Theoretical Studies of Structure-Function Relationships in Kv Channels: Electrostatics of the Voltage Sensor

Voltage-gated ion channels mediate electrical excitability of cellular membranes. Reduced models of the voltage sensor (VS) of Kv channels produce insight into the electrostatic physics underlying the response of the highly positively charged S4 transmembrane domain to changes in membrane potential and other electrostatic parameters. By calculating the partition function computed from the electrostatic energy over translational and/or rotational degrees of freedom, I compute expectations of charge displacement, energetics, probability distributions of translation & rotation and Maxwell stress for arrangements of S4 positively charged residues; these computations can then be compared with experimental results to elucidate the role of various putative atomic level features of the VS. A `paddle' model is rejected on electrostatic grounds, owing to unfavorable energetics, insufficient charge displacement and excessive Maxwell stress. On the other hand, a `sliding helix' model with three local counter-charges, a protein dielectric coefficient of 4 and a 2/3 interval of counter-charge positioning relative to the S4-helix period of positive residues is electrostatically reasonable, comparing well with Shaker (Seoh et al., 1996). Lack of counter-charges destabilizes the S4 in the membrane; counter-charge interval helps determine the number and shape of energy barriers and troughs over the range of motion of the S4; and the local dielectric coefficient of the protein constrains the height of energy maxima. These `sliding helix' models compare favorably with experimental results for single & double mutant charge experiments on Shaker. Single S4 positive charge mutants are predicted quite well by this model; single counter-charge mutants are predicted less well; and double mutants for both an S4 charge and a counter-charge are characterized least well

Voltage sensing in ion channels: Mesoscale simulations of biological devices

Electrical signaling via voltage-gated ion channels depends upon the function of a voltage sensor (VS), identified with the S1-S4 domain in voltage-gated K+ channels. Here we investigate some energetic aspects of the sliding-helix model of the VS using simulations based on VS charges, linear dielectrics and whole-body motion. Model electrostatics in voltage-clamped boundary conditions are solved using a boundary element method. The statistical mechanical consequences of the electrostatic configurational energy are computed to gain insight into the sliding-helix mechanism and to predict experimentally measured ensemble properties such as gating charge displaced by an applied voltage. Those consequences and ensemble properties are investigated for two alternate S4 configurations, \alpha- and 3(10)-helical. Both forms of VS are found to have an inherent electrostatic stability. Maximal charge displacement is limited by geometry, specifically the range of movement where S4 charges and counter-charges overlap in the region of weak dielectric. Charge displacement responds more steeply to voltage in the \alpha-helical than the 3(10)-helical sensor. This difference is due to differences on the order of 0.1 eV in the landscapes of electrostatic energy. As a step toward integrating these VS models into a full-channel model, we include a hypothetical external load in the Hamiltonian of the system and analyze the energetic in/output relation of the VS.Comment: arXiv admin note: substantial text overlap with arXiv:1112.299

Virtual Connectome: Discovering therelationship between structural and functionalconnectivity during steady-states andtransitions

The Virtual Connectome project is a new collaboration between the Charité Universitätsmedizin Berlin, the Indiana University Network Science Institute and the Neuroscience SimLab, JSC, Forschungszentrum Jülich.The main goal of the project is to understand the relationship between structural and functional connectivity in the human brain.Experimental and simulated data of many subjects over long time spans will be analyzed and compared to identify the particular structural connectivity and brain model parameters which better predict the brain activity of the each individual.This presentation aims at providing a general introduction to the project and highlight current work which would benefit from collaborations with mathematicians in order to:1.Understand the capabilities of a Dynamic Mean Field Model of Neural Networks to model transitions between different dynamic states, and refine the model in order to better predict these states.2.Understand the role of the inner inhibition in this Dynamic Mean Field Model in order to obtain a simplified expression which depends on the strength of the inputs to a brain region

Arbor -- a morphologically-detailed neural network simulation library for contemporary high-performance computing architectures

We introduce Arbor, a performance portable library for simulation of large networks of multi-compartment neurons on HPC systems. Arbor is open source software, developed under the auspices of the HBP. The performance portability is by virtue of back-end specific optimizations for x86 multicore, Intel KNL, and NVIDIA GPUs. When coupled with low memory overheads, these optimizations make Arbor an order of magnitude faster than the most widely-used comparable simulation software. The single-node performance can be scaled out to run very large models at extreme scale with efficient weak scaling. HPC, GPU, neuroscience, neuron, softwareComment: PDP 2019 27th Euromicro International Conference on Parallel, Distributed and Network-based Processin

Neutral and Charged Polymers at Interfaces

Chain-like macromolecules (polymers) show characteristic adsorption properties due to their flexibility and internal degrees of freedom, when attracted to surfaces and interfaces. In this review we discuss concepts and features that are relevant to the adsorption of neutral and charged polymers at equilibrium, including the type of polymer/surface interaction, the solvent quality, the characteristics of the surface, and the polymer structure. We pay special attention to the case of charged polymers (polyelectrolytes) that have a special importance due to their water solubility. We present a summary of recent progress in this rapidly evolving field. Because many experimental studies are performed with rather stiff biopolymers, we discuss in detail the case of semi-flexible polymers in addition to flexible ones. We first review the behavior of neutral and charged chains in solution. Then, the adsorption of a single polymer chain is considered. Next, the adsorption and depletion processes in the many-chain case are reviewed. Profiles, changes in the surface tension and polymer surface excess are presented. Mean-field and corrections due to fluctuations and lateral correlations are discussed. The force of interaction between two adsorbed layers, which is important in understanding colloidal stability, is characterized. The behavior of grafted polymers is also reviewed, both for neutral and charged polymer brushes.Comment: a review: 130 pages, 30 ps figures; final form, added reference

Mosaic Chromosomal alterations in Blood across ancestries Using Whole-Genome Sequencing

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis

Association Between Whole Blood-Derived Mitochondrial Dna Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia)