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Addition of the in situ generated Schwartz reagent to widely available isocyanates constitutes a chemoselective, high-yielding, and versatile approach to the synthesis of variously functionalized formamides. Steric and electronic factors or the presence of sensitive functionalities (esters, nitro groups, nitriles, alkenes) do not compromise the potential of the method. Full preservation of the stereochemical information contained in the starting materials is observed. The use of formamides in the nucleophilic addition of organometallic reagents (Chida–Sato allylation, Charette–Huang addition to imidoyl triflate activated amides, Matteson homologation of boronic esters) is briefly investigated.

An efficient, chemoselective homologation of Weinreb amides to the corresponding variously substituted α-oxyketones has been developed via the addition of lithiated α-oxygenated species. This one-step, experimentally easy, high yielding protocol is amenable not only for accessing simple α-oxyketones but also for more complex substituted ones ranging from primary and secondary alkyl-type to aromatic ones. Full delivery of the stereochemical information contained in the starting materials is observed through both the employment of enantioenriched Weinreb amides and optically active organolithium species.

An efficient, chemoselective approach to spiro-epoxyoxindoles via the addition of chloromethyllithium followed by ring-closure of the intermediate alkoxide is reported. Chemoselectivity is fully preserved in the presence of different electrophilic sites. The synthetic potential of selected spiro-epoxyindoles has been exploited in the copper(I)-catalyzed intramolecular oxyarylation of an alkyne and in the formation of N,N-dimethylisoindigo via the addition of dihalocarbenoids.

The nucleophilic addition of widely available and variously functionalized organolithium reagents to isothiocyanates represents a straightforward, high-yielding, one-pot method to access secondary thioamides. The simple reaction conditions required and the broad scope (>50 cases examples) makes it a robust and reliable method to access both simple and complex thioamides, including enantiopure ones. Noxious and unpleasant-smelling sulfurating agents, usually employed in the literature established methods, are avoided during the whole synthetic procedure thus, rendering the protocol highly attractive, also for sustainability aspects.

Synthesis and pharmacological evaluation of a series of condensed quinoline derivatives bearing a basic nitrogen on piperazine or [(dimethylamino)ethyl]thio moieties attached at the 2-position of the quinoline nucleus are described. 5-HT receptor binding studies revealed, for most of the compounds studied, nanomolar affinity for the 5-HT3 receptor subtype. The most active compound, benzopyrano[3,4-c]quinoline derivative 5f, displayed a Ki value very similar to that reported for quipazine along with an improved selectivity. Functional and in vivo testing carried out on three selected compounds showed that 5f,j,n are potent 5-HT3 receptor antagonists with potencies in the same range as the best known 5-HT3 receptor antagonists ondansetron, tropisetron, and zacopride. The crystal and molecular structures of compounds 5f,j,n were determined by single-crystal X-ray diffraction and used as starting structures for molecular modeling studies. Comparative molecular field analysis (CoMFA) was applied to binding constants of compounds 5a-p and 6a-h. The cross-validated r2, derived from partial least-squares calculations, indicated a good predictive capacity for affinity values in the series of compounds investigated. Evidence for the prediction capacity is provided in the form of plots of actual vs predicted pKi values. The steric and electrostatic features of the CoMFA-derived model are presented as standard coefficient contour maps of steric and electrostatic fields.

The preparation of six diazinyl 3-pyridyl ketones 3–8 is described. Detailed 1H and 13C nmr data of these novel building blocks are given.

Summary The pyrazolopyrimidothiazole ring system (compound N, table II) has been previously reported by us as a new competitive antagonist (apparent pA 2 = 7.3 equiv to 55 nM) at NK2-receptors. As part of our investigation on polycondensed heterocycles containing the pyrimidine ring as antagonists of G-protein coupled receptors, pyrimidoindole derivatives were prepared and tested in order to probe the topography of the NK2-receptors and ascertain the pattern of frameworks that result in optimum affinity and specificity. The title indole derivatives 5, 11a-d, 12c, 13a,b and 14b were ‘de novo’ designed or selected from our chemical archives and prepared by up-to-date synthetic routes, thus exploring new synthetic methodologies. According to the established graphic computer model, none of the tested substances exhibited activity as a consequence of the violation of an excluded volume area due the unfavourable position of the aromatic substituents.

The preparation of N-acetylpyrazolyl-quinoxalines and results of semiempirical MO calculations are presented. The structure determination of the isomers 3a, b was achieved by X-ray analysis.

Parallel Screening has been introduced as an in silico method to predict the potential biological activities of compounds by screening them with a multitude of pharmacophore models. This study presents an early application example employing a Pipeline Pilot-based screening platform for automatic large-scale virtual activity profiling. An extensive set of HIV protease inhibitor pharmacophore models was used to screen a selection of active and inactive compounds. Furthermore, we aimed to address the usually critically eyed point, whether it is possible in a parallel screening system to differentiate between similar molecules/molecules acting on closely related proteins, and therefore we incorporated a collection of other protease inhibitors including aspartic protease inhibitors. The results of the screening experiments show a clear trend toward most extensive retrieval of known active ligands, followed by the general protease inhibitors and lowest recovery of inactive compounds.

Cytochrome P450 19 (P450 19, aromatase) constitutes a successful target for the treatment of breast cancer. This study analyzes chemical features common to P450 19 inhibitors to develop ligand-based, selective pharmacophore models for this enzyme. The HipHop and HypoRefine algorithms implemented in the Catalyst software package were employed to create both common feature and quantitative models. The common feature model for P450 19 includes two ring aromatic features in its core and two hydrogen bond acceptors at the ends. The models were used as database search queries to identify active compounds from the NCI database.

Three-dimensional pharmacophore models for peptidic and small organic nonpeptidic inhibitors of the human rhinovirus 3C protease were generated in a structure-based as well as in a ligand-based approach, using the software package Catalyst. The inhibitors possess an electrophilic moiety, often a Michael acceptor function, which covalently binds to a cysteine in the active site of the enzyme. Since this process presents the key step for virus inactivation, the creation of a new function in Catalyst was required in order to include this decisive functionality into the pharmacophore models. In the present study we focus on this feature definition process because it presents an innovative strategy to expand the pharmacophore description ability of the Catalyst software to also include covalent bonds between ligand and binding site. The resulting hypotheses were then used for virtual screening of 3D databases in order to verify their quality and to search for structurally diverse, possible new lead substances.

We examined the quality of Catalyst's conformational model generation algorithm via a large scale study based on the crystal structures of a sample of 510 pharmaceutically relevant protein-ligand complexes extracted from the Protein Data Bank (PDB). Our results show that the tested algorithms implemented within Catalyst are able to produce high quality conformers, which in most of the cases are well suited for in silico drug research. Catalyst-specific settings were analyzed, such as the method used for the conformational model generation (FAST vs BEST) and the maximum number of generated conformers. By setting these options for higher fitting quality, the average RMS values describing the similarity of experimental and simulated conformers were improved from an RMS of 1.06 with max. 50 FAST generated conformers to an RMS of 0.93 with max. 255 BEST generated conformers, which represents an improvement by 12%. Each method provides best fitting conformers with an RMS value1.50 in more than 80% of all cases. We analyzed the computing time/quality ratio of various conformational model generation settings and examined ligands in high energy conformations. Furthermore, properties of the same ligands in various proteins were investigated, and the fitting qualities of experimental conformations from the PDB and the Cambridge Structural Database (CSD) were compared. One of the most important conclusions of former studies, the fact that bioactive conformers often have energy high above that of global minima, was confirmed.

Drug metabolizing enzymes and transporters are often involved in clinically relevant drug-drug interactions. These functional proteins can be induced by a wide range of xenobiotics. The induction is mediated by a group of receptors known as orphan nuclear receptors. The pregnane X receptor (PXR) is a member of this receptor family and regulates the expression of multiple Cytochrome P450 enzyme families (e.g. CYP 3A and 2B), phase II enzymes (e.g. UDP glucuronosyl transferases), and transporters (e.g. multidrug resistance protein 1). The software package Catalyst was employed to derive pharmacophore models for PXR activation. A structure based pharmacophore hypothesis and several ligand based ones were compared in order to identify ligand receptor interactions essential for receptor activation. The results suggest that hydrogen bonding to Gln285 is indispensable for PXR activation. Most ligands were found to form a second hydrogen bond to His407. Hydrophobic interactions are not essential for receptor activation but contribute to ligand affinity. Highly active compounds share up to five hydrophobic features that allow the ligand to occupy large areas of the predominantly hydrophobic binding pocket.

From the historically grown archive of protein-ligand complexes in the Protein Data Bank small organic ligands are extracted and interpreted in terms of their chemical characteristics and features. Subsequently, pharmacophores representing ligand-receptor interaction are derived from each of these small molecules and its surrounding amino acids. Based on a defined set of only six types of chemical features and volume constraints, three-dimensional pharmacophore models are constructed, which are sufficiently selective to identify the described binding mode and are thus a useful tool for in-silico screening of large compound databases. The algorithms for ligand extraction and interpretation as well as the pharmacophore creation technique from the automatically interpreted data are presented and applied to a rhinovirus capsid complex as application example.

Factor Xa inhibitors are innovative anticoagulant agents that provide a better safety/efficacy profile compared to other anticoagulative drugs. A chemical feature-based modeling approach was applied to identify crucial pharmacophore patterns from 3D crystal structures of inhibitors bound to human factor Xa (Pdb entries 1fjs, 1kns, 1eqz) using the software LIGANDSCOUT and CATALYST. The complex structures were selected regarding the criteria of high inhibitory potency (i.e. all ligands show K(i) values against factor Xa in the subnanomolar range) and good resolution (i.e. at least 2.2 A) in order to generate selective and high quality pharmacophore models. The resulting chemical-feature based hypotheses were used for virtual screening of commercial molecular databases such as the WDI database. Furthermore, a ligand-based molecular modeling approach was performed to obtain common-feature hypotheses that represent the relevant chemical interactions between 10 bioactive factor Xa inhibitors and the protein, respectively. In a next step a virtual combinatorial library was designed in order to generate new compounds with similar chemical and spatial properties as known inhibitors. The software tool ILIB DIVERSE was used for this procedure in order to provide new scaffolds of this group of anticoagulants. Finally we present the combination of these two techniques, hence virtual screening was performed with selective pharmacophore models in a focused virtual combinatorial database. De novo derived molecular scaffolds that were able to adequately satisfy the pharmacophore criteria are revealed and are promising templates for candidates for further development.

Virtual screening of large libraries of organic compounds combined with pharmacological high throughput screening is widely used for drug discovery in the pharmaceutical industry. Our aim was to explore the efficiency of using a biased 3D database comprising secondary metabolites from antiinflammatory medicinal plants as a source for the virtual screening. For this study pharmacophore models of cyclooxygenase I and II (COX-1, COX-2), key enzymes in the inflammation process, were generated with structure-based as well as common feature based modeling, resulting in three COX hypotheses. Four different multiconfomational 3D databases limited in molecular weight between 300 and 700 Da were applied to the screening in order to compare and analyze the obtained hit rates. Two of them were created in-house (DIOS, NPD). The database DIOS consists of 2752 compounds from phytochemical reports of antiinflammatory medicinal plants described by the ethnopharmacological source 'De material medica' of Pedanius Dioscorides, whereas NPD contains almost 80,000 compounds gathered arbitrarily from natural sources. In addition, two available multiconformational 3D libraries comprising marketed and development drug substances (DWI and NCI), mainly originating from synthesis, were used for comparison. As a test of the pharmacophore models' capability in natural sources, the models were used to search for known COX inhibitory natural products. This was achieved with some exceptions, which are discussed in the paper. Depending on the hypothesis used, DWI and NCI library searches produced hit rates in the range of 6.6% to 13.7%. A slight increase of the number of molecules assessed for binding was achieved with the database of natural products (NPD). Using the biased 3D database DIOS, however, the average increase of efficiency reached 77% to 133% compared to the hit rates resulting from WDI and NCI. The statistical benefit of a combination of an ethnopharmacological approach with the potential of computer aided drug discovery by in silico screening was demonstrated exemplified on the applied targets COX-1 and COX-2.