Probing the Solution Structure of IκB Kinase (IKK) Subunit γ and Its Interaction with Kaposi Sarcoma-associated Herpes Virus Flice-interacting Protein and IKK Subunit β by EPR Spectroscopy.

Viral flice-interacting protein (vFLIP), encoded by the oncogenic Kaposi sarcoma-associated herpes virus (KSHV), constitutively activates the canonical nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) pathway. This is achieved through subversion of the IκB kinase (IKK) complex (or signalosome), which involves a physical interaction between vFLIP and the modulatory subunit IKKγ. Although this interaction has been examined both in vivo and in vitro, the mechanism by which vFLIP activates the kinase remains to be determined. Because IKKγ functions as a scaffold, recruiting both vFLIP and the IKKα/β subunits, it has been proposed that binding of vFLIP could trigger a structural rearrangement in IKKγ conducive to activation. To investigate this hypothesis we engineered a series of mutants along the length of the IKKγ molecule that could be individually modified with nitroxide spin labels. Subsequent distance measurements using electron paramagnetic resonance spectroscopy combined with molecular modeling and molecular dynamics simulations revealed that IKKγ is a parallel coiled-coil whose response to binding of vFLIP or IKKβ is localized twisting/stiffening and not large-scale rearrangements. The coiled-coil comprises N- and C-terminal regions with distinct registers accommodated by a twist: this structural motif is exploited by vFLIP, allowing it to bind and subsequently activate the NF-κB pathway. In vivo assays confirm that NF-κB activation by vFLIP only requires the N-terminal region up to the transition between the registers, which is located directly C-terminal of the vFLIP binding site

Side chain to main chain hydrogen bonds stabilize a polyglutamine helix in a transcription factor

Polyglutamine (polyQ) tracts are low-complexity regions and their expansion is linked to certain neurodegenerative diseases. Here the authors combine experimental and computational approaches to find that the length of the androgen receptor polyQ tract correlates with its helicity and show that the polyQ helical structure is stabilized by hydrogen bonds between the Gln side chains and main chain carbonyl groups

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

FRETpredict

<p>FRETpredict is a Python package based on the rotamer library approach for calculating FRET efficiency from protein conformational ensembles and MD trajectories.</p&gt

FRETpredict: a Python package for FRET efficiency predictions using rotamer libraries

Abstract Förster resonance energy transfer (FRET) is a widely-used and versatile technique for the structural characterization of biomolecules. Here, we introduce FRETpredict, an easy-to-use Python software to predict FRET efficiencies from ensembles of protein conformations. FRETpredict uses a rotamer library approach to describe the FRET probes covalently bound to the protein. The software efficiently and flexibly operates on large conformational ensembles such as those generated by molecular dynamics simulations to facilitate the validation or refinement of molecular models and the interpretation of experimental data. We provide access to rotamer libraries for many commonly used dyes and linkers and describe a general methodology to generate new rotamer libraries for FRET probes. We demonstrate the performance and accuracy of the software for different types of systems: a rigid peptide (polyproline 11), an intrinsically disordered protein (ACTR), and three folded proteins (HiSiaP, SBD2, and MalE). FRETpredict is open source (GPLv3) and is available at github.com/KULL-Centre/FRETpredict and as a Python PyPI package at pypi.org/project/FRETpredict

DEER-PREdict: Software for efficient calculation of spin-labeling EPR and NMR data from conformational ensembles

Owing to their plasticity, intrinsically disordered and multidomain proteins require descriptions based on multiple conformations, thus calling for techniques and analysis tools that are capable of dealing with conformational ensembles rather than a single protein structure. Here, we introduce DEER-PREdict, a software program to predict Double Electron-Electron Resonance distance distributions as well as Paramagnetic Relaxation Enhancement rates from ensembles of protein conformations. DEER-PREdict uses an established rotamer library approach to describe the paramagnetic probes which are bound covalently to the protein.DEER-PREdict has been designed to operate efficiently on large conformational ensembles, such as those generated by molecular dynamics simulation, to facilitate the validation or refinement of molecular models as well as the interpretation of experimental data. The performance and accuracy of the software is demonstrated with experimentally characterized protein systems: HIV-1 protease, T4 Lysozyme and Acyl-CoA-binding protein. DEER-PREdict is open source (GPLv3) and available at github.com/KULL-Centre/DEERpredict and as a Python PyPI package pypi.org/project/DEERPREdict.M.B.A.K. acknowledges funding from the Lundbeck Foundation (lundbeckfonden.com). R.C. acknowledges funding from MINECO (CTQ2016-78636-P, https://www.mineco.gob.es/). K.L.-L. acknowledges funding via a Sapere Aude Starting Grant from the Danish Council for Independent Research (Natur og Univers, Det Frie Forskningsråd, 12-126214, https://dff.dk/) and the Lundbeck Foundation BRAINSTRUC initiative in structural biology (R155-2015-2666, lundbeckfonden.com). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewe

Loop Interactions and Dynamics Tune the Enzymatic Activity of the Human Histone Deacetylase 8

The human histone deacetylase 8 (HDAC8) is a key hydrolase in gene regulation and has been identified as a drug target for the treatment of several cancers. Previously the HDAC8 enzyme has been extensively studied using biochemical techniques, X-ray crystallography, and computational methods. Those investigations have yielded detailed information about the active site and have demonstrated that the substrate entrance surface is highly dynamic. Yet it has remained unclear how the dynamics of the entrance surface tune and influence the catalytic activity of HDAC8. Using long time scale all atom molecular dynamics simulations we have found a mechanism whereby the interactions and dynamics of two loops tune the configuration of functionally important residues of HDAC8 and could therefore influence the activity of the enzyme. We subsequently investigated this hypothesis using a well-established fluorescence activity assay and a noninvasive real-time progression assay, where deacetylation of a p53 based peptide was observed by nuclear magnetic resonance spectroscopy. Our work delivers detailed insight into the dynamic loop network of HDAC8 and provides an explanation for a number of experimental observations