular dynamics simulations

Pharmacophore modeling is a widely used technique in computer-aided drug discovery. Structure-based pharmacophore models of a ligand in complex with a protein have proven to be useful for supporting in silico hit discovery, hit to lead expansion, and lead optimization. As a structure-based approach it depends on the correct interpretation of ligand–protein interactions. There are legitimate concerns about the fidelity of the bound ligand and about non-physiological contacts with parts of the crystal and the solvent effects that influence the protein structure. A possible way to refine the structure of a protein–ligand system is to use the final structure of a given MD simulation. In this study we compare pharmacophore models built using the initial protein–ligand structure obtained from the protein data bank (PDB) with pharmacophore models built with the final structure of a molecular dynamics simulation. We show that the pharmacophore models differ in feature number and feature type and that the pharmacophore models built from the last structure of a MD simulation shows in some cases better ability to distinguish between active and decoy ligand structures.Graphical abstract

A Molecular Dynamics-Shared Pharmacophore Approach to Boost Early-Enrichment Virtual Screening: A Case Study on Peroxisome Proliferator-Activated Receptorα

Molecular dynamics (MD) simulations can be used, prior to virtual screening, to add flexibility to proteins and study them in a dynamic way. Furthermore, the use of multiple crystal structures of the same protein containing different co‐crystallized ligands can help elucidate the role of the ligand on a protein′s active conformation, and then explore the most common interactions between small molecules and the receptor. In this work, we evaluated the contribution of the combined use of MD on crystal structures containing the same protein but different ligands to examine the crucial ligand–protein interactions within the complexes. The study was carried out on peroxisome proliferator‐activated receptor α (PPARα). Findings derived from the dynamic analysis of interactions were then used as features for pharmacophore generation and constraints for generating the docking grid for use in virtual screening. We found that information derived from short multiple MD simulations using different molecules within the binding pocket of the target can improve the early enrichment of active ligands in the virtual screening process for this receptor. In the end we adopted a consensus scoring based on docking score and pharmacophore alignment to rank our dataset. Our results showed an improvement in virtual screening performance in early recognition when screening was performed with the Molecular dYnamics SHAred PharmacophorE (MYSHAPE) approach.

A daily single dose of a novel modafinil analogue CE-123 improves memory acquisition and memory retrieval

HIGHLIGHTS5‐((Benzhydrylsulfinyl)methyl) thiazole (CE‐123) was synthetized as a novel dopamine reuptake inhibitor.CE‐123 with respect to NET, DAT and SERT is a highly selective DAT inhibitor with no basic neurotoxicity.CE‐123 enters the brain and shows lower elimination than R‐modafinil.CE‐123 improves spatial memory performance in the rat. ABSTRACT Dopamine reuptake inhibitors have been shown to improve cognitive parameters in various tasks and animal models. We recently reported a series of modafinil analogues, of which the most promising, 5‐((benzhydrylsulfinyl)methyl) thiazole (CE‐123), was selected for further development. The present study aims to characterize pharmacological properties of CE‐123 and to investigate the potential to enhance memory performance in a rat model. In vitro transporter assays were performed in cells expressing human transporters. CE‐123 blocked uptake of [3H] dopamine (IC50=4.606&mgr;M) while effects on serotonin (SERT) and the norepinephrine transporter (NET) were negligible. Blood‐brain barrier and pharmacokinetic studies showed that the compound reached the brain and lower elimination than R‐modafinil. The Pro‐cognitive effect was evaluated in a spatial hole‐board task in male Sprague‐Dawley rats and CE‐123 enhances memory acquisition and memory retrieval, represented by significantly increased reference memory indices and shortened latency. Since DAT blockers can be considered as indirect dopamine receptor agonists, western blotting was used to quantify protein levels of dopamine receptors D1R, D2R and D5R and DAT in the synaptosomal fraction of hippocampal subregions CA1, CA3 and dentate gyrus (DG). CE‐123 administration in rats increased total DAT levels and D1R protein levels were significantly increased in CA1 and CA3 in treated/trained groups. The increase of D5R was observed in DG only. Dopamine receptors, particularly D1R, seem to play a role in mediating CE‐123‐induced memory enhancement. Dopamine reuptake inhibition by CE‐123 may represent a novel and improved stimulant therapeutic for impairments of cognitive functions.

SAR-Guided Scoring Function and Mutational Validation Reveal the Binding Mode of CGS-8216 at the α1+/γ2– Benzodiazepine Site

The structural resolution of a bound ligand-receptor complex is a key asset to efficiently drive lead optimization in drug design. However, structural resolution of many drug targets still remains a challenging endeavor. In the absence of structural knowledge, scientists resort to structure-activity relationships (SARs) to promote compound development. In this study, we incorporated ligand-based knowledge to formulate a docking scoring function that evaluates binding poses for their agreement with a known SAR. We showcased this protocol by identifying the binding mode of the pyrazoloquinolinone (PQ) CGS-8216 at the benzodiazepine binding site of the GABAA receptor. Further evaluation of the final pose by molecular dynamics and free energy simulations revealed a close proximity between the pendent phenyl ring of the PQ and γ2D56, congruent with the low potency of carboxyphenyl analogues. Ultimately, we introduced the γ2D56A mutation and in fact observed a 10-fold potency increase in the carboxyphenyl analogue, providing experimental evidence in favor of our binding hypothesis.

Heterocyclic Analogues of Modafinil as Novel, Atypical Dopamine Transporter Inhibitors

Modafinil is a wake promoting compound with high potential for cognitive enhancement. It is targeting the dopamine transporter (DAT) with moderate selectivity, thereby leading to reuptake inhibition and increased dopamine levels in the synaptic cleft. A series of modafinil analogues have been reported so far, but more target-specific analogues remain to be discovered. It was the aim of this study to synthesize and characterize such analogues and, indeed, a series of compounds were showing higher activities on the DAT and a higher selectivity toward DAT versus serotonin and norepinephrine transporters than modafinil. This was achieved by substituting the amide moiety by five- and six-membered aromatic heterocycles. In vitro studies indicated binding to the cocaine pocket on DAT, although molecular dynamics revealed binding different from that of cocaine. Moreover, no release of dopamine was observed, ruling out amphetamine-like effects. The absence of neurotoxicity of a representative analogue may encourage further preclinical studies of the above-mentioned compounds.