Steffen Renner

Small-molecule inhibition of APT1 affects Ras localization and signaling

Cycles of depalmitoylation and repalmitoylation critically control the steady-state localization and function of various peripheral membrane proteins, such as Ras proto-oncogene products. Interference with acylation using small molecules is a strategy to modulate cellular localization--and thereby unregulated signaling--caused by palmitoylated Ras proteins. We present the knowledge-based development and characterization of a potent inhibitor of acyl protein thioesterase 1 (APT1), a bona fide depalmitoylating enzyme that is, so far, poorly characterized in cells. The inhibitor, palmostatin B, perturbs the cellular acylation cycle at the level of depalmitoylation and thereby causes a loss of the precise steady-state localization of palmitoylated Ras. As a consequence, palmostatin B induces partial phenotypic reversion in oncogenic HRasG12V-transformed fibroblasts. We identify APT1 as one of the thioesterases in the acylation cycle and show that this protein is a cellular target of the inhibitor.

Interactive exploration of chemical space with Scaffold Hunter.

We describe Scaffold Hunter, a highly interactive computer-based tool for navigation in chemical space that fosters intuitive recognition of complex structural relationships associated with bioactivity. The program reads compound structures and bioactivity data, generates compound scaffolds, correlates them in a hierarchical tree-like arrangement, and annotates them with bioactivity. Brachiation along tree branches from structurally complex to simple scaffolds allows identification of new ligand types. We provide proof of concept for pyruvate kinase.

Natural-product-derived fragments for fragment-based ligand discovery.

Fragment-based ligand and drug discovery predominantly employs sp2-rich compounds covering well-explored regions of chemical space. Despite the ease with which such fragments can be coupled, this focus on flat compounds is widely cited as contributing to the attrition rate of the drug discovery process. In contrast, biologically validated natural products are rich in stereogenic centres and populate areas of chemical space not occupied by average synthetic molecules. Here, we have analysed more than 180,000 natural product structures to arrive at 2,000 clusters of natural-product-derived fragments with high structural diversity, which resemble natural scaffolds and are rich in sp3-configured centres. The structures of the cluster centres differ from previously explored fragment libraries, but for nearly half of the clusters representative members are commercially available. We validate their usefulness for the discovery of novel ligand and inhibitor types by means of protein X-ray crystallography and the identification of novel stabilizers of inactive conformations of p38α MAP kinase and of inhibitors of several phosphatases. Natural products populate areas of chemical space not occupied by average synthetic molecules. Here, an analysis of more than 180,000 natural product structures results in a library of 2,000 natural-product-derived fragments, which resemble the properties of the natural products themselves and give access to novel inhibitor chemotypes.

Bioactivity-guided mapping and navigation of chemical space

The structure- and chemistry-based hierarchical organization of library scaffolds in tree-like arrangements provides a valid, intuitive means to map and navigate chemical space. We demonstrate that scaffold trees built using bioactivity as the key selection criterion for structural simplification during tree construction allow efficient and intuitive mapping, visualization and navigation of the chemical space defined by a given library, which in turn allows correlation of this chemical space with the investigated bioactivity and further compound design. Brachiation along the branches of such trees from structurally complex to simple scaffolds with retained yet varying bioactivity is feasible at high frequency for the five major pharmaceutically relevant target classes and allows for the identification of new inhibitor types for a given target. We provide proof of principle by identifying new active scaffolds for 5-lipoxygenase and the estrogen receptor ERalpha.

Comparison of correlation vector methods for ligand-based similarity searching

Correlation vector methods were tested for their usefulness in ligand-based virtual screening. Three molecular descriptors – two based on potential pharmacophore points and one on partial atom charges – and three similarity measures – the Manhattan distance, the Euclidian distance and the Tanimoto coefficient – were compared. The alignment-free descriptors seem to be particularly applicable when a course-grain filtering of data sets is required in combination with a high execution speed. Significant enrichment of actives was obtained by retrospective analysis. The cumulative percentages for all three descriptors allow for the retrieval of up to 78% of the active molecules in the first five percent of the reference database. Different descriptors retrieved only weakly overlapping sets of active molecules among the top-ranking compounds. If a single similarity index is to be used, the Manhattan distance seems to be particularly applicable. Generally, none of the three different descriptors tested in this study clearly outperformed the others. The suitability of a descriptor critically depends on the ligand-receptor interaction under investigation. For ligand-based similarity searching it is recommended to exploit several descriptors in parallel.

Scaffold-hopping potential of ligand-based similarity concepts.

ion from chemical structure. Consequently, such methods have been employed for the design of screening libraries, relying on their scaffold-hopping potential. 3, 8–12] In this study we compared the scaffold-hopping efficiency of topological, three-dimensional and molecular-surface-based pharmacophore pair descriptors with a popular substructure fingerprint method. Two molecules are considered to have different scaffolds if they have different topologies. This idea is based on the concept that druglike molecules are built up from a scaffold and side chains. There are several reasons for seeking a set of diverse scaffolds. Different chemotypes offer a choice in terms of chemical accessibility and prospects for lead optimization. Multiple lead structures (“backup” compounds) lower the chance of attrition in drug development through undesirable ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties. Scaffold hopping can also be applied to move from natural substrates to more druglike chemotypes. 5, 14] Furthermore, the creation of intellectual property is facilitated when multiple novel bioactive agents are available. Different virtual-screening concepts have been proposed for scaffold hopping. These include three-dimensional pharmacophore models, 15] pseudoreceptors, protein-structure-based de novo design, 17] and ligand-based similarity searching. Typically, rapid similarity searching is based on the comparison of descriptor vectors rather than on the explicit alignment of molecules to a reference and can thus be efficiently applied to screening large datasets. Herein, we concentrated on such methods. Similarity searching is founded on the similarity principle, which states that similar molecules exhibit similar biological effects. A straightforward similarity-searching approach is to compare the connection tables to assess the similarity between two molecules. Such methods include substructure fingerprints like the MACCS keys, which are based on exact chemical substructures. Substructure matching approaches were reported to be among the most successful for virtual screening. 7] The classification of intermolecular interactions into general pharmacophore types provides a way to obtain a more general description of the underlying chemotypes of molecules. 9] Three such descriptors were employed in the work reported herein: the topological CATS descriptor, 21] the three-dimensional CATS3D descriptor, and the molecular-surface-based SURFCATS descriptor (Figure 1). Molecular representations that are based on three-dimensional conformations like molecular surface-based descriptors are independent from the molecular connectivity and should have a favorable scaffold-hopping potential. 23] The three CATS descriptors describe a molecule in the form of a histogram that contains the normalized frequencies of all pairs of potential pharmacophore points (PPP) in a molecule. In our study, PPP pairs were further subdivided into PPP–PPP distan[a] S. Renner, Prof. Dr. G. Schneider Beilstein Endowed Chair for Cheminformatics Institute of Organic Chemistry & Chemical Biology Johann Wolfgang Goethe University Siesmayerstraße 70, 60323 Frankfurt (Germany) URL: www.modlab.de Fax: (+49)69-798-29826 E-mail : g.schneider@chemie.uni-frankfurt.de Supporting information for this article is available on the WWW under http://www.chemmedchem.org or from the author. Figure 1. The CATS family of descriptors: CATS, CATS3D, and SURFCATS. All descriptors are based on a PPP (potential pharmacophore point)-type description of the underlying molecule. For each descriptor, pairs of PPPs are transformed into a correlation vector. CATS is calculated from the topological distances of atom-based PPP pairs. For CATS3D the spatial distances between atom-based PPPs are used instead. SURFACTS uses the spatial distances between PPPs on the contact surface of a molecule. Here the PPPs represent the atom types of the nearest atom to each surface point. ChemMedChem 2006, 1, 181 – 185 A 2006 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim 181 ces and different pharmacophore types. For CATS, pairs of PPPs with shortest topological distances of up to ten bonds were counted, matching at least one of the pharmacophore types: anion, cation, hydrogen-bond donor, hydrogen-bond acceptor, or hydrophobic. For CATS3D and SURFCATS, pairs of PPPs were considered to fall into one of 20 equal-distance bins from 0–20 E. For the latter two methods, one of the pharmacophore types anion, cation, hydrogen-bond donor, hydrogenbond acceptor, polar (hydrogen-bond acceptor and hydrogenbond donor), or hydrophobic were assigned with the ph4_ aType function in the software suite MOE. For SURFCATS, surface points were calculated with the Gauss–Connolly function in MOE with a spacing of 2 E which were subsequently assigned to the pharmacophore type of the nearest atom. Finally, each bin of the three descriptors was scaled by the added occurrence of the respective PPPs. For comparison with a conceptually different descriptor, the MACCS keys were used as implemented in MOE. To assess the degree of scaffold hopping, one must define the term “scaffold”. Herein, we followed the concept of Xu and Johnson employing the software suite Meqi, which has recently been devised for the analysis of chemical libraries. 27] Two different definitions of a scaffold were applied: cyclic system (“Scaffold”, Sc) and reduced cyclic system (“Reduced Scaffold”, ReSc) (Figure 2). In Meqi, each molecular topology is specified by a particular molecular equivalence index (meqi) which is used to distinguish between different scaffolds and reduced scaffolds. Ligands from ten different target classes from the COBRA database of annotated ligands (version 2.1, 4705 molecules) were used as reference for retrospective virtual screening: angiotensin-converting enzyme (ACE, 44 compounds, 28 scaffolds, 17 reduced scaffolds), cyclooxygenase 2 (COX2, 94, 27, 14), corticotropin-releasing factor (CRF antagonists, 63, 33, 23), dipeptidyl peptidase IV (DPP, 25, 13, 7), human immunodeficiency virus protease (HIVP, 58, 46, 31), matrix metalloproteinase (MMP, 77, 47, 19), neurokinin receptors (NK, 118, 65, 49), peroxisome proliferator-activated receptor (PPAR, 35, 29, 17), b-amyloid-converting enzyme (BACE, 44, 13, 12), and thrombin (THR, 188, 100, 36). According to the number of scaffolds and reduced scaffolds in relation to the number of molecules, the datasets range from sets with a low scaffold diversity (for example, COX2) to sets with a large relative scaffold diversity (such as PPAR and HIVP). The complete COBRA database contained 1628 different scaffolds and 637 distinct reduced scaffolds. For retrospective screening, each molecule from each target class was taken iteratively as the reference molecule for a virtual screening experiment, in which all other molecules were ranked according to their similarity to the reference molecule. For quantification of “similarity” three similarity indices were employed: Manhattan distance [Eq. (1)] , Euclidean distance [Eq. (2)] , and Tanimoto similarity [Eq. (3)]:

Homology Model-Based Virtual Screening for GPCR Ligands Using Docking and Target-Biased Scoring

The current study investigates the combination of two recently reported techniques for the improvement of homology model-based virtual screening for G-protein coupled receptor (GPCR) ligands. First, ligand-supported homology modeling was used to generate receptor models that were in agreement with mutagenesis data and structure-activity relationship information of the ligands. Second, interaction patterns from known ligands to the receptor were applied for scoring and rank ordering compounds from a virtual library using ligand-receptor interaction fingerprint-based similarity (IFS). Our approach was evaluated in retrospective virtual screening experiments for antagonists of the metabotropic glutamate receptor (mGluR) subtype 5. The results of our approach were compared to the results obtained by conventional scoring functions (Dock-Score, PMF-Score, Gold-Score, ChemScore, and FlexX-Score). The IFS lead to significantly higher enrichment rates, relative to the competing scoring functions. Though using a target-biased scoring approach, the results were not biased toward the chemical classes of the reference structures. Our results indicate that the presented approach has the potential to serve as a general setup for successful structure-based GPCR virtual screening.

Total Synthesis of Chondramide C and Its Binding Mode to F‐Actin

The actin cytoskeleton maintains the cell s shape and is essential for cell movement, phagocytosis, and cytokinesis. Small molecules that interfere with the dynamic assembly and disassembly of actin have hence proven to be invaluable tools for chemical biology and medicinal chemistry research. In particular, natural products have been uncovered that either inhibit or induce F-actin polymer formation from the monomeric G-actin and thereby modulate the maintenance of the cytoskeleton. Phalloidin (1), jasplakinolide (2), and chondramide C (3) (Scheme 1) stabilize F-actin by a similar mode of action. In contrast to 1, jasplakinolide (2) and chondramide C (3) are cell-permeable and display potency against tumor cell lines which renders them interesting target structures for drug discovery. While several total syntheses of 2 have been described, the commercially not available 18membered ring cyclodepsipeptide 3 has not been prepared so far, and its stereochemistry had remained unresolved. Here we unveil a successful total synthesis of chondramide C (3) that has allowed us to easily access diastereoisomers and firmly assign the configuration of all its stereogenic centers. Furthermore, initial biological investigations and results of computationally docking phalloidin (1) and chondramide C (3) to its molecular target site on F-actin are reported. In a retrosynthetic sense it was planned to synthesize 3 via the peptide acid 4 from acids 6–8, Fmoc-Ala-OH (9), and

Recent trends and observations in the design of high-quality screening collections

The design of a high-quality screening collection is of utmost importance for the early drug-discovery process and provides, in combination with high-quality assay systems, the foundation of future discoveries. Herein, we review recent trends and observations to successfully expand the access to bioactive chemical space, including the feedback from hit assessment interviews of high-throughput screening campaigns; recent successes with chemogenomics target family approaches, the identification of new relevant target/domain families, diversity-oriented synthesis and new emerging compound classes, and non-classical approaches, such as fragment-based screening and DNA-encoded chemical libraries. The role of in silico library design approaches are emphasized.

Anticancer properties of an important drug lead podophyllotoxin can be efficiently mimicked by diverse heterocyclic scaffolds accessible via one-step synthesis.

Structural simplification of an antimitotic natural product podophyllotoxin with mimetic heterocyclic scaffolds constructed using multicomponent reactions led to the identification of compounds exhibiting low nanomolar antiproliferative and apoptosis-inducing properties. The most potent compounds were found in the dihydropyridopyrazole, dihydropyridonaphthalene, dihydropyridoindole, and dihydropyridopyrimidine scaffold series. Biochemical mechanistic studies performed with dihydropyridopyrazole compounds showed that these heterocycles inhibit in vitro tubulin polymerization and disrupt the formation of mitotic spindles in dividing cells at low nanomolar concentrations, in a manner similar to podophyllotoxin itself. Separation of a racemic dihydropyridonaphthalene into individual enantiomers demonstrated that only the optical antipode matching the absolute configuration of podophyllotoxin possessed potent anticancer activity. Computer modeling, performed using the podophyllotoxin binding site on β-tubulin, provided a theoretical understanding of these successful experimental findings.