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arXiv2014

Best of Both Worlds: Uniform sampling in Cartesian and Cayley Molecular Assembly Configuration Space

EASAL (efficient atlasing and sampling of assembly landscapes) is a recently reported geometric method for representing, visualizing, sampling and computing integrals over the potential energy landscape tailored for small molecular assemblies. EASAL's efficiency arises from the fact that small assembly landscapes permit the use of so-called Cayley parameters (inter-atomic distances) for geometric representation and sampling of the assembly configuration space regions; this results in their isolation, convexification, customized sampling and systematic traversal using a comprehensive topological roadmap, ensuring reasonable coverage of crucial but narrow regions of low effective dimension. However, this alone is inadequate for accurate computation of configurational entropy and other integrals, required for estimation of both free energy and kinetics - where it is essential to obtain uniform sampling in appropriate cartesian or moduli space parameterization. Standard adjustment of Cayley sampling via the Jacobian of the map between the two parameterizations is fraught with challenges stemming from an illconditioned Jacobian. This paper formalizes and analyzes these challenges to provide modifications to EASAL that secure the advantages of Cayley sampling while ensuring certain minimum distance and coverage relationships between sampled configurations - in Cartesian space. The modified EASAL's performance is compared with the basic EASAL and the data are presented for Human and Rat Islet Amylin Polypeptide (HiAPP, PDB-2KJ7 and RiAPP PDB-2KB8) dimerization (the two differ in only 6 out of 37 residues, but the former aggregates into fibrils, while the latter does not).

physics.chem-ph↗

arXiv2014

Nerves and Anesthesia: A physics perspective on medicine

We present a recent theory for nerve pulse propagation and anesthesia and argue that both nerve activity and the action of anesthetics can be understood on the basis of simple physical laws. It was found experimentally that biological membranes melt from a solid state to a liquid state just below physiological temperature. Such melting processes have a profound influence on the physical properties of cell membranes. They make it possible for mechanical pulses (solitons) to travel along nerve axons. In these pulses, a region of solid phase travels in the liquid nerve membrane. These pulses display many properties associated with the action potential in nerves. Both general and local anesthetics lower melting temperatures of membranes. Thus, they make it more difficult to excite the nerve membrane. Since hydrostatic pressure increases melting temperatures, it counteracts anesthesia. This theory has the virtue of providing a simple explanation of the famous Meyer-Overton correlation, which states that the effectiveness of an anesthetic is proportional to its solubility in the lipid membranes of cells. We offer evidence that this concept if also applicable to local anesthesia. Finally, we show that the presence of transitions has an influence on channel activity that can arise even in the absence of proteins.

physics.bio-ph↗

arXiv2014

Physiologically motivated multiplex Kuramoto model describes phase diagram of cortical activity

We derive a two-layer multiplex Kuramoto model from weakly coupled Wilson-Cowan oscillators on a cortical network with inhibitory synaptic time delays. Depending on the coupling strength and a phase shift parameter, related to cerebral blood flow and GABA concentration, respectively, we numerically identify three macroscopic phases: unsynchronized, synchronized, and chaotic dynamics. These correspond to physiological background-, epileptic seizure-, and resting-state cortical activity, respectively. We also observe frequency suppression at the transition from resting-state to seizure activity.

q-bio.NC↗

arXiv2014

Predictions of tertiary stuctures of $α$-helical membrane proteins by replica-exchange method with consideration of helix deformations

We propose an improved prediction method of the tertiary structures of $α$-helical membrane proteins based on the replica-exchange method by taking into account helix deformations. Our method allows wide applications because transmembrane helices of native membrane proteins are often distorted. In order to test the effectiveness of the present method, we applied it to the structure predictions of glycophorin A and phospholamban. The results were in accord with experiments.

q-bio.BM↗

arXiv2014

Remodeling of Fibrous Extracellular Matrices by Contractile Cells: Predictions from Discrete Fiber Network Simulations

Contractile forces exerted on the surrounding extracellular matrix (ECM) lead to the alignment and stretching of constituent fibers within the vicinity of cells. As a consequence, the matrix reorganizes to form thick bundles of aligned fibers that enable force transmission over distances larger than the size of the cells. Contractile force-mediated remodeling of ECM fibers has bearing on a number of physiologic and pathophysiologic phenomena. In this work, we present a computational model to capture cell-mediated remodeling within fibrous matrices using finite element based discrete fiber network simulations. The model is shown to accurately capture collagen alignment, heterogeneous deformations, and long-range force transmission observed experimentally. The zone of mechanical influence surrounding a single contractile cell and the interaction between two cells are predicted from the strain-induced alignment of fibers. Through parametric studies, the effect of cell contractility and cell shape anisotropy on matrix remodeling and force transmission are quantified and summarized in a phase diagram. For highly contractile and elongated cells, we find a sensing distance that is ten times the cell size, in agreement with experimental observations.

q-bio.CB↗

arXiv2015

Alignment of cryo-EM movies of individual particles by optimization of image translations

Direct detector device (DDD) cameras have revolutionized single particle electron cryomicroscopy (cryo-EM). In addition to an improved camera detective quantum efficiency, acquisition of DDD movies allows for correction of movement of the specimen, due both to instabilities in the microscope specimen stage and electron beam-induced movement. Unlike specimen stage drift, beam-induced movement is not always homogeneous within an image. Local correlation in the trajectories of nearby particles suggests that beam-induced motion is due to deformation of the ice layer. Algorithms have already been described that can correct movement for large regions of frames and for > 1 MDa protein particles. Another algorithm allows individual < 1 MDa protein particle trajectories to be estimated, but requires rolling averages to be calculated from frames and fits linear trajectories for particles. Here we describe an algorithm that allows for individual < 1 MDa particle images to be aligned without frame averaging or linear trajectories. The algorithm maximizes the overall correlation of the shifted frames with the sum of the shifted frames. The optimum in this single objective function is found efficiently by making use of analytically calculated derivatives of the function. To smooth estimates of particle trajectories, rapid changes in particle positions between frames are penalized in the objective function and weighted averaging of nearby trajectories ensures local correlation in trajectories. This individual particle motion correction, in combination with weighting of Fourier components to account for increasing radiation damage in later frames, can be used to improve 3-D maps from single particle cryo-EM.

q-bio.QM↗

arXiv2017

Swarming collapse under limited information flow between individuals

The emergence of collective decision in swarms and their coordinated response to complex environments underscore the central role played by social transmission of information. Here, the different possible origins of information flow bottlenecks are identified. Using a combination of network-, control- and information-theoretic elements applied to a group of interacting self-propelled particles, the effect of varying information capacity of the signaling channel on dynamic collective behaviors is revealed. We find a sufficient condition on the information data rate that guarantees the effectiveness of swarming while also highlighting the profound connection with the topology of the underlying interaction network. We also show that when decreasing the data rate, the swarming behavior invariably vanishes following a second-order phase transition irrespective of the intrinsic noise level. The variations along the transition line are found to be in good agreement with information-theoretic predictions.

nlin.AO↗

arXiv2014

Why so many sperm cells?

A key limiting step in fertility is the search for the oocyte by spermatozoa. Initially, there are tens of millions of sperm cells, but a single one will make it to the oocyte. This may be one of the most severe selection processes designed by evolution, whose role is yet to be understood. Why is it that such a huge redundancy is required and what does that mean for the search process? we propose to discuss here these questions and consequently a new line of interdisciplinary research needed to find possible answers.

q-bio.CB↗

arXiv2014

Modeling sequence-specific polymers using anisotropic coarse-grained sites allows quantitative comparison with experiment

Certain sequences of peptoid polymers (synthetic analogs of peptides) assemble into bilayer nanosheets via a nonequilibrium assembly pathway of adsorption, compression, and collapse at an air-water interface. As with other large-scale dynamic processes in biology and materials science, understanding the details of this supramolecular assembly process requires a modeling approach that captures behavior on a wide range of length and time scales, from those on which individual sidechains fluctuate to those on which assemblies of polymers evolve. Here we demonstrate that a new coarse-grained modeling approach is accurate and computationally efficient enough to do so. Our approach uses only a minimal number of coarse-grained sites, but retains independently fluctuating orientational degrees of freedom for each site. These orientational degrees of freedom allow us to accurately parameterize both bonded and nonbonded interactions, and to generate all-atom configurations with sufficient accuracy to perform atomic scattering calculations and to interface with all-atom simulations. We have used this approach to reproduce all available experimental X-ray scattering spectra (for stacked nanosheets, and for peptoids adsorbed at air-water interfaces and in solution), in order to resolve the microscopic, real-space structures responsible for these Fourier-space features. By interfacing with all-atom simulations, we have also laid the foundations for future multiscale simulations of sequence-specific polymers that communicate in both directions across scales.

physics.bio-ph↗

arXiv2014

Hydrodynamical random walker with chemotactic memory

A three-dimensional hydrodynamical model for a micro random walker is combined with the idea of chemotactic signaling network of E. coli. Diffusion exponents, orientational correlation functions and their dependence on the geometrical and dynamical parameters of the system are analyzed numerically. Because of the chemotactic memory, the walker shows superdiffusing displacements in all directions with the largest diffusion exponent for a direction along the food gradient. Mean square displacements and orientational correlation functions show that the chemotactic memory washes out all the signatures due to the geometrical asymmetry of the walker and statistical properties are asymmetric only with respect to the direction of food gradient. For different values of the memory time, the Chemotactic index (CI) is also calculated.

cond-mat.soft↗

arXiv2014

How the active and diffusional nature of brain tissues can generate monopole signals at micrometer sized measures

We investigate mechanisms which could generate transient monopole signals in measuring current source density (CSD), as it had been indicated to occur in recent small volume experiments. A simple model is defined for this purpose. It is emphasized that the active nature of the neural biological activity, with its ability to generate ionic density imbalances, might be able to induce appreciable monopole signals in CSD detectors at micrometer scales. Thus, it follows that when both diffusive and ohmic transport are considered to be present in neural tissues, potential measures in micrometer regions can include appreciable electric monopole signals, for sufficiently small values of the ratio (σa^{2})/(εD), where "σ" is the conductivity, "ε" is the dielectric constant, "D" is the diffusion constant and "a" is the linear dimension of the ionic charge densities generated by the neural processes. Ranges of possible magnitudes for these parameters in the considered experimental studies are estimated. The analysis indicates values for the ratio between the dipolar and monopole signals which are close to the ones measured in Pyramidal cells in recent experiments. The measured results for Spiny Stellate cells are also qualitatively described by the model by predicting a finite monopole signal in combination with vanishing dipolar and quadrupole ones.

physics.bio-ph↗

arXiv2014

Using Simulations and kinetic network models to reveal the dynamics and functions of Riboswitches

Riboswitches, RNA elements found in the untranslated region, regulate gene expression by binding to target metaboloites with exquisite specificity. Binding of metabolites to the conserved aptamer domain allosterically alters the conformation in the downstream expression platform. The fate of gene expression is determined by the changes in the downstream RNA sequence. As the metabolite-dependent cotranscriptional folding and unfolding dynamics of riboswitches is the key determinant of gene expression, it is important to investigate both the thermodynamics and kinetics of riboswitches both in the presence and absence of metabolite. Single molecule force experiments that decipher the free energy landscape of riboswitches from their mechanical responses, theoretical and computational studies have recently shed light on the distinct mechanism of folding dynamics in different classes of riboswitches. Here we first discuss the dynamics of water around riboswitch, highlighting that water dynamics can enhance the fluctuation of nucleic acid structure. To go beyond native state fluctuations we used the Self-Organized Polymer (SOP) model to predict the dynamics of add adenine riboswitch under mechanical forces. In addition to quantitatively predicting the folding landscape of add-riboswitch our simulations also explain the difference in the dynamics between pbuE adenine- and add adenine-riboswitches. In order to probe the function {\it in vivo} we use the folding landscape to propose a system level kinetic network model to quantitatively predict how gene expression is regulated for riboswitches that are under kinetic control.

q-bio.BM↗

arXiv2016

A physical model for dementia

Aging associated brain decline often result in some kind of dementia. Even when this is a complex brain disorder a physical model can be used in order to describe its general behavior. This model is based in first principles. A probabilistic model for the development of dementia is obtained and fitted to some experimental data obtained from the Alzheimer's Disease Neuroimaging Initiative. It is explained how dementia appears as a consequence of aging and why it is irreversible.

q-bio.NC↗

arXiv2014

The unknotted strands of life: knots are very rare in RNA structures

The ongoing effort to detect and characterize physical entanglement in biopolymers has so far established that knots are present in many globular proteins and also abound in viral DNA packaged inside bacteriophages. RNA molecules, on the other hand, have not yet been systematically screened for the occurrence of physical knots. We have accordingly undertaken the systematic profiling of the ~6,000 RNA structures present in the protein data bank. The search identified no more than three deeply-knotted RNA molecules. These are ribosomal RNAs solved by cryo-em and consist of about 3,000 nucleotides. Compared to the case of proteins and viral DNA, the observed incidence of RNA knots is therefore practically negligible. This suggests that either evolutionary selection, or thermodynamic and kinetic folding mechanisms act towards minimizing the entanglement of RNA to an extent that is unparalleled by other types of biomolecules. The properties of the three observed RNA knotting patterns provide valuable clues for designing RNA sequences capable of self-tying in a twist-knot fold.

q-bio.BM↗

arXiv2014

Cellular Uptake and Biocompatibility of Bismuth Ferrite Harmonic Advanced Nanoparticles

Bismuth Ferrite (BFO) nanoparticles (BFO-NP) display interesting optical (nonlinear response) and magnetic properties which make them amenable for bio-oriented applications as intra- and extra membrane contrast agents. Due to the relatively recent availability of this material in well dispersed nanometric form, its biocompatibility was not known to date. In this study, we present a thorough assessment of the effects of in vitro exposure of human adenocarcinoma (A549), lung squamous carcinoma (NCI-H520), and acute monocytic leukemia (THP-1) cell lines to uncoated and poly(ethylene glycol)-coated BFO-NP in the form of cytotoxicity, haemolytic response and biocompatibility. Our results support the attractiveness of the functional-BFO towards biomedical applications focused on advanced diagnostic imaging.

q-bio.CB↗

arXiv2014

Conservation of writhe helicity under anti-parallel reconnection

Reconnection is a fundamental event in many areas of science, from the interaction of vortices in classical and quantum fluids, and magnetic flux tubes in magnetohydrodynamics and plasma physics, to the recombination in polymer physics and DNA biology. By using fundamental results in topological fluid mechanics, the helicity of a flux tube can be calculated in terms of writhe and twist contributions. Here we show that the writhe is conserved under anti-parallel reconnection. Hence, for a pair of interacting flux tubes of equal flux, if the twist of the reconnected tube is the sum of the original twists of the interacting tubes, then helicity is conserved during reconnection. Thus, any deviation from helicity conservation is entirely due to the intrinsic twist inserted or deleted locally at the reconnection site. This result has important implications for helicity and energy considerations in various physical contexts.

math-ph↗

arXiv2016

Network reconstruction by the stationary distribution of random walk process

It is known that the stationary distribution of the random walk process is dependent on the structure of the network. This could provide us a solution of the network reconstruction. However, the stationary distribution of the random walk process can only reflect the relative size of node degrees directly, how to infer the real connection is still a problem. In this paper, we will propose a method to reconstruct network by the random walk process, which can reconstruct the total number of links, degree sequence and links sequentially. In our method, only the stationary distribution is used, and no data of the evolution process is needed, such as the first passage time. We perform our method on some network models and real-world network, the results indicate our method can reconstruct networks accurately, even when we can not get the exact stationary distribution.

physics.soc-ph↗

arXiv2014

Open chemical reaction networks, steady-state loads and Braess-like paradox

Open chemical reaction systems involve matter-exchange with the surroundings. As a result, species can accumulate inside a system during the course of the reaction. We study the role of network topology in governing the concentration build-up inside a fixed reaction volume at steady state, particularly focusing on the effect of additional paths. The problem is akin to that in traffic networks where an extra route, surprisingly, can increase the overall travel time. This is known as the Braess' paradox. Here, we report chemical analogues of such a paradox in suitably chosen reaction networks, where extra reaction step(s) can inflate the total concentration, denoted as `load', at steady state. It is shown that, such counter-intuitive behavior emerges in a qualitatively similar pattern in networks of varying complexities. We then explore how such extra routes affect the load in a biochemical scheme of uric acid degradation. From a thorough analysis of this network, we propose a functional role of some decomposition steps that can trim the load, indicating the importance of the latter in the evolution of reaction mechanisms in living matter.

physics.chem-ph↗