(S)Pinning down protein interactions by NMR

Protein molecules are highly diverse communication platforms and their interaction repertoire stretches from atoms over small molecules such as sugars and lipids to macromolecules. An important route to understanding molecular communication is to quantitatively describe their interactions. These types of analyses determine the amounts and proportions of individual constituents that participate in a reaction as well as their rates of reactions and their thermodynamics. Although many different methods are available, there is currently no single method able to quantitatively capture and describe all types of protein reactions, which can span orders of magnitudes in affinities, reaction rates, and lifetimes of states. As the more versatile technique, solution NMR spectroscopy offers a remarkable catalogue of methods that can be successfully applied to the quantitative as well as qualitative descriptions of protein interactions. In this review we provide an easy‐access approach to NMR for the non‐NMR specialist and describe how and when solution state NMR spectroscopy is the method of choice for addressing protein ligand interaction. We describe very briefly the theoretical background and illustrate simple protein–ligand interactions as well as typical strategies for measuring binding constants using NMR spectroscopy. Finally, this review provides examples of caveats of the method as well as the options to improve the outcome of an NMR analysis of a protein interaction reaction

G_s protein peptidomimetics as allosteric modulators of the β₂-adrenergic receptor

A series of G(s) protein peptidomimetics were designed and synthesised based on the published X-ray crystal structure of the active state β(2)-adrenergic receptor (β(2)AR) in complex with the G(s) protein (PDB 3SN6). We hypothesised that such peptidomimetics may function as allosteric modulators that target the intracellular G(s) protein binding site of the β(2)AR. Peptidomimetics were designed to mimic the 15 residue C-terminal α-helix of the G(s) protein and were pre-organised in a helical conformation by (i, i + 4)-stapling using copper catalysed azide alkyne cycloaddition. Linear and stapled peptidomimetics were analysed by circular dichroism (CD) and characterised in a membrane-based cAMP accumulation assay and in a bimane fluorescence assay on purified β(2)AR. Several peptidomimetics inhibited agonist isoproterenol (ISO) induced cAMP formation by lowering the ISO maximal efficacy up to 61%. Moreover, some peptidomimetics were found to significantly decrease the potency of ISO up to 39-fold. In the bimane fluorescence assay none of the tested peptidomimetics could stabilise an active-like conformation of β(2)AR. Overall, the obtained pharmacological data suggest that some of the peptidomimetics may be able to compete with the native G(s) protein for the intracellular binding site to block ISO-induced cAMP formation, but are unable to stabilise an active-like receptor conformation

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

Conformational rigidity and protein dynamics at distinct timescales regulate PTP1B activity and allostery

Protein function originates from a cooperation of structural rigidity, dynamics at different timescales and allostery. However, how these three pillars of protein function are integrated is still only poorly understood. Here we show how these pillars are connected in Protein Tyrosine Phosphatase 1B (PTP1B), a drug target for diabetes and cancer that catalyzes the dephosphorylation of numerous substrates in essential signaling pathways. By combining new experimental and computational data on wt-PTP1B and ≥10 PTP1B variants in multiple states, we discovered a fundamental and evolutionarily conserved CH/π switch that is critical for positioning the catalytically important WPD loop. Furthermore, our data show that PTP1B uses conformational and dynamic allostery to regulate its activity. This shows that both conformational rigidity and dynamics are essential for controlling protein activity. This connection between rigidity and dynamics at different timescales is likely a hallmark of all enzyme function

Hyperon signatures in the PANDA experiment at FAIR

We present a detailed simulation study of the signatures from the sequential decays of the triple-strange pbar p -> Ω+Ω- -> K+ΛbarK- Λ -> K+pbarπ+K-pπ- process in the PANDA central tracking system with focus on hit patterns and precise time measurement. We present a systematic approach for studying physics channels at the detector level and develop input criteria for tracking algorithms and trigger lines. Finally, we study the beam momentum dependence on the reconstruction efficiency for the PANDA detector