The ability of mononuclear dinitrosyl iron commplexes (M-DNICs) with thiolate ligands to act as NO donors and to trigger S-nitrosation of thiols can be explain only in the paradigm of the model of the [Fe+(NO+)2] core ({Fe(NO)2}7 according to the Enemark-Feltham classification). Similarly, the {(RS−)2Fe+(NO+)2}+ structure describing the distribution of unpaired electron density in M-DNIC corresponds to the low-spin (<svg style="vertical-align:-2.22495pt;width:51.025002px;" id="M1" height="14.85" version="1.1" viewBox="0 0 51.025002 14.85" width="51.025002" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"><g transform="matrix(.017,-0,0,-.017,.062,12.012)"><path id="x1D446" d="M457 488l-30 -3q-17 148 -131 148q-53 0 -84.5 -34.5t-31.5 -82.5q0 -42 25.5 -72t74.5 -62l33 -22q63 -42 95 -85t32 -102q0 -84 -67 -137t-163 -53q-58 0 -113 22t-70 43l-4 152l27 4q4 -32 15 -62.5t31 -59.5t53.5 -47t76.5 -18q56 0 92 35t36 96q0 39 -25 70t-78 68&#xA;l-31 22q-32 23 -53.5 41.5t-45 57t-23.5 77.5q0 82 58 132.5t156 50.5q46 0 101 -17l18.5 -6t17 -6t8.5 -3q-4 -55 0 -147z" /></g><g transform="matrix(.017,-0,0,-.017,12.931,12.012)"><path id="x3D" d="M535 323h-483v50h483v-50zM535 138h-483v50h483v-50z" /></g><g transform="matrix(.017,-0,0,-.017,27.634,12.012)"><path id="x31" d="M384 0h-275v27q67 5 81.5 18.5t14.5 68.5v385q0 38 -7.5 47.5t-40.5 10.5l-48 2v24q85 15 178 52v-521q0 -55 14.5 -68.5t82.5 -18.5v-27z" /></g><g transform="matrix(.017,-0,0,-.017,35.794,12.012)"><path id="x2F" d="M368 703l-264 -866h-60l265 866h59z" /></g><g transform="matrix(.017,-0,0,-.017,42.797,12.012)"><path id="x32" d="M412 140l28 -9q0 -2 -35 -131h-373v23q112 112 161 170q59 70 92 127t33 115q0 63 -31 98t-86 35q-75 0 -137 -93l-22 20l57 81q55 59 135 59q69 0 118.5 -46.5t49.5 -122.5q0 -62 -29.5 -114t-102.5 -130l-141 -149h186q42 0 58.5 10.5t38.5 56.5z" /></g></svg>) state with a d7 electron configuration of the iron atom and predominant localization of the unpaired electron on MO(<svg style="vertical-align:-3.27605pt;width:20.4375px;" id="M2" height="16.3125" version="1.1" viewBox="0 0 20.4375 16.3125" width="20.4375" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"><g transform="matrix(.017,-0,0,-.017,.062,12.162)"><path id="x64" d="M517 51v-25q-101 -18 -155 -38v65l-61 -36q-50 -29 -78 -29q-68 0 -126.5 58t-58.5 155q0 103 77 175.5t180 72.5q36 0 67 -12v143q0 48 -11.5 58.5t-65.5 14.5v25q79 9 156 34v-597q0 -38 7.5 -48t36.5 -13zM362 85v275q-35 51 -103 51q-20 0 -40.5 -8.5t-42 -28&#xA;t-35 -57.5t-13.5 -89q0 -83 42 -130t96 -47q51 0 96 34z" /></g><g transform="matrix(.012,-0,0,-.012,9.038,16.25)"><path id="x7A" d="M387 138l26 -13l-46 -125h-329l-7 15q109 161 249 388h-89q-52 0 -71.5 -13.5t-41.5 -57.5l-14 -27l-25 9q20 70 34 144h21q8 -21 55 -21h230l6 -14l-244 -390h99q54 0 78.5 16.5t55.5 64.5z" /></g><g transform="matrix(.012,-0,0,-.012,14.037,16.25)"><use xlink:href="#x32" /></g></svg>) and the square planar structure of M-DNIC. On the other side, the formation of molecular orbitals of M-DNIC including orbitals of the iron atom, thiolate and nitrosyl ligands results in a transfer of electron density from sulfur atoms to the iron atom and nitrosyl ligands. Under these conditions, the positive charge on the nitrosyl ligands diminishes appreciably, the interaction of the ligands with hydroxyl ions or with thiols slows down and the hydrolysis of nitrosyl ligands and the S-nitrosating effect of the latter are not manifested. Most probably, the S-nitrosating effect of nitrosyl ligands is a result of weak binding of thiolate ligands to the iron atom under conditions favoring destabilization of M-DNIC.

Anatoly F. Vanin

Dosymzhan Sh. Burbaev

Electronic and Spatial Structures of Water-Soluble Dinitrosyl Iron Complexes with Thiol-Containing Ligands Underlying Their Ability to Act as Nitric Oxide and Nitrosonium Ion Donors

To explore the fundamental biomechanics of sound frequency transduction in the cochlea, a two-dimensional analytical model of the basilar membrane was constructed from first principles. Quantitative analysis showed that axial forces along the membrane are negligible, condensing the problem to a set of ordered one-dimensional models in the radial dimension, for which all parameters can be specified from experimental data. Solutions of the radial models for asymmetrical boundary conditions produce realistic deformation patterns. The resulting second-order differential equations, based on the original concepts of Helmholtz and Guyton, and including viscoelastic restoring forces, predict a frequency map and amplitudes of deflections that are consistent with classical observations. They also predict the effects of an observation hole drilled in the surrounding bone, the effects of curvature of the cochlear spiral, as well as apparent traveling waves under a variety of experimental conditions. A quantitative rendition of the classical Helmholtz-Guyton model captures the essence of cochlear mechanics and unifies the competing resonance and traveling wave theories.

Charles F. Babbs

Quantitative  Reappraisal  of the Helmholtz-Guyton Resonance Theory of Frequency Tuning in the Cochlea

The baseplate subantenna in chlorosomes of green anoxygenic photosynthetic bacteria, belonging to the families Chloroflexaceae and Chlorobiaceae, is known to represent a complex of bacteriochlorophyll (BChl) a with the ~6 kDa CsmA proteins. Earlier, we showed the existence of a similar BChl a subantenna in chlorosomes of the photosynthetic green bacterium Oscillochloris trichoides, member of Oscillochloridaceae, the third family of green photosynthetic bacteria. However, this BChl a subantenna was not visually identified in absorption spectra of isolated Osc. trichoides chlorosomes in contrast to those of Chloroflexaceae and Chlorobiaceae. In this work, using room and low-temperature absorbance and fluorescence spectroscopy and sodium dodecyl sulfate polyacrylamide gel electrophoresis analysis of alkaline-treated and untreated chlorosomes of Osc. trichoides, we showed that the baseplate BChl a subantenna does exist in Oscillochloridaceae chlorosomes as a complex of BChl a with the 5.7 kDa CsmA protein. The present results support the idea that the baseplate subantenna, representing a complex of BChl a with a ~6 kDa CsmA protein, is a universal interface between the BChl c subantenna of chlorosomes and the nearest light-harvesting BChl a subantenna in all three known families of green anoxygenic photosynthetic bacteria.

Anastasiya Zobova

Alexandra Taisova

Eugeny Lukashev

Nataliya Fedorova

Ludmila Baratova

Zoya Fetisova

CsmA Protein is Associated with BChl a in the Baseplate Subantenna of Chlorosomes of the Photosynthetic Green Filamentous Bacterium Oscillochloris trichoides belonging to the Family Oscillochloridaceae

Reducing a feature vector to an optimized dimensionality is a common problem in biomedical signal analysis. This analysis retrieves the characteristics of the time series and its associated measures with an adequate methodology followed by an appropriate statistical assessment of these measures (e.g., spectral power or fractal dimension). As a step towards such a statistical assessment, we present a data resampling approach. The techniques allow estimating <svg style="vertical-align:-2.3205pt;width:38.400002px;" id="M1" height="18.725" version="1.1" viewBox="0 0 38.400002 18.725" width="38.400002" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"><g transform="matrix(.017,-0,0,-.017,.062,15.775)"><path id="x1D70E" d="M548 455q-32 -77 -74 -77q-37 0 -103 10l-3 -2q36 -30 48.5 -62t12.5 -80q0 -103 -75 -179.5t-175 -76.5q-70 0 -113 45t-43 128q0 115 83.5 200.5t209.5 85.5q31 0 77.5 -4t67.5 -4q36 0 62 30zM350 274q0 54 -17 86q-19 35 -57 35q-50 0 -90 -37.5t-59 -91.5t-19 -109&#xA;q0 -61 24.5 -96.5t65.5 -35.5q51 0 87.5 46.5t50.5 100.5t14 102z" /></g><g transform="matrix(.012,-0,0,-.012,9.663,7.613)"><path id="x32" d="M412 140l28 -9q0 -2 -35 -131h-373v23q112 112 161 170q59 70 92 127t33 115q0 63 -31 98t-86 35q-75 0 -137 -93l-22 20l57 81q55 59 135 59q69 0 118.5 -46.5t49.5 -122.5q0 -62 -29.5 -114t-102.5 -130l-141 -149h186q42 0 58.5 10.5t38.5 56.5z" /></g><g transform="matrix(.017,-0,0,-.017,16,15.775)"><path id="x28" d="M300 -147l-18 -23q-106 71 -159 185.5t-53 254.5v1q0 139 53 252.5t159 186.5l18 -24q-74 -62 -115.5 -173.5t-41.5 -242.5q0 -130 41.5 -242.5t115.5 -174.5z" /></g><g transform="matrix(.017,-0,0,-.017,21.882,15.775)"><path id="x1D439" d="M599 650l-18 -160l-30 -2q-2 70 -11 94q-5 16 -26 24t-75 8h-94q-27 0 -33.5 -6.5t-12.5 -32.5l-43 -226h108q52 0 72.5 5t31 18t28.5 52h28l-40 -200h-28q-1 42 -6 56.5t-24.5 21t-70.5 6.5h-108l-32 -177q-13 -65 1 -80.5t88 -22.5l-8 -28h-279l6 28q61 5 77.5 20.5&#xA;t29.5 81.5l72 387l7.5 40.5t1 26.5t-4 18t-15.5 10t-24 6t-37 4l8 28h461z" /></g><g transform="matrix(.017,-0,0,-.017,32.455,15.775)"><path id="x29" d="M275 270q0 -296 -211 -440l-19 23q75 62 116.5 174t41.5 243t-42 243t-116 173l19 24q211 -144 211 -440z" /></g></svg>, that is, the variance of an F-value from variance analysis. Three test statistics are derived from the so-called F-ratio <svg style="vertical-align:-2.3205pt;width:62.3125px;" id="M2" height="18.725" version="1.1" viewBox="0 0 62.3125 18.725" width="62.3125" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"><g transform="matrix(.017,-0,0,-.017,.062,15.775)"><use xlink:href="#x1D70E" /></g><g transform="matrix(.012,-0,0,-.012,9.663,7.613)"><use xlink:href="#x32" /></g><g transform="matrix(.017,-0,0,-.017,16,15.775)"><use xlink:href="#x28" /></g><g transform="matrix(.017,-0,0,-.017,21.882,15.775)"><use xlink:href="#x1D439" /></g><g transform="matrix(.017,-0,0,-.017,32.455,15.775)"><use xlink:href="#x29" /></g><g transform="matrix(.017,-0,0,-.017,38.336,15.775)"><path id="x2F" d="M368 703l-264 -866h-60l265 866h59z" /></g><g transform="matrix(.017,-0,0,-.017,45.34,15.775)"><use xlink:href="#x1D439" /></g><g transform="matrix(.012,-0,0,-.012,55.913,7.613)"><use xlink:href="#x32" /></g></svg>. A Bayesian formalism assigns weights to hypotheses and their corresponding measures considered (hypothesis weighting). This leads to complete, partial, or noninclusion of these measures into an optimized feature vector. We thus distinguished the EEG of healthy probands from the EEG of patients diagnosed as schizophrenic. A reliable discriminance performance of 81% based on Taken's χ, <svg style="vertical-align:-0.1638pt;width:9.7749996px;" id="M3" height="7.9499998" version="1.1" viewBox="0 0 9.7749996 7.9499998" width="9.7749996" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"><g transform="matrix(.017,-0,0,-.017,.062,7.675)"><path id="x1D6FC" d="M545 106q-67 -118 -134 -118q-24 0 -40 37.5t-30 129.5h-2q-47 -72 -103 -119.5t-108 -47.5q-47 0 -76 45.5t-29 119.5q0 113 85 204t174 91q47 0 70 -33.5t43 -119.5h3q32 47 80 140l55 13l10 -9q-47 -80 -138 -201q17 -99 27.5 -136t22.5 -37q23 0 69 61zM333 204&#xA;q-14 98 -31 149.5t-50 51.5q-49 0 -94 -70t-45 -164q0 -55 15.5 -86t40.5 -31q70 0 164 150z" /></g></svg>-, and <svg style="vertical-align:-0.1638pt;width:8.9125004px;" id="M4" height="12.4375" version="1.1" viewBox="0 0 8.9125004 12.4375" width="8.9125004" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"><g transform="matrix(.017,-0,0,-.017,.062,12.162)"><path id="x1D6FF" d="M494 514l-10 -15q-56 76 -106.5 117t-110.5 41q-45 0 -45 -30q0 -28 109 -152q59 -68 86 -118.5t27 -107.5q0 -62 -29.5 -119.5t-86.5 -96.5q-64 -45 -138 -45q-76 0 -121.5 53t-45.5 136q0 74 40.5 135t98.5 95q43 26 87 42q-40 59 -57.5 92t-17.5 62q0 46 39 77.5&#xA;t90 31.5q54 0 97.5 -35.5t65 -78.5t28.5 -84zM359 234q0 84 -90 191q-47 -17 -74 -47q-81 -89 -81 -200q0 -71 32.5 -109.5t72.5 -38.5q47 0 80 33t46.5 77.5t13.5 93.5z" /></g></svg>-power was found.

R. M. D&#xFC;nki

M. Dressel

F-Ratio Test and Hypothesis Weighting: A Methodology to Optimize Feature Vector Size


		Recently, much attention has been given to the problem of drug delivery through the cell-membrane in order to treat and manage several diseases. The discovery of cell penetrating peptides (CPPs) represents a major breakthrough for the transport of large-cargo molecules that may be useful in clinical applications. CPPs are rich in basic amino acids such as arginine and lysine and are able to translocate over membranes and gain access to the cell interior. They can deliver large-cargo molecules, such as oligonucleotides, into cells. Endocytosis and direct penetration have been suggested as the two major uptake mechanisms, a subject still under debate. Unresolved questions include the detailed molecular uptake mechanism(s), reasons for cell toxicity, and the delivery efficiency of CPPs for different cargoes. Here, we give a review focused on uptake mechanisms used by CPPs for membrane translocation and certain experimental factors that affect the mechanism(s).

Fatemeh Madani

Staffan Lindberg

&#220;lo Langel

Shiroh Futaki

Astrid Gr&#228;slund

Mechanisms of Cellular Uptake of Cell-Penetrating Peptides

We examined tRNA flexibility using a combination of steered and unbiased molecular dynamics simulations. Using Maxwell&#39;s demon algorithm, molecular dynamics was used to steer X-ray structure data toward that from an alternative state obtained from cryogenic-electron microscopy density maps. Thus, we were able to fit X-ray structures of tRNA onto cryogenic-electron microscopy density maps for hybrid states of tRNA. Additionally, we employed both Maxwell&#39;s demon molecular dynamics simulations and unbiased simulation methods to identify possible ribosome-tRNA contact areas where the ribosome may discriminate tRNAs during translation. Herein, we collected &#62;500&#x2009;ns of simulation data to assess the global range of motion for tRNAs. Biased simulations can be used to steer between known conformational stop points, while unbiased simulations allow for a general testing of conformational space previously unexplored. The unbiased molecular dynamics data describes the global conformational changes of tRNA on a sub-microsecond time scale for comparison with steered data. Additionally, the unbiased molecular dynamics data was used to identify putative contacts between tRNA and the ribosome during the accommodation step of translation. We found that the primary contact regions were H71 and H92 of the 50S subunit and ribosomal proteins L14 and L16.

Thomas R. Caulfield

Batsal Devkota

Geoffrey C. Rollins

Examinations of tRNA Range of Motion Using Simulations of Cryo-EM Microscopy and X-Ray Data

The mathematical model of the operation of the first enzyme of the Escherichia coli phosphotransferase system, EI, is proposed. Parameters of the kinetic model describing the operation of EI under different conditions are identified on the basis of a large amount of known experimental data. The verified model is employed to predict modes of operation of EI under both in vivo physiological conditions and in vitro nonphysiological conditions. The model predicts that under in vivo physiological conditions, the rate of phosphotransfer from EI to the second protein of the phosphotransferase system HPr by the dimer is much higher than by the monomer. A hypothesis is proposed on the basis of calculations that the transfer by a monomer plays a role in the regulation of chemotaxis. At submicromolar pyruvate concentration, the model predicts nonmonotonic dependence of the phosphotransfer rate on the substrate (PEP) concentration.

T. A. Karelina

H. Ma

I. Goryanin

O. V. Demin

EI of the Phosphotransferase System of Escherichia coli: Mathematical Modeling Approach to Analysis of Its Kinetic Properties

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Journal of Biophysics