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Proteins of the Sec1 family have been shown to interact with target-membrane t-SNAREs that are homologous to the neuronal protein syntaxin. We demonstrate that yeast Sec1p coprecipitates not only the syntaxin homologue Ssop, but also the other two exocytic SNAREs (Sec9p and Sncp) in amounts and in proportions characteristic of SNARE complexes in yeast lysates. The interaction between Sec1p and Ssop is limited by the abundance of SNARE complexes present in sec mutants that are defective in either SNARE complex assembly or disassembly. Furthermore, the localization of green fluorescent protein (GFP)-tagged Sec1p coincides with sites of vesicle docking and fusion where SNARE complexes are believed to assemble and function. The proposal that SNARE complexes act as receptors for Sec1p is supported by the mislocalization of GFP-Sec1p in a mutant defective for SNARE complex assembly and by the robust localization of GFP-Sec1p in a mutant that fails to disassemble SNARE complexes. The results presented here place yeast Sec1p at the core of the exocytic fusion machinery, bound to SNARE complexes and localized to sites of secretion.
Pubmed ID: 10427089 RIS Download
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NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything
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