15 research outputs found
Recognition and Accommodation at the Androgen Receptor Coactivator Binding Interface
Prostate cancer is a leading killer of men in the industrialized world. Underlying this disease is the aberrant action of the androgen receptor (AR). AR is distinguished from other nuclear receptors in that after hormone binding, it preferentially responds to a specialized set of coactivators bearing aromatic-rich motifs, while responding poorly to coactivators bearing the leucine-rich “NR box” motifs favored by other nuclear receptors. Under normal conditions, interactions with these AR-specific coactivators through aromatic-rich motifs underlie targeted gene transcription. However, during prostate cancer, abnormal association with such coactivators, as well as with coactivators containing canonical leucine-rich motifs, promotes disease progression. To understand the paradox of this unusual selectivity, we have derived a complete set of peptide motifs that interact with AR using phage display. Binding affinities were measured for a selected set of these peptides and their interactions with AR determined by X-ray crystallography. Structures of AR in complex with FxxLF, LxxLL, FxxLW, WxxLF, WxxVW, FxxFF, and FxxYF motifs reveal a changing surface of the AR coactivator binding interface that permits accommodation of both AR-specific aromatic-rich motifs and canonical leucine-rich motifs. Induced fit provides perfect mating of the motifs representing the known family of AR coactivators and suggests a framework for the design of AR coactivator antagonists
25th annual computational neuroscience meeting: CNS-2016
The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong
Surfactant-Only Stabilized Dispersions of Multiwalled Carbon Nanotubes in High-Electrolyte-Concentration Brines
Multiwalled carbon
nanotubes (MWNTs) exhibit promising properties
for potential applications in oil production. Because of their substantial
surface area, they could be used as carriers for catalysts or chemicals
into subsurface oil and gas zones to change the properties of reservoir
fluids or rock. A prerequisite for utilizing the MWNT in reservoir
applications is to generate stable aqueous-phase dispersions that
are well-dispersed and able to propagate successfully through the
reservoir medium. In this study, different types of surfactants were
investigated for their ability to disperse MWNTs in high-ionic-strength
solutions typical of oil reservoirs up to 10% American Petroleum Institute
(API) brine (8 wt % NaCl and 2 wt % CaCl<sub>2</sub>). Stable nanotube
dispersions in deionized water were achieved with the anionic surfactants
evaluated. Compression of the electrical double layer, however, at
high ionic strength, e.g., >3 wt % electrolytes, led to rapid aggregation
of the anionic surfactant-aided nanotube dispersion. This study showed
that by dispersing nanotubes in nonionic surfactant such as alkylphenol
polyethoxylates with a large number of ethylene oxide (EO) groups,
stable MWNT dispersions were obtained in 10 wt % brine. In the sandpack
column test, a binary surfactant formulation, which consisted of a
nonionic surfactant and an anionic surfactant in the proper ratios,
exhibited an excellent capability to propagate MWNT, with 96% of the
injected nanotubes recovered in the effluent. The adsorption density
of surfactants onto MWNT was determined to be 9 molecules/nm<sup>2</sup> from the shift of the CMC value in the surface tension measurement.
This study reveals that steric repulsion between the nanotubes could
eliminate the aggregation of dispersed MWNT under the high-electrolyte-concentration
condition, whereas nanotube–nanotube and nanotube–sand
surface electrical repulsion could assist in the transport of the
MWNT dispersion through porous media
Effect of Reservoirs Conditions on Designing Single-Well Chemical Tracer Tests Under Extreme Brine Conditions
Disrupting Admicelle Formation and Preventing Surfactant Adsorption on Metal Oxide Surfaces Using Sacrificial Polyelectrolytes
Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation
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An LXR-Cholesterol Axis Creates a Metabolic Co-Dependency for Brain Cancers
Small-molecule inhibitors targeting growth factor receptors have failed to show efficacy for brain cancers, potentially due to their inability to achieve sufficient drug levels in the CNS. Targeting non-oncogene tumor co-dependencies provides an alternative approach, particularly if drugs with high brain penetration can be identified. Here we demonstrate that the highly lethal brain cancer glioblastoma (GBM) is remarkably dependent on cholesterol for survival, rendering these tumors sensitive to Liver X receptor (LXR) agonist-dependent cell death. We show that LXR-623, a clinically viable, highly brain-penetrant LXRα-partial/LXRβ-full agonist selectively kills GBM cells in an LXRβ- and cholesterol-dependent fashion, causing tumor regression and prolonged survival in mouse models. Thus, a metabolic co-dependency provides a pharmacological means to kill growth factor-activated cancers in the CNS
Profiling of engineering hotspots identifies an allosteric CRISPR-Cas9 switch.
The clustered, regularly interspaced, short palindromic repeats (CRISPR)-associated protein Cas9 from Streptococcus pyogenes is an RNA-guided DNA endonuclease with widespread utility for genome modification. However, the structural constraints limiting the engineering of Cas9 have not been determined. Here we experimentally profile Cas9 using randomized insertional mutagenesis and delineate hotspots in the structure capable of tolerating insertions of a PDZ domain without disruption of the enzyme's binding and cleavage functions. Orthogonal domains or combinations of domains can be inserted into the identified sites with minimal functional consequence. To illustrate the utility of the identified sites, we construct an allosterically regulated Cas9 by insertion of the estrogen receptor-α ligand-binding domain. This protein showed robust, ligand-dependent activation in prokaryotic and eukaryotic cells, establishing a versatile one-component system for inducible and reversible Cas9 activation. Thus, domain insertion profiling facilitates the rapid generation of new Cas9 functionalities and provides useful data for future engineering of Cas9