Julie Penzotti

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In bee venom phospholipase A2, histidine-34 probably functions as a Brønsted base to deprotonate the attacking water. Aspartate-64 and tyrosine-87 form a hydrogen bonding network with histidine-34. We have prepared mutants at these positions and studied their kinetic properties. The mutant in which histidine-34 is changed to glutamine is catalytically(More)
A variety of machine learning algorithms, including hierarchical clustering, decision trees, k-nearest neighbours, support vector machines and bagging, were applied to construct models to predict the molecular weight of the polymers produced by a set of 96 homogeneous catalysts. The goal of the study was to develop models that could be used to screen large(More)
Myasthenia gravis (MG) is characterized by muscle weakness due to autoimmunity against the nicotinic acetylcholine receptor (nAChR). MG is associated with polymorphisms in HLA-DQ genes and the aim of the present study was to characterize structural differences in the peptide binding groove of HLA-DQ molecules positively and negatively associated with MG.(More)
Myelin oligodendrocyte glycoprotein (MOG) is a protein on the surface of myelin sheaths. It is a putative target of the autoimmune attack in the inflammatory and demyelinating CNS disease multiple sclerosis and its animal model, experimental autoimmune encephalomyelitis. MOG belongs to the immunoglobulin superfamily (IgSF), and its extracellular N-terminal(More)
In order to develop robust machine-learning or statistical models for predicting biological activity, descriptors that capture the essence of the protein-ligand interaction are required. In the absence of structural information from X-ray or NMR experiments, deriving informative descriptors can be difficult. We have developed feature-map vectors (FMVs), a(More)
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