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At least 127 records · Page 7Linked to original sources

arXiv2001

Optimality of the genetic code with respect to protein stability and amino acid frequencies

How robust is the natural genetic code with respect to mistranslation errors? It has long been known that the genetic code is very efficient in limiting the effect of point mutation. A misread codon will commonly code either for the same amino acid or for a similar one in terms of its biochemical properties, so the structure and function of the coded protein remain relatively unaltered. Previous studies have attempted to address this question more quantitatively, namely by statistically estimating the fraction of randomly generated codes that do better than the genetic code regarding its overall robustness. In this paper, we extend these results by investigating the role of amino acid frequencies in the optimality of the genetic code. When measuring the relative fitness of the natural code with respect to a random code, it is indeed natural to assume that a translation error affecting a frequent amino acid is less favorable than that of a rare one, at equal mutation cost. We find that taking the amino acid frequency into account accordingly decreases the fraction of random codes that beat the natural code, making the latter comparatively even more robust. This effect is particularly pronounced when more refined measures of the amino acid substitution cost are used than hydrophobicity. To show this, we devise a new cost function by evaluating with computer experiments the change in folding free energy caused by all possible single-site mutations in a set of known protein structures. With this cost function, we estimate that of the order of one random code out of 100 millions is more fit than the natural code when taking amino acid frequencies into account. The genetic code seems therefore structured so as to minimize the consequences of translation errors on the 3D structure and stability of proteins.

physics.bio-ph↗

arXiv2002

Errors drive the evolution of biological signalling to costly codes

Reduction of costs in biological signalling seems an evolutionary advantage, but recent experiments have shown signalling codes shifted to signals of high cost with a underutilisation of low cost signals. Here I show that errors in the efficient translation of biological states into signals shift codes to higher costs, effectively performing a quality control. The statistical structure of signal usage is predicted to be of a generalised Boltzmann form that penalises signals that are costly and sensitive to errors. This predicted distribution of signal usage against signal cost has two main features: an exponential tail required for cost efficiency and an underutilisation of the low cost signals required to protect the signalling quality from the errors. These predictions are shown to correspond quantitatively to the experiments in which gathering signal statistics is feasible as in visual cortex neurons.

physics.bio-ph↗

arXiv2001

Hamming distance geometry of a protein conformational space. Application to the clustering of a 4 ns molecular dynamics trajectory of the HIV-1 integrase catalytic core

Protein structures can be encoded into binary sequences, these are used to define a Hamming distance in conformational space: the distance between two different molecular conformations is the number of different bits in their sequences. Each bit in the sequence arises from a partition of conformational space in two halves. Thus, the information encoded in the binary sequences is also used to characterize the regions of conformational space visited by the system. We apply this distance and their associated geometric structures, to the clustering and analysis of conformations sampled during a 4 ns molecular dynamics simulation of the HIV-1 integrase catalytic core. The cluster analysis of the simulation shows a division of the trajectory into two segments of 2.6 and 1.4 ns length, which are qualitatively different: the data points to the fact that equilibration is only reached at the end of the first segment. Some length of the paper is devoted to compare the Hamming distance to the r.m.s. deviation measure. The analysis of the cases studied so far, shows that under the same conditions the two measures behave quite differently, and that the Hamming distance appears to be more robust than the r.m.s. deviation.

physics.bio-ph↗

arXiv2001

Intercellular Communication Via Intracellular Calcium Oscillations

In this letter we present the results of a simple model for intercellular communication via calcium oscillations, motivated in part by a recent experimental study. The model describes two cells (a "donor" and "sensor") whose intracellular dynamics involve a calcium-induced, calcium release process. The cells are coupled by assuming that the the input of the sensor cell is proportional to the output of the donor cell. As one varies the frequency of calcium oscillations of the donor cell, the sensor cell passes through a sequence of N:M phase locked regimes and exhibits a "Devil's staircase" behavior. Such a phase locked response has been seen experimentally in pulsatile stimulation of single cells. We also study a stochastic version of the coupled two cell model. We find that phase locking holds for realistic choices for the cell volume.

physics.bio-ph↗

arXiv2002

Clustering of SNPs along a chromosome: can the neutral model be rejected?

Single nucleotide polymorphisms (SNPs) often appear in clusters along the length of a chromosome. This is due to variation in local coalescent times caused by,for example, selection or recombination. Here we investigate whether recombination alone (within a neutral model) can cause statistically significant SNP clustering. We measure the extent of SNP clustering as the ratio between the variance of SNPs found in bins of length $l$, and the mean number of SNPs in such bins, $σ^2_l/μ_l$. For a uniform SNP distribution $σ^2_l/μ_l=1$, for clustered SNPs $σ^2_l/μ_l > 1$. Apart from the bin length, three length scales are important when accounting for SNP clustering: The mean distance between neighboring SNPs, $Δ$, the mean length of chromosome segments with constant time to the most recent common ancestor, $\el$, and the total length of the chromosome, $L$. We show that SNP clustering is observed if $Δ< \el \ll L$. Moreover, if $l\ll \el \ll L$, clustering becomes independent of the rate of recombination. We apply our results to the analysis of SNP data sets from mice, and human chromosomes 6 and X. Of the three data sets investigated, the human X chromosome displays the most significant deviation from neutrality.

physics.bio-ph↗

arXiv2002

Dynamical investigation of macromolecular hybridization bioassays

A novel sensoric technique for the dynamical in situ investigation of a hybridization bio assay is presented, which utilizes a metal bead labeling method. Therein, hybridization results in an increased metal coverage on parts of a substrate, where it takes place. Our sensing principle relies on the measurement of the radio frequency impedance of the hybridization spots. We propose several examples for sensor devices.

physics.ins-det↗

arXiv2002

Developing Mathematics for Insight into Sensorimotor Neurobiology

This paper summarizes a research program to express the organization of sensorimotor control by specifying physiological states and the conditions for transitions among them. By a slight change in standard notation, conditional dynamics provides a moving spotlight, focussing on salient subspaces within a high-dimensional space. This mathematical approach serves as a window on the organization of sensorimotor neurobiology. The intertwined efforts to express the intrinsic organization of neurobiology and to clarify it mathematically are yielding a mathematical structure that is growing on fertile empirical ground.

physics.bio-ph↗

arXiv2004

Degeneracy in the genetic code and its symmetries by base substitutions

Why is the genetic code the way it is? The most successful theory states that the codon assignments minimise the effects of errors arising in primordial living systems. Here a transversion is reported that leaves invariant degeneracy in the genetic code. A model was established to address the question: How should sets of synonymous codons be chosen to minimise the deleterious effects of non synonymous substitutions? It is shown that the arithmetic theory of quadratic forms provides the framework for degeneracy in the genetic code.

physics.bio-ph↗

arXiv2003

Does tumor growth follow a 'universal law'?

A general model for the ontogenetic growth of living organisms has been recently proposed. Here we investigate the extension of this model to the growth of solid malignant tumors. A variety of in vitro and in vivo data are analyzed and compared with the prediction of a 'universal' law, relating properly rescaled tumor masses and tumor growth times. The results support the notion that tumor growth follows such a universal law. Several important implications of this finding are discussed, including its relevance for tumor metastasis and recurrence, cell turnover rates, angiogenesis and invasion.

physics.med-ph↗

arXiv2003

A Possible Mechanism of Biological Memories in terms of Quantum Fluids

A mechanism of memories, especially biological memories, is studied in terms of quantum fluids. Two-dimensional flows in central potentials $V_a(ρ)=-a^2g_aρ^{2(a-1)}$ ($a\not=0$ and $ρ=\sqrt{x^2+y^2}$) have zero-energy eigenstates that degenerate infinitely for all $a$. It is shown that stable standing waves constructed from the zero-energy flows are confined in various types of polygons which can be the minimum units of memory systems. Vortex patterns awoken in the units by stimuli correspond to the memories of the stimuli. This memory system is not a system for preserving memories as usual but that for awaking memories. The system has interesting properties; (i) the absolute economy as for the energy consumption, (ii) the infinite variety for a huge number of memories, (iii) the perfect recovery of the system from any disturbances by stimuli, and (iv) the large flexibility in the construction of the system. A process for thinking is also proposed in terms of this memory system.

physics.bio-ph↗

arXiv1998

Scaling Laws and Similarity Detection in Sequence Alignment with Gaps

We study the problem of similarity detection by sequence alignment with gaps, using a recently established theoretical framework based on the morphology of alignment paths. Alignments of sequences without mutual correlations are found to have scale-invariant statistics. This is the basis for a scaling theory of alignments of correlated sequences. Using a simple Markov model of evolution, we generate sequences with well-defined mutual correlations and quantify the fidelity of an alignment in an unambiguous way. The scaling theory predicts the dependence of the fidelity on the alignment parameters and on the statistical evolution parameters characterizing the sequence correlations. Specific criteria for the optimal choice of alignment parameters emerge from this theory. The results are verified by extensive numerical simulations.

physics.bio-ph↗

arXiv1998

Discrimination of the Healthy and Sick Cardiac Autonomic Nervous System by a New Wavelet Analysis of Heartbeat Intervals

We demonstrate that it is possible to distinguish with a complete certainty between healthy subjects and patients with various dysfunctions of the cardiac nervous system by way of multiresolutional wavelet transform of RR intervals. We repeated the study of Thurner et al on different ensemble of subjects. We show that reconstructed series using a filter which discards wavelet coefficients related with higher scales enables one to classify individuals for which the method otherwise is inconclusive. We suggest a delimiting diagnostic value of the standard deviation of the filtered, reconstructed RR interval time series in the range of $\sim 0.035$ (for the above mentioned filter), below which individuals are at risk.

physics.med-ph↗

arXiv1998

Nearly Closed Loops in Biological Systems as Electromagnetic Receptors

It is noted here that when a nearly closed loop in a biological system, such as a self-synapsing (autapsing) neuron or mutually synapsing pair, is exposed to an AC magnetic field, the induced electric fields in the insulating gaps can be many orders of magnitude larger than the average values typically discussed in the literature.$^{1,2}$ It is suggested that animal nervous systems might possibly be affected in selected spots by man-made alternating magnetic fields at weaker levels than previously supposed. Radio and microwave radiation should be considered particularly suspect.

physics.bio-ph↗

arXiv1998

Hydrophobic Effects on a Molecular Scale

A theoretical approach is developed to quantify hydrophobic hydration and interactions on a molecular scale, with the goal of gaining insight into the molecular origins of hydrophobic effects. The model is based on the fundamental relation between the probability for cavity formation in bulk water resulting from molecular-scale density fluctuations, and the hydration free energy of the simplest hydrophobic solute, a hard particle. This probability is estimated using an information theory (IT) approach, incorporating experimentally available properties of bulk water -- the density and radial distribution function. The IT approach reproduces the simplest hydrophobic effects: hydration of spherical nonpolar solutes, the potential of mean force between methane molecules, and solvent contributions to the torsional equilibrium of butane. Applications of this approach to study temperature and pressure effects provide new insights into the thermodynamics and kinetics of protein folding. The IT model relates the hydrophobic-entropy convergence observed in protein unfolding experiments to the macroscopic isothermal compressibility of water. A novel explanation for pressure denaturation of proteins follows from an analysis of the pressure stability of hydrophobic aggregates, suggesting that water penetrates the hydrophobic core of proteins at high pressures. This resolves a long-standing puzzle, whether pressure denaturation contradicts the hydrophobic-core model of protein stability. Finally, issues of ``dewetting'' of molecularly large nonpolar solutes are discussed in the context of a recently developed perturbation theory approach.

physics.chem-ph↗

arXiv1998

A dynamic programming algorithm for RNA structure prediction including pseudoknots

We describe a dynamic programming algorithm for predicting optimal RNA secondary structure, including pseudoknots. The algorithm has a worst case complexity of ${\cal O}(N^6)$ in time and ${\cal O}(N^4)$ in storage. The description of the algorithm is complex, which led us to adopt a useful graphical representation (Feynman diagrams) borrowed from quantum field theory. We present an implementation of the algorithm that generates the optimal minimum energy structure for a single RNA sequence, using standard RNA folding thermodynamic parameters augmented by a few parameters describing the thermodynamic stability of pseudoknots. We demonstrate the properties of the algorithm by using it to predict structures for several small pseudoknotted and non-pseudoknotted RNAs. Although the time and memory demands of the algorithm are steep, we believe this is the first algorithm to be able to fold optimal (minimum energy) pseudoknotted RNAs with the accepted RNA thermodynamic model.

physics.bio-ph↗

arXiv2007

Measurability of side chain rotational isomer populations: NMR and molecular mechanics of cobalt glycyl-leucine dipeptide model system

The cobalt glycyl-leucine dipeptide is a model system for studying the effects of Karplus equation calibration, molecular mechanics accuracy, backbone conformation, and thermal motions on the measurability of side chain rotational isomer populations. We analyze measurements of 8 vicinal coupling constants about the alpha to beta-carbon and beta to gamma-carbon bonds of the leucine side chain and of 10 NOESY cross relaxation rates across these bonds. Molecular mechanics and peptide and protein crystallographic databases are an essential part of this analysis because they independently suggest that the trans gauche-plus and gauche-minus trans rotational isomers of the leucine side chain predominate. They also both suggest that puckering of the cobalt dipeptide ring system reduces the gauche-plus gauche-plus rotational isomer population to less than about 10%. At the present +/- 1 Hz calibration accuracy of Karplus equations for vicinal coupling constants, the predominant trans gauche-plus and gauche-minus trans rotational isomer populations can be measured with about 5% accuracy, but the population of the gauche-plus gauche-plus rotational isomer is probably very near or just below the limit of measurability. These estimates also depend upon qualitative assessments of the accuracy of the molecular mechanics energy wells. We introduce gel graphics that are ideally suited to presenting qualitative error and measurability estimates.

physics.bio-ph↗

arXiv1999

Physical Parameters for Biconcave Shape Vesicles

The Helfrich's shape equation of axisymmetric vesicles is studied. A sufficient condition on the physical parameters and some geometric properties are discovered for the biconcave shape.

physics.bio-ph↗

arXiv2004

Semiclassical Neural Network

We have constructed a simple semiclassical model of neural network where neurons have quantum links with one another in a chosen way and affect one another in a fashion analogous to action potentials. We have examined the role of stochasticity introduced by the quantum potential and compare the system with the classical system of an integrate-and-fire model by Hopfield. Average periodicity and short term retentivity of input memory are noted.

quant-ph↗