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Although RII protein kinase A (PKA) regulatory subunits are constitutively localized to discrete cellular compartments through binding to A-kinase-anchoring proteins (AKAPs), RI subunits are primarily diffuse in the cytoplasm. In this paper, we report a novel AKAP-dependent localization of RIα to distinct organelles, specifically, multivesicular bodies (MVBs). This localization depends on binding to AKAP11, which binds tightly to free RIα or RIα in complex with catalytic subunit (holoenzyme). However, recruitment to MVBs occurs only with the release of PKA catalytic subunit (PKAc). This recruitment is reversed by reassociation with PKAc, and it is disrupted by the presence of AKAP peptides, mutations in the RIα AKAP-binding site, or knockdown of AKAP11. Cyclic adenosine monophosphate binding not only unleashes active PKAc but also leads to the targeting of AKAP11:RIα to MVBs. Therefore, we show that the RIα holoenzyme is part of a signaling complex with AKAP11, in which AKAP11 may direct RIα functionality after disassociation from PKAc. This model defines a new paradigm for PKA signaling.
Pubmed ID: 21502359 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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