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81.
Fan (in Southeast Asian Bull Math 25, 217–221, 2001) determines the endomorphism type of a finite projective plane. In this note we show that Fan’s result actually characterizes the class of projective planes among the finite bipartite graphs of diameter three. In fact, this will follow from a generalization of Fan’s theorem and its converse to all finite bipartite graphs with diameter d and girth g such that (1) d + 1<g≤2d, and (2) every pair of adjacent edges is contained in a circuit of length g. 相似文献
82.
Xing Huang Detre Teschner Maria Dimitrakopoulou Alexey Fedorov Benjamin Frank Ralph Kraehnert Frank Rosowski Harry Kaiser Stephan Schunk Christiane Kuretschka Robert Schlgl Marc‐Georg Willinger Annette Trunschke 《Angewandte Chemie (Weinheim an der Bergstrasse, Germany)》2019,131(26):8801-8805
The direct conversion of syngas to ethanol, typically using promoted Rh catalysts, is a cornerstone reaction in CO2 utilization and hydrogen storage technologies. A rational catalyst development requires a detailed structural understanding of the activated catalyst and the role of promoters in driving chemoselectivity. Herein, we report a comprehensive atomic‐scale study of metal–promoter interactions in silica‐supported Rh, Rh–Mn, and Rh–Mn–Fe catalysts by aberration‐corrected (AC) TEM. While the catalytic reaction leads to the formation of a Rh carbide phase in the Rh–Mn/SiO2 catalyst, the addition of Fe results in the formation of bimetallic Rh–Fe alloys, which further improves the selectivity and prevents the carbide formation. In all promoted catalysts, Mn is present as an oxide decorating the metal particles. Based on the atomic insight obtained, structural and electronic modifications induced by promoters are revealed and a basis for refined theoretical models is provided. 相似文献
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Roy A. Meoded Dr. Reiko Ueoka Dr. Eric J. N. Helfrich Dr. Katja Jensen Nancy Magnus Prof. Dr. Birgit Piechulla Prof. Dr. Jörn Piel 《Angewandte Chemie (International ed. in English)》2018,57(36):11644-11648
Enzymatic core components from trans‐acyltransferase polyketide synthases (trans‐AT PKSs) catalyze exceptionally diverse biosynthetic transformations to generate structurally complex bioactive compounds. Here we focus on a group of oxygenases identified in various trans‐AT PKS pathways, including those for pederin, oocydins, and toblerols. Using the oocydin pathway homologue (OocK) from Serratia plymuthica 4Rx13 and N‐acetylcysteamine (SNAC) thioesters as test surrogates for acyl carrier protein (ACP)‐tethered intermediates, we show that the enzyme inserts oxygen into β‐ketoacyl moieties to yield malonyl ester SNAC products. Based on these data and the identification of a non‐hydrolyzed oocydin congener with retained ester moiety, we propose a unified biosynthetic pathway of oocydins, haterumalides, and biselides. By providing access to internal ester, carboxylate pseudostarter, and terminal hydroxyl functions, oxygen insertion into polyketide backbones greatly expands the biosynthetic scope of PKSs. 相似文献
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Enzymatic or In Vivo Installation of Propargyl Groups in Combination with Click Chemistry for the Enrichment and Detection of Methyltransferase Target Sites in RNA
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Schwaighofer A Schroeter T Mika S Hansen K Ter Laak A Lienau P Reichel A Heinrich N Müller KR 《Journal of chemical information and modeling》2008,48(4):785-796
Metabolic stability is an important property of drug molecules that should-optimally-be taken into account early on in the drug design process. Along with numerous medium- or high-throughput assays being implemented in early drug discovery, a prediction tool for this property could be of high value. However, metabolic stability is inherently difficult to predict, and no commercial tools are available for this purpose. In this work, we present a machine learning approach to predicting metabolic stability that is tailored to compounds from the drug development process at Bayer Schering Pharma. For four different in vitro assays, we develop Bayesian classification models to predict the probability of a compound being metabolically stable. The chosen approach implicitly takes the "domain of applicability" into account. The developed models were validated on recent project data at Bayer Schering Pharma, showing that the predictions are highly accurate and the domain of applicability is estimated correctly. Furthermore, we evaluate the modeling method on a set of publicly available data. 相似文献
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