Fragment‐Based De Novo Design Reveals a Small‐Molecule Inhibitor of Helicobacter Pylori HtrA

Sustained identification of innovative chemical entities is key for the success of chemical biology and drug discovery. We report the fragment‐based, computer‐assisted de novo design of a small molecule inhibiting Helicobacter pylori HtrA protease. Molecular binding of the designed compound to HtrA was confirmed through biophysical methods, supporting its functional activity in vitro. Hit expansion led to the identification of the currently best‐in‐class HtrA inhibitor. The results obtained reinforce the validity of ligand‐based de novo design and binding‐kinetics‐guided optimization for the efficient discovery of pioneering lead structures and prototyping drug‐like chemical probes with tailored bioactivity.     

Multidimensional De Novo Design Reveals 5‐HT2B Receptor‐Selective Ligands

We report a multi‐objective de novo design study driven by synthetic tractability and aimed at the prioritization of computer‐generated 5‐HT_2B receptor ligands with accurately predicted target‐binding affinities. Relying on quantitative bioactivity models we designed and synthesized structurally novel, selective, nanomolar, and ligand‐efficient 5‐HT_2B modulators with sustained cell‐based effects. Our results suggest that seamless amalgamation of computational activity prediction and molecular design with microfluidics‐assisted synthesis enables the swift generation of small molecules with the desired polypharmacology.     

Context-based identification of protein-protein interfaces and "hot-spot" residues

Reliable determination of protein-protein interaction sites is of critical importance for structure-based design of small molecules modulating protein function through macromolecular interfaces. We present an alignment-free computational method for prediction of protein-protein interface residues. The method ("iPred") is based on a knowledge-based scoring function adapted from the field of protein folding and small molecule docking. Based on a training set of 394 hetero-dimeric proteins iPred achieves sustained accuracy on an external unbound test set. Prediction robustness was assessed from more than 1500 diverse complexes containing homo- and hetero-dimers. The technique does not rely on sequence conservation, so that rapid interface identification is possible even for proteins for which homologs are unknown or lack conserved residue patterns in interface region. Functional "hot-spot" residues are enriched among the predicted interface residues, rendering the method predestined for macromolecular binding site identification and drug design studies aiming at modulating protein-protein interaction that might influence protein function. For a comparative structural model of peptidase HtrA from Helicobacter pylori, we performed mutation studies for predicted hot-spot residues, which were confirmed as functionally relevant for HtrA activity or oligomerization.     

Assay Related Target Similarity (ARTS) - chemogenomics approach for quantitative comparison of biological targets

Computer-based chemogenomics approaches compare macromolecular drug targets based on their amino acid sequences or derived properties, by similarity of their ligands, or according to ligand-target interaction models. Here we present ARTS (Assay Related Target Similarity) as a quantitative index that estimates target similarity directly from measured affinities of a set of probe compounds. This approach reduces the risk of deducing artificial target relationships from mutually inactive compounds. ARTS implements a scoring scheme that matches intertarget similarity based on dose-response measurements. While all experimentally derived target similarities have a tendency to be data set-dependent, we demonstrate that ARTS depends less on the used data set than the commonly used Pearson correlation or Tanimoto index.     

Divergent Synthesis of Molecular Winch Prototypes

We report the synthesis of conceptually new prototypes of molecular winches with the ultimate aim to investigate the work performed by a single ruthenium-based molecular motor anchored on a surface by probing its ability to pull a load upon electrically-driven directional rotation. According to a technomimetic design, the motor was embedded in a winch structure, with a long flexible polyethylene glycol chain terminated by an azide hook to connect a variety of molecular loads. The structure of the motor was first derivatized by means of two sequential cross-coupling reactions involving a penta(4-halogenophenyl)cyclopentadienyl hydrotris(indazolyl)borate ruthenium(II) precursor and the resulting benzylamine derivative was next exploited as key intermediate in the divergent synthesis of a family of nanowinch prototypes. A one-pot method involving sequential peptide coupling and Cu-catalyzed azide-alkyne cycloaddition was developed to yield four loaded nanowinches, with load fragments encompassing triptycene, fullerene and porphyrin moieties.     

Protein‐protein docking by shape‐complementarity and property matching

We present a computational approach to protein‐protein docking based on surface shape complementarity (“ProBinder”). Within this docking approach, we implemented a new surface decomposition method that considers local shape features on the protein surface. This new surface shape decomposition results in a deterministic representation of curvature features on the protein surface, such as “knobs,” “holes,” and “flats” together with their point normals. For the actual docking procedure, we used geometric hashing, which allows for the rapid, translation‐, and rotation‐free comparison of point coordinates. Candidate solutions were scored based on knowledge‐based potentials and steric criteria. The potentials included electrostatic complementarity, desolvation energy, amino acid contact preferences, and a van‐der‐Waals potential. We applied ProBinder to a diverse test set of 68 bound and 30 unbound test cases compiled from the Dockground database. Sixty‐four percent of the protein‐protein test complexes were ranked with an root mean square deviation (RMSD) < 5 Å to the target solution among the top 10 predictions for the bound data set. In 82% of the unbound samples, docking poses were ranked within the top ten solutions with an RMSD < 10 Å to the target solution. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Linearformen in Logarithmen von U-Zahlen und Transzendenz von Potenzen II

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