Browsing Department of Chemistry by Author "de Bruyn Kops, Christina"
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ALADDIN: Docking Approach Augmented by Machine Learning for Protein Structure Selection Yields Superior Virtual Screening Performance
Fan, Ningning; Bauer, Christoph; Stork, Conrad; de Bruyn Kops, Christina; Kirchmair, Johannes (Peer reviewed; Journal article, 2019-10)Protein flexibility and solvation pose major challenges to docking algorithms and scoring functions. One established strategy for addressing these challenges is to use multiple protein conformations for docking (all‐against‐all ... -
Analysis of the FLVR motif of SHIP1 and its importance for the protein stability of SH2 containing signaling proteins
Ehm, Patrick; Lange, Faabiola; Hentschel, Carolin; Jepsen, Anneke; Glück, Madeleine; Nelson, Nina; Bettin, Bettina; de Bruyn Kops, Christina; Kirchmair, Johannes; Nalaskowski, Marcus; Jücker, Manfred (Peer reviewed; Journal article, 2019)Binding of proteins with SH2 domains to tyrosine-phosphorylated signaling proteins is a key mechanism for transmission of biological signals within the cell. Characterization of dysregulated proteins in cell signaling ... -
FAME 3: Predicting the sites of metabolism in synthetic compounds and natural products for phase 1 and phase 2 metabolic enzymes
Sicho, Martin; Stork, Conrad; Mazzolari, Angelica; de Bruyn Kops, Christina; Pedretti, Alessandro; Testa, Bernard; Vistoli, Giulio; Svozil, Daniel; Kirchmair, Johannes (Journal article; Peer reviewed, 2019)In this work we present the third generation of FAst MEtabolizer (FAME 3), a collection of extra trees classifiers for the prediction of sites of metabolism (SoMs) in small molecules such as drugs, druglike compounds, ... -
GLORY: Generator of the structures of likely cytochrome P450 metabolites based on predicted sites of metabolism
de Bruyn Kops, Christina; Stork, Conrad; Sicho, Martin; Kochev, Nikolay; Svozil, Daniel; Jeliazkova, Nina; Kirchmair, Johannes (Peer reviewed; Journal article, 2019-06-12)Computational prediction of xenobiotic metabolism can provide valuable information to guide the development of drugs, cosmetics, agrochemicals, and other chemical entities. We have previously developed FAME 2, an effective ...