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(41 - 60 of 130)

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Manno-epi-cyclophellitols enable activity-based protein profiling of human α-mannosidases and discovery of new Golgi mannosidase II inhibitors
Manno-epi-cyclophellitols enable activity-based protein profiling of human α-mannosidases and discovery of new golgi mannosidase II inhibitors
Discovery of a NAPE-PLD inhibitor that modulates emotional behavior in mice
Olaparib based photo-affinity probes for PARP-1 detection in living cells
Discovery of N-(Indazol-3-yl)piperidine-4-carboxylic Acids as RORγt Allosteric Inhibitors for Autoimmune Diseases
Stress-induced modulation of endocannabinoid signaling leads to delayed strengthening of synaptic connectivity in the amygdala
Structure–Activity Relationship Studies of α-Ketoamides as Inhibitors of the Phospholipase A and Acyltransferase Enzyme Family
Identification of α,β-Hydrolase Domain Containing Protein 6 as a Diacylglycerol Lipase in Neuro-2a Cells
Development of a Retinal-Based Probe for the Profiling of Retinaldehyde Dehydrogenases in Cancer Cells
Activity-based protein profiling of the human failing ischemic heart reveals alterations in hydrolase activities involving the endocannabinoid system
Identification of alpha,beta-Hydrolase Domain Containing Protein 6 as a Diacylglycerol Lipase in Neuro-2a Cells
ABHD2 inhibitor identified by activity-based protein profiling reduces acrosome reaction
Structure Kinetics Relationships and Molecular Dynamics Show Crucial Role for Heterocycle Leaving Group in Irreversible Diacylglycerol Lipase Inhibitors
Endocannabinoid contributions to alcohol habits and motivation: Relevance to treatment
Drug Discovery Maps, a Machine Learning Model That Visualizes and Predicts Kinome-Ilnhibitor Interaction Landscapes
Comprehensive structure-activity-relationship of azaindoles as highly potent FLT3 inhibitors
Comprehensive structure-activity-relationship of azaindoles as highly potent FLT3 inhibitors
High Fat Diet Increases Circulating Endocannabinoids Accompanied by Increased Synthesis Enzymes in Adipose Tissue
Activity-based protein profiling identifies α-ketoamides as inhibitors for Phospholipase A2 Group XVI
Drug Discovery Maps, a Machine Learning Model That Visualizes and Predicts Kinome-Inhibitor Interaction Landscapes

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