SEARCH · Searcharxiv

Results for “q-bio”

Search indexed arXiv papers on artificial intelligence, large language models, computer vision and robotics. Read source abstracts and follow links to arXiv.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 955 records · Page 53Linked to original sources

arXiv1999

Protein folding using contact maps

We present the development of the idea to use dynamics in the space of contact maps as a computational approach to the protein folding problem. We first introduce two important technical ingredients, the reconstruction of a three dimensional conformation from a contact map and the Monte Carlo dynamics in contact map space. We then discuss two approximations to the free energy of the contact maps and a method to derive energy parameters based on perceptron learning. Finally we present results, first for predictions based on threading and then for energy minimization of crambin and of a set of 6 immunoglobulins. The main result is that we proved that the two simple approximations we studied for the free energy are not suitable for protein folding. Perspectives are discussed in the last section.

cond-mat.soft↗

arXiv1998

An Oscillator Neural Network Retrieving Sparsely Coded Phase Patterns

Little is known theoretically about the associative memory capabilities of neural networks in which information is encoded not only in the mean firing rate but also in the timing of firings. Particularly, in the case that the fraction of active neurons involved in memorizing patterns becomes small, it is biologically important to consider the timings of firings and to study how such consideration influences storage capacities and quality of recalled patterns. For this purpose, we propose a simple extended model of oscillator neural networks to allow for expression of non-firing state. %which is able to memorize sparsely coded phase patterns including non-firing states. Analyzing both equilibrium states and dynamical properties in recalling processes, we find that the system possesses good associative memory.

cond-mat.dis-nn↗

arXiv1999

Multi-Self-Overlap Ensemble for protein folding: ground state search and thermodynamics

Long chains of the HP lattice protein model are studied by the Multi-Self-Overlap Ensemble(MSOE) Monte Carlo method, which was developed recently by the authors. MSOE successfully finds the lowest energy states reported before for sequences of the chain length $N=42\sim 100$ in two and three dimensions. Moreover, MSOE realizes the lowest energy state that ever found in a case of N=100. Finite-temperature properties of these sequences are also investigated by MSOE. Two successive transitions are observed between the native and random coil states. Thermodynamic analysis suggests that the ground state degeneracy is relevant to the order of the transitions in the HP model.

cond-mat.soft↗

arXiv1999

Coiling of Cylindrical Membrane Stacks with Anchored Polymers

We study experimentally a coiling instability of cylindrical multilamellar stacks of phospholipid membranes, induced by polymers with hydrophobic anchors grafted along their hydrophilic backbone. We interpret our experimental results in terms of a model, in which local membrane curvature and polymer concentration are coupled. The model predicts the occurence of maximally tight coils above a threshold anchor occupancy. Indeed, only maximally tight coils are observed experimentally. Our system is unique in that coils form in the absence of twist.

cond-mat.soft↗

arXiv1999

Coexistence of native and denatured phases in a single protein-like molecule

In order to understand the nuclei which develop during the course of protein folding and unfolding, we examine phase segregation of a single heteropolymer chain which occurs in equilibrium. These segregated conformations are characterized by a nucleus of monomers which are superimposable upon the native conformation. We computationally generate the phase segregation by applying a ``folding pressure,'' or adding an energetic bonus for native monomer-monomer contacts. The computer models reveal a fundamental difference in the nucleation process between heteropolymeric and the more familiar vapor-liquid systems: in a polymer system, some nuclei hinder folding via topological constraints and must be partially destroyed in order for folding to proceed. To illustrate this finding, we examine the kinetics of protein unfolding in the long chain limit through scaling arguments. We find that because of the topological constraints, the critical nucleus size is of the order of the entire chain size so that unfolding time scales as $\exp [c N^{2/3} ]$, where $N$ and $c$ are the chain length and a constant.

cond-mat.dis-nn↗

arXiv1999

Statistical Mechanics of Torque Induced Denaturation of DNA

A unifying theory of the denaturation transition of DNA, driven by temperature T or induced by an external mechanical torque Gamma is presented. Our model couples the hydrogen-bond opening and the untwisting of the helicoidal molecular structure. We show that denaturation corresponds to a first-order phase transition from B-DNA to d-DNA phases and that the coexistence region is naturally parametrized by the degree of supercoiling sigma. The denaturation free energy, the temperature dependence of the twist angle, the phase diagram in the T,Gamma plane and isotherms in the sigma, Gamma plane are calculated and show a good agreement with experimental data.

cond-mat.stat-mech↗

arXiv1999

Random walks in the space of conformations of toy proteins

Monte Carlo dynamics of the lattice 48 monomers toy protein is interpreted as a random walk in an abstract (discrete) space of conformations. To test the geometry of this space, we examine the return probability $P(T)$, which is the probability to find the polymer in the native state after $T$ Monte Carlo steps, provided that it starts from the native state at the initial moment. Comparing computational data with the theoretical expressions for $P(T)$ for random walks in a variety of different spaces, we show that conformational spaces of polymer loops may have non-trivial dimensions and exhibit negative curvature characteristic of Lobachevskii (hyperbolic) geometry.

cond-mat.dis-nn↗

arXiv1999

Error Thresholds on Dynamic Fittness-Landscapes

In this paper we investigate error-thresholds on dynamics fitness-landscapes. We show that there exists both lower and an upper threshold, representing limits to the copying fidelity of simple replicators. The lower bound can be expressed as a correction term to the error-threshold present on a static landscape. The upper error-threshold is a new limit that only exists on dynamic fitness-landscapes. We also show that for long genomes on highly dynamic fitness-landscapes there exists a lower bound on the selection pressure needed to enable effective selection of genomes with superior fitness independent of mutation rates, i.e., there are distinct limits to the evolutionary parameters in dynamic environments.

physics.bio-ph↗

arXiv1999

A twist in chiral interaction between biological helices

Using an exact solution for the pair interaction potential, we show that long, rigid, chiral molecules with helical surface charge patterns have a preferential interaxial angle ~((RH)^1/2)/L, where L is the length of the molecules, R is the closest distance between their axes, and H is the helical pitch. Estimates based on this formula suggest a solution for the puzzle of small interaxial angles in a-helix bundles and in cholesteric phases of DNA.

physics.bio-ph↗

arXiv2000

Rupture of multiple parallel molecular bonds under dynamic loading

Biological adhesion often involves several pairs of specific receptor-ligand molecules. Using rate equations, we study theoretically the rupture of such multiple parallel bonds under dynamic loading assisted by thermal activation. For a simple generic type of cooperativity, both the rupture time and force exhibit several different scaling regimes. The dependence of the rupture force on the number of bonds is predicted to be either linear, like a square root or logarithmic.

physics.bio-ph↗

arXiv1999

Fast Response and Temporal Coding on Coherent Oscillations in Small-World Networks

We have investigated the role that different connectivity regimes play on the dynamics of a network of Hodgkin-Huxley neurons by computer simulations. The different connectivity topologies exhibit the following features: random connectivity topologies give rise to fast system response yet are unable to produce coherent oscillations in the average activity of the network; on the other hand, regular connectivity topologies give rise to coherent oscillations and temporal coding, but in a temporal scale that is not in accordance with fast signal processing. Finally, small-world (SW) connectivity topologies, which fall between random and regular ones, take advantage of the best features of both, giving rise to fast system response with coherent oscillations along with reproducible temporal coding on clusters of neurons. Our work is the first, to the best of our knowledge, to show the need for a small-world topology in order to obtain all these features in synergy within a biologically plausible time scale.

cond-mat.dis-nn↗

arXiv2000

Role of Secondary Motifs in Fast Folding Polymers: A Dynamical Variational Principle

A fascinating and open question challenging biochemistry, physics and even geometry is the presence of highly regular motifs such as alpha-helices in the folded state of biopolymers and proteins. Stimulating explanations ranging from chemical propensity to simple geometrical reasoning have been invoked to rationalize the existence of such secondary structures. We formulate a dynamical variational principle for selection in conformation space based on the requirement that the backbone of the native state of biologically viable polymers be rapidly accessible from the denatured state. The variational principle is shown to result in the emergence of helical order in compact structures.

cond-mat.stat-mech↗

arXiv1999

Origin of Native Driving Force in Protein Folding

We derive an expression with four adjustable parameters that reproduces well the 20x20 Miyazawa-Jernigan potential matrix extracted from known protein structures. The numerical values of the parameters can be approximately computed from the surface tension of water, water-screened dipole interactions between residues and water and among residues, and average exposures of residues in folded proteins.

cond-mat↗

arXiv2000

Origin of complexity in multicellular organisms

Through extensive studies of dynamical system modeling cellular growth and reproduction, we find evidence that complexity arises in multicellular organisms naturally through evolution. Without any elaborate control mechanism, these systems can exhibit complex pattern formation with spontaneous cell differentiation. Such systems employ a `cooperative' use of resources and maintain a larger growth speed than simple cell systems, which exist in a homogeneous state and behave 'selfishly'. The relevance of the diversity of chemicals and reaction dynamics to the growth of a multicellular organism is demonstrated. Chaotic biochemical dynamics are found to provide the multi-potency of stem cells.

nlin.AO↗

arXiv2020

Random Networks of Spiking Neurons: Instability in the Xenopus tadpole moto-neural pattern

A large network of integrate-and-fire neurons is studied analytically when the synaptic weights are independently randomly distributed according to a Gaussian distribution with arbitrary mean and variance. The relevant order parameters are identified, and it is shown that such network is statistically equivalent to an ensemble of independent integrate-and-fire neurons with each input signal given by the sum of a self-interaction deterministic term and a Gaussian colored noise. The model is able to reproduce the quasi-synchronous oscillations, and the dropout of their frequency, of the central nervous system neurons of the swimming Xenopus tadpole. Predictions from the model are proposed for future experiments.

cond-mat.dis-nn↗

arXiv2000

Energetic Components of Cooperative Protein Folding

A new lattice protein model with a four-helix bundle ground state is analyzed by a parameter-space Monte Carlo histogram technique to evaluate the effects of an extensive variety of model potentials on folding thermodynamics. Cooperative helical formation and contact energies based on a 5-letter alphabet are found to be insufficient to satisfy calorimetric and other experimental criteria for two-state folding. Such proteinlike behaviors are predicted, however, by models with polypeptide-like local conformational restrictions and environment-dependent hydrogen bonding-like interactions.

cond-mat.stat-mech↗

arXiv2000

Twirling Elastica: Kinks, Viscous Drag, and Torsional Stress

Biological filaments such as DNA or bacterial flagella are typically curved in their natural states. To elucidate the interplay of viscous drag, twisting, and bending in the overdamped dynamics of such filaments, we compute the steady-state torsional stress and shape of a rotating rod with a kink. Drag deforms the rod, ultimately extending or folding it depending on the kink angle. For certain kink angles and kink locations, both states are possible at high rotation rates. The agreement between our macroscopic experiments and the theory is good, with no adjustable parameters.

cond-mat.soft↗

arXiv2000

Random replicators with high-order interactions

We use tools of the equilibrium statistical mechanics of disordered systems to study analytically the statistical properties of an ecosystem composed of N species interacting via random, Gaussian interactions of order p >= 2, and deterministic self-interactions u <= 0. We show that for nonzero u the effect of increasing the order of the interactions is to make the system more cooperative, in the sense that the fraction of extinct species is greatly reduced. Furthermore, we find that for p > 2 there is a threshold value which gives a lower bound to the concentration of the surviving species, preventing then the existence of rare species and, consequently, increasing the robustness of the ecosystem to external perturbations.

cond-mat.stat-mech↗