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Tim Geppert Ewgenij Proschak Gisbert Schneider 《Journal of computational chemistry》2010,31(9):1919-1928
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 相似文献
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Michael Schmuker Marien de Bruyne Melanie Hähnel Gisbert Schneider 《Chemistry Central journal》2007,1(1):11-10
Background
Olfactory receptors work at the interface between the chemical world of volatile molecules and the perception of scent in the brain. Their main purpose is to translate chemical space into information that can be processed by neural circuits. Assuming that these receptors have evolved to cope with this task, the analysis of their coding strategy promises to yield valuable insight in how to encode chemical information in an efficient way. 相似文献25.
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Fragment‐Based De Novo Design Reveals a Small‐Molecule Inhibitor of Helicobacter Pylori HtrA
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Thomas P. Schmidt Dr. Manja Böhm Katharina Stutz Daniel Reker Dr. Bernhard Pfeiffer Prof. Dr. Karl‐Heinz Altmann Prof. Dr. Steffen Backert Prof. Dr. Silja Wessler Prof. Dr. Gisbert Schneider 《Angewandte Chemie (International ed. in English)》2015,54(35):10244-10248
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. 相似文献
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Dr. Tiago Rodrigues Nadine Hauser Daniel Reker Dr. Michael Reutlinger Tiffany Wunderlin Dr. Jacques Hamon Dr. Guido Koch Prof. Dr. Gisbert Schneider 《Angewandte Chemie (International ed. in English)》2015,54(5):1551-1555
We report a multi‐objective de novo design study driven by synthetic tractability and aimed at the prioritization of computer‐generated 5‐HT2B 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‐HT2B 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. 相似文献
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