Daniel Moser

VAMMPIRE: A Matched Molecular Pairs Database for Structure-Based Drug Design and Optimization

Structure-based optimization to improve the affinity of a lead compound is an established approach in drug discovery. Knowledge-based databases holding molecular replacements can be supportive in the optimization process. We introduce a strategy to relate the substitution effect within matched molecular pairs (MMPs) to the atom environment within the cocrystallized protein-ligand complex. Virtually Aligned Matched Molecular Pairs Including Receptor Environment (VAMMPIRE) database and the supplementary web interface ( http://vammpire.pharmchem.uni-frankfurt.de ) provide valuable information for structure-based lead optimization.

Dual-target virtual screening by pharmacophore elucidation and molecular shape filtering.

Dual-target inhibitors gained increased attention in the past years. A novel in silico approach was employed for the discovery of dual 5-lipoxygenase/soluble epoxide hydrolase inhibitors. The ligand-based approach uses excessive pharmacophore elucidation and pharmacophore alignment in conjunction with shape-based scoring. The virtual screening results were verified in vitro, leading to nine novel inhibitors including a dual-target compound.

Exploring the Chemical Space of Multitarget Ligands Using Aligned Self-Organizing Maps

Design of multitarget drugs and polypharmacological compounds has become popular during the past decade. However, the main approach to design such compounds is to link two selective ligands via a flexible linker. Although such chimeric ligands often have reasonable potency in vitro, the in vivo efficacy is low due to high molecular weight, low ligand efficiency, and poor pharmacokinetic profile. We developed an unprecedented in silico approach for fragment-based design of multitarget ligands. It relies on superposition of the chemical spaces related to the affinity on single targets represented by self-organizing maps. We used this approach for screening of molecular fragments, which bind to the enzymes 5-lipoxygenase (5-LO) and soluble epoxide hydrolase (sEH). Using STD-NMR and activity-based assays, we were able to identify fragments binding to both targets. Furthermore, we were able to expand one of the fragments to a potent dual inhibitor bearing a reasonable molecular weight (MW = 446) and high affinity to both targets (IC50 of 0.03 μM toward 5-LO and 0.17 μM toward sEH).

Evaluation of structure-derived pharmacophore of soluble epoxide hydrolase inhibitors by virtual screening

The soluble epoxide hydrolase (sEH) is an enzyme located downstream of the CYP 450 branch of the arachidonic acid cascade and can be linked to a number of indications, including cardiovascular disorders, diabetes and inflammatory processes. Numerous inhibitors (sEHI) have been reported, mostly based on urea or amide scaffolds. The search for valid bioisosteric replacements is an ongoing challenge in the discovery of sEHI. We developed a receptor-based pharmacophore model on the basis of 13 crystal structures of the sEH and performed a virtual screening for novel compounds. The virtual screening hits were verified in vitro proving the basic applicability of the model and leading to novel non-urea sEHI.

Probing metallo-β-lactamases with molecular fragments identified by consensus docking

Bacterial resistance mediated by metallo-β-lactamases (MBLs) is a major problem for the treatment of infections. An MBL inhibitor could restore the potency of β-lactam antibiotics. Fragment-based design might deliver valuable starting points for the discovery of novel MBL inhibitors. In this study, we chose an in silico approach to search for fragments able to bind and inhibit NDM-1, VIM-1, and IMP-7. We used consensus docking to identify low molecular weight compounds from a commercially available library. Most promising compounds were evaluated in a sensitive fluorescence-based activity assay and by the orthogonal biophysical technique saturation transfer difference (STD)-NMR. (1)H-(15)N chemical shift perturbation NMR was used to confirm the reversible binding and measure the dissociation constant of the most promising compound qualifying it as a high-quality starting point for further optimization.

VAMMPIRE-LORD: A Web Server for Straightforward Lead Optimization Using Matched Molecular Pairs

VAMMPIRE-LORD (lead optimization by rational design) describes an innovative strategy to improve the binding affinity of a defined lead compound using 3D matched molecular pairs (3D-MMPs). 3D-MMPs are defined as pairs of molecules that differ in exactly one structural transformation and have a known bioactive conformation. We developed a novel atom-pair descriptor (LORD_FP) that represents the ligand-as well as the receptor environment-of a chemical transformation and built a predictive model based on 17602 3D-MMPs. We demonstrate that the created model is able to extrapolate the knowledge of a chemical transformation and the associated effect on ligand affinity to any similar system. VAMMPIRE-LORD was implemented as a web server that guides the user step-by-step through the optimization process of a defined lead compound.

PENG: A Neural Gas-Based Approach for Pharmacophore Elucidation. Method Design, Validation, and Virtual Screening for Novel Ligands of LTA4H

The pharmacophore concept is commonly employed in virtual screening for hit identification. A pharmacophore is generally defined as the three-dimensional arrangement of the structural and physicochemical features of a compound responsible for its affinity to a pharmacological target. Given a number of active ligands binding to a particular target in the same manner, it can reasonably be assumed that they have some shared features, a common pharmacophore. We present a growing neural gas (GNG)-based approach for the extraction of the relevant features which we called PENG (pharmacophore elucidation by neural gas). Results of retrospective validation indicate an acceptable quality of the generated models. Additionally a prospective virtual screening for leukotriene A4 hydrolase (LTA4H) inhibitors was performed. LTA4H is a bifunctional zinc metalloprotease which displays both epoxide hydrolase and aminopeptidase activity. We could show that the PENG approach is able to predict the binding mode of the ligand by X-ray crystallography. Furthermore, we identified a novel chemotype of LTA4H inhibitors.

DrugBank screening revealed alitretinoin and bexarotene as liver X receptor modulators

In silico screening of DrugBank database to detect liver X receptor (LXR) agonism of marketed drugs using a self-organizing map and successive LXR-Gal4 hybrid reporter gene assay evaluation in vitro discovered alitretinoin and bexarotene as partial liver X receptor agonists. Dose-response curves demonstrated that plasma concentrations observed in clinical trials are sufficient for LXR activation and thus could account for LXR-mediated side-effects such as hypercholesterolemia and hyperlipidemia. The discovered drugs are the first reported dual LXR/RXR agonists and can serve as lead structures for LXR and dual LXR/RXR modulator development.

Design of dual ligands using excessive pharmacophore query alignment

Dual- or multi-target ligands have gained increased attention in the past years due to several advantages, including more simple pharmacokinetic and phamarcodynamic properties compared to a combined application of several drugs. Furthermore multi-target ligands often possess improved efficacy [1]. We present a new approach for the discovery of dual-target ligands using aligned pharmacophore models combined with a shape-based scoring. Starting with two sets of known active compounds for each target, a number of different pharmacophore models is generated and subjected to pairwise graph-based alignment using the Kabsch-Algorithm [2,3]. Since a compound may be able to bind to different targets in different conformations, the algorithm aligns pairs of pharmacophore models sharing the same features which are not necessarily at the exactly same spatial distance. Using the aligned models, a pharmacophore search on a multi-conformation-database is performed to find compounds matching both models. The potentially “dual” ligands are scored by a shape-based comparison with the known active molecules using ShaEP [4]. Using this approach, we performed a prospective fragment-based virtual screening for dual 5-LO/sEH inhibitors. Both enzymes play an important role in the arachidonic acid cascade and are involved in inflammatory processes, pain, cardiovascular diseases and allergic reactions [5,6]. Beside several new selective inhibitors we were able to find a compound inhibiting both enzymes in low micromolar concentrations. The results indicate that the idea of aligned pharmacophore models can be successfully employed for the discovery of dual-target ligands.