1,318 research outputs found
Ab initio RNA folding
RNA molecules are essential cellular machines performing a wide variety of
functions for which a specific three-dimensional structure is required. Over
the last several years, experimental determination of RNA structures through
X-ray crystallography and NMR seems to have reached a plateau in the number of
structures resolved each year, but as more and more RNA sequences are being
discovered, need for structure prediction tools to complement experimental data
is strong. Theoretical approaches to RNA folding have been developed since the
late nineties when the first algorithms for secondary structure prediction
appeared. Over the last 10 years a number of prediction methods for 3D
structures have been developed, first based on bioinformatics and data-mining,
and more recently based on a coarse-grained physical representation of the
systems. In this review we are going to present the challenges of RNA structure
prediction and the main ideas behind bioinformatic approaches and physics-based
approaches. We will focus on the description of the more recent physics-based
phenomenological models and on how they are built to include the specificity of
the interactions of RNA bases, whose role is critical in folding. Through
examples from different models, we will point out the strengths of
physics-based approaches, which are able not only to predict equilibrium
structures, but also to investigate dynamical and thermodynamical behavior, and
the open challenges to include more key interactions ruling RNA folding.Comment: 28 pages, 18 figure
Self-organised criticality in base-pair breathing in DNA with a defect
We analyse base-pair breathing in a DNA sequence of 12 base-pairs with a
defective base at its centre. We use both all-atom molecular dynamics (MD)
simulations and a system of stochastic differential equations (SDE). In both
cases, Fourier analysis of the trajectories reveals self-organised critical
behaviour in the breathing of base-pairs. The Fourier Transforms (FT) of the
interbase distances show power-law behaviour with gradients close to -1. The
scale-invariant behaviour we have found provides evidence for the view that
base-pair breathing corresponds to the nucleation stage of large-scale DNA
opening (or 'melting') and that this process is a (second-order) phase
transition. Although the random forces in our SDE system were introduced as
white noise, FTs of the displacements exhibit pink noise, as do the
displacements in the AMBER/MD simulations.Comment: 18 pages, 8 figure
Quantumlike Chaos in the Frequency Distributions of the Bases A, C, G, T in Drosophila DNA
Continuous periodogram power spectral analyses of fractal fluctuations of
frequency distributions of bases A, C, G, T in Drosophila DNA show that the
power spectra follow the universal inverse power-law form of the statistical
normal distribution. Inverse power-law form for power spectra of space-time
fluctuations is generic to dynamical systems in nature and is identified as
self-organized criticality. The author has developed a general systems theory,
which provides universal quantification for observed self-organized criticality
in terms of the statistical normal distribution. The long-range correlations
intrinsic to self-organized criticality in macro-scale dynamical systems are a
signature of quantumlike chaos. The fractal fluctuations self-organize to form
an overall logarithmic spiral trajectory with the quasiperiodic Penrose tiling
pattern for the internal structure. Power spectral analysis resolves such a
spiral trajectory as an eddy continuum with embedded dominant wavebands. The
dominant peak periodicities are functions of the golden mean. The observed
fractal frequency distributions of the Drosophila DNA base sequences exhibit
quasicrystalline structure with long-range spatial correlations or
self-organized criticality. Modification of the DNA base sequence structure at
any location may have significant noticeable effects on the function of the DNA
molecule as a whole. The presence of non-coding introns may not be redundant,
but serve to organize the effective functioning of the coding exons in the DNA
molecule as a complete unit.Comment: 46 pages, 9 figure
Stochastic Physics, Complex Systems and Biology
In complex systems, the interplay between nonlinear and stochastic dynamics,
e.g., J. Monod's necessity and chance, gives rise to an evolutionary process in
Darwinian sense, in terms of discrete jumps among attractors, with punctuated
equilibrium, spontaneous random "mutations" and "adaptations". On an
evlutionary time scale it produces sustainable diversity among individuals in a
homogeneous population rather than convergence as usually predicted by a
deterministic dynamics. The emergent discrete states in such a system, i.e.,
attractors, have natural robustness against both internal and external
perturbations. Phenotypic states of a biological cell, a mesoscopic nonlinear
stochastic open biochemical system, could be understood through such a
perspective.Comment: 10 page
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