KV1.2 channel-specific blocker from Mesobuthus eupeus scorpion venom: Structural basis of selectivity.
Scorpion venom is an unmatched source of selective high-affinity ligands of potassium channels. There is a high
demand for such compounds to identify and manipulate the activity of particular channel isoforms. The objective
of this study was to obtain and characterize a specific ligand of voltage-gated potassium channel KV1.2. As a
result, we report the remarkable selectivity of the peptide MeKTx11-1 (α-KTx 1.16) from Mesobuthus eupeus
scorpion venom to this channel isoform. MeKTx11-1 is a high-affinity blocker of KV1.2 (IC50 ∼0.2 nM), while its
activity against KV1.1, KV1.3, and KV1.6 is 10 000, 330 and 45 000 fold lower, respectively, as measured using
the voltage-clamp technique on mammalian channels expressed in Xenopus oocytes. Two substitutions, G9V and
P37S, convert MeKTx11-1 to its natural analog MeKTx11-3 (α-KTx 1.17) having 15 times lower activity and
reduced selectivity to KV1.2. We produced MeKTx11-1 and MeKTx11-3 as well as their mutants MeKTx11-
1(G9V) and MeKTx11-1(P37S) recombinantly and demonstrated that point mutations provide an intermediate
effect on selectivity. Key structural elements that explain MeKTx11-1 specificity were identified by molecular
modeling of the toxin–channel complexes. Confirming our molecular modeling predictions, site-directed transfer
of these elements from the pore region of KV1.2 to KV1.3 resulted in the enhanced sensitivity of mutant KV1.3
channels to MeKTx11-1. We conclude that MeKTx11-1 may be used as a selective tool in neurobiology.
The method ofWave Packet Molecular Dynamics Method (WPMD) is a promising replacement of the classical molecular dynamics for the simulations of many-electron systems including nonideal plasmas. In this contribution we report on a packet splitting technique where an electron is represented by multiple Gaussians, with mixing coefficients playing the role of additional dynamic variables. It provides larger flexibility and better accuracy than the original WPMD with a single Gaussian per electron. As a test case we consider ionization of hydrogen atom in a short laser pulse, where the split packets provide a basis for quantum branching.
The wave packet molecular dynamics (WPMD) method provides a variational approximation to the solution of the time-dependent Schr¨odinger equation. Its application in the field of high-temperature dense plasmas has yielded diverging electron width (spreading), which results in diminishing electron-nuclear interactions. Electron spreading has previously been ascribed to a shortcoming of the WPMD method and has been counteracted by various heuristic additions to the models used. We employ more accurate methods to determine if spreading continues to be predicted by them and how WPMD can be improved. A scattering process involving a single dynamic electron interacting with a periodic array of statically screened protons is used as a model problem for comparison. We compare the numerically exact split operator Fourier transform method, the Wigner trajectory method, and the time-dependent variational principle (TDVP). Within the framework of the TDVP, we use the standard variational form of WPMD, the single Gaussian wave packet (WP), as well as a sum of Gaussian WPs, as in the split WP method. Wave packet spreading is predicted by all methods, so it is not the source of the unphysical diminishing of electron-nuclear interactions in WPMD at high temperatures. Instead, the Gaussian WP’s inability to correctly reproduce breakup of the electron’s probability density into localized density near the protons is responsible for the deviation from more accurate predictions. Extensions of WPMD must include a mechanism for breakup to occur in order to yield dynamics that lead to accurate electron densities.
Helical segments are common structural elements of membrane proteins. Dimerization and oligomerization of transmembrane (TM) α-helices provides the framework for spatial structure formation and protein-protein interactions. The membrane itself also takes part in the protein functioning. There are some examples of the mutual influence of the lipid bilayer properties and embedded membrane proteins. This work aims at the detail investigation of protein-lipid interactions using model systems: TM peptides corresponding to native protein segments. Three peptides were considered corresponding to TM domains of human glycophorin A (GpA), epidermal growth factor receptor (EGFR) and proposed TM-segment of human neuraminidase-1 (Neu1). A computational analysis of structural and dynamical properties was performed using molecular dynamics method. Monomers of peptides were considered incorporated into hydrated lipid bilayers. It was confirmed, that all these TM peptides have stable helical conformation in lipid environment, and the mutual adaptation of peptides and membrane was observed. It was shown that incorporation of the peptide into membrane results in the modulation of local and mean structural properties of the bilayer. Each peptide interacts with lipid acyl chains having special binding sites on the surface of central part of α-helix that exist for at least 200 ns. However, lipid acyl chains substitute each other faster occupying the same site. The formation of a special pattern of protein-lipid interactions may modulate the association of TM domains of membrane proteins, so membrane environment should be considered when proposing new substances targeting cell receptors.
This paper describes the surface environment of the dense plasma arcs that damage rf accelerators, tokamaks, and other high gradient structures. We simulate the dense, nonideal plasma sheath near a metallic surface using molecular dynamics (MD) to evaluate sheaths in the non-Debye region for high density, low temperature plasmas. We use direct two-component MD simulations where the interactions between all electrons and ions are computed explicitly. We find that the non-Debye sheath can be extrapolated from the Debye sheath parameters with small corrections. We find that these parameters are roughly consistent with previous particle-in-cell code estimates, pointing to densities in the range 10^24–10^25 m^3. The high surface fields implied by these results could produce field emission that would short the sheath and cause an instability in the time evolution of the arc, and this mechanism could limit the maximum density and surface field in the arc. These results also provide a way of understanding how the properties of the arc depend on the properties (sublimation energy, for example) of the metal. Using these results, and equating surface tension and plasma pressure, it is possible to infer a range of plasma densities and sheath potentials from scanning electron microscope images of arc damage. We find that the high density plasma these results imply and the level of plasma pressure they would produce is consistent with arc damage on a scale 100 nm or less, in examples where the liquid metal would cool before this structure would be lost. We find that the submicron component of arc damage, the burn voltage, and fluctuations in the visible light production of arcs may be the most direct indicators of the parameters of the dense plasma arc, and the most useful diagnostics of the mechanisms limiting gradients in accelerators.
Plasmatic membranes contain high amount of membrane proteins. They perform vital functions of life, so any disruptions in their structure result in pathologies and diseases. Studies of these proteins with experimental methods are very complicated and expensive, as they require the membrane environment. Despite considerable progress achieved so far in methods of structure determination and property analysis, many computational methods are developing to predict the structural and dynamical parameters of proteins in membranes. Among the algorithms of modeling are the homology analysis, de novo structure prediction, molecular dynamics simulations and other. With growing computational capabilities, sophisticated techniques are developed taking into account more environmental factors. Combined approaches with different levels of approximation of intermolecular interactions are widely used. The major interest in studies of membrane proteins is focused on their transmembrane domains that are fundamental structural elements and are constituted by α-helices or helical bundles incorporated into lipid bilayer in most cases. Therefore, the fundamental problem of interaction of a pair of helices in membrane arises: the exact mechanism of this process is still not so clear. In place of the prevailing concept of dimerization motifs that states the importance of protein-protein contacts, a new model of the membrane as an adaptable lipid matrix is proposed. It states that biological membrane can adjust its properties around proteins and also modulates their activity. This mechanism of the mutual influence of two components is challenging modern computational methods of membrane model- ing because these systems are quite large and include many components to be treated accurately. Nowadays, investigations of the complex multi-component model systems become possible with modern methods of computational experiment.
Transmembrane α-helical domains are common structural elements in membrane proteins structure. They are involved into functioning of receptors and ion channels. Protein-protein interactions in lipid environment underlie the function of the most membrane systems. The properties of lipid environment can modulate the activity of membrane proteins, such as receptor tyrosine kinases. Glycophorin A is a glycoprotein that forms a very stable dimer. Its transmembrane domain is known as a good model system to study dimerization of α-helices. The major mechanism of the disturbance of a dimer by point mutations is thought to be a change of protein-protein contacts, but the role of the membrane is not well understood. In present work we study the behavior of transmembrane segment of human glycophorin A and two mutant forms G83A and T87V using molecular dynamics simulations in lipid environment. The free energy of dimerization has been estimated and the analysis of lipid properties was done. We propose different mechanisms for each mutation: T87V strongly changes protein-protein contacts. For G83A we demonstrate with the decomposition approach the major contribution of non-favorable protein-lipid contacts coupled with the redistribution interfacial protein-protein interactions. For monomers and dimers of all three forms of glycophorin A we found lipid binding sites near the interface of dimerization in the hydrophobic region of the bilayer. Surprisingly, in the case of monomers lipid acyl chains bind to the interfacial residues. Thus, the membrane plays an active role in dimer formation.
One of the key advances in genome assembly that has led to a significant improvement in contig lengths has been improved algorithms for utilization of paired reads (mate-pairs). While in most assemblers, mate-pair information is used in a post-processing step, the recently proposed Paired de Bruijn Graph (PDBG) approach incorporates the mate-pair information directly in the assembly graph structure. However, the PDBG approach faces difficulties when the variation in the insert sizes is high. To address this problem, we first transform mate-pairs into edge-pair histograms that allow one to better estimate the distance between edges in the assembly graph that represent regions linked by multiple mate-pairs. Further, we combine the ideas of mate-pair transformation and PDBGs to construct new data structures for genome assembly: pathsets and pathset graphs.
Many environmental stimuli present a quasi-rhythmic structure at different timescales that the brain needs to decompose and integrate. Cortical oscillations have been proposed as instruments of sensory de-multiplexing, i.e., the parallel processing of different frequency streams in sensory signals. Yet their causal role in such a process has never been demonstrated. Here, we used a neural microcircuit model to address whether coupled theta–gamma oscillations, as observed in human auditory cortex, could underpin the multiscale sensory analysis of speech. We show that, in continuous speech, theta oscillations can flexibly track the syllabic rhythm and temporally organize the phoneme-level response of gamma neurons into a code that enables syllable identification. The tracking of slow speech fluctuations by theta oscillations, and its coupling to gamma-spiking activity both appeared as critical features for accurate speech encoding. These results demonstrate that cortical oscillations can be a key instrument of speech de-multiplexing, parsing, and encoding.
Papers about natural protection territories
Neuronal nicotinic acetylcholine receptors (NNRs) of the α7 subtype have been shown to contribute to the release of dopamine in the nucleus accumbens. The site of action and the underlying mechanism, however, are unclear. Here we applied a circuit modeling approach, supported by electrochemical in vivo recordings, to clarify this issue. Modeling revealed two potential mechanisms for the drop in accumbal dopamine efflux evoked by the selective α7 partial agonist TC-7020. TC-7020 could desensitize α7 NNRs located predominantly on dopamine neurons or glutamatergic afferents to them or, alternatively, activate α7 NNRs located on the glutamatergic afferents to GABAergic interneurons in the ventral tegmental area. Only the model based on desensitization, however, was able to explain the neutralizing effect of coapplied PNU-120596, a positive allosteric modulator. According to our results, the most likely sites of action are the preterminal α7 NNRs controlling glutamate release from cortical afferents to the nucleus accumbens. These findings offer a rationale for the further investigation of α7 NNR agonists as therapy for diseases associated with enhanced mesolimbic dopaminergic tone, such as schizophrenia and addiction