1,258 research outputs found
Entropic Landscape: the method to predict folding patterns and regional stability of proteins
I propose a new method to calculate the entropy of a given protein sequence fragment. The set of fragment entropies over all possible fragments of the given sequence shows which region of the sequence is statistically stable and which region has a strong desire to fold into particular conformations. Here are three methods to calculate fragment entropy, the results from each of which represent entropies of different stage of protein folding
Dogs Never Gets Prion Diseases. The Entropic Landscape Analysis of Prion Proteins Answers Why.
The Entropic Landscape Analysis was applied to the prion protein sequences of various mammals in order to detect potential sites of variants that would be responsible for the susceptibility of prion disease infection. Among familiar mammals, canines including dogs have been demonstrating strong resistance to prion diseases. Among the canine specifc substitutions the entropic landscape analysis pinpoints the substitutions Asn104Gly and Ser107Asn having the biggest impact to the conformational transition and stability. Although they must be further corroborated by experiments in vivo et vitro, the results are demonstrating that the entropic landscape analysis is useful enough to screen substitutions and polymorphisms potentially relevant to conformational stability and transition because the calculation time for the analysis is as long as a few seconds, and the analysis can be done without knowing the 3D structures
The Entropic Landscape of proteins revealing protein folding mechanism
It has long since been a mystery why most proteins fold within a flash of time into particular structures out of astronomically large numbers of possible conformations. Even more confusing is that protein folding in vivo is played out in rich solution containing various organic and non-organic, big and small molecules and ions which would potentially bind the protein molecules and prevent them folding. A possible answer to these mysteries might be, "Nature have favoured such proteins that quickly fold in rich solution through natural selection". Then what mechanism of folding has been favoured? Here I show how to decipher protein sequences to reveal the folding mechanism. The entropic landscape of a protein sequence tells which region of the sequence sets out to fold first which next and last. Each step of the folding procedure is programmed in the sequence. This make it clear why proteins fold quickly and escape from surrounding molecules and ions. The folding pathways represented by the entropic landscape agree with the pathways experimentally proposed. Besides, the simulation of protein folding scheduled by the entropic landscape generates native-like conformations, where the lower the entropy of a sequential region is the earlier its conformation is optimized in terms of energy minimization. The attempt to simulate protein folding gives further insights into the folding mechanism
Entangled spin clusters: some special features
In this paper, we study three specific aspects of entanglement in small spin
clusters. We first study the effect of inhomogeneous exchange coupling strength
on the entanglement properties of the S=1/2 antiferromagnetic linear chain
tetramer compound NaCuAsO_{4}. The entanglement gap temperature, T_{E}, is
found to have a non-monotonic dependence on the value of , the exchange
coupling inhomogeneity parameter. We next determine the variation of T_{E} as a
function of S for a spin dimer, a trimer and a tetrahedron. The temperature
T_{E} is found to increase as a function of S, but the scaled entanglement gap
temperature t_{E} goes to zero as S becomes large. Lastly, we study a spin-1
dimer compound to illustrate the quantum complementarity relation. We show that
in the experimentally realizable parameter region, magnetization and
entanglement plateaus appear simultaneously at low temperatures as a function
of the magnetic field. Also, the sharp increase in one quantity as a function
of the magnetic field is accompanied by a sharp decrease in the other so that
the quantum complementarity relation is not violated.Comment: 17 pages, 6 figures. Accepted in Phys. Rev.
Robust Bayesian graphical modeling using -divergence
Gaussian graphical model is one of the powerful tools to analyze conditional
independence between two variables for multivariate Gaussian-distributed
observations. When the dimension of data is moderate or high, penalized
likelihood methods such as the graphical lasso are useful to detect significant
conditional independence structures. However, the estimates are affected by
outliers due to the Gaussian assumption. This paper proposes a novel robust
posterior distribution for inference of Gaussian graphical models using the
-divergence which is one of the robust divergences. In particular, we
focus on the Bayesian graphical lasso by assuming the Laplace-type prior for
elements of the inverse covariance matrix. The proposed posterior distribution
matches its maximum a posteriori estimate with the minimum -divergence
estimate provided by the frequentist penalized method. We show that the
proposed method satisfies the posterior robustness which is a kind of measure
of robustness in the Bayesian analysis. The property means that the information
of outliers is automatically ignored in the posterior distribution as long as
the outliers are extremely large, which also provides theoretical robustness of
point estimate for the existing frequentist method. A sufficient condition for
the posterior propriety of the proposed posterior distribution is also shown.
Furthermore, an efficient posterior computation algorithm via the weighted
Bayesian bootstrap method is proposed. The performance of the proposed method
is illustrated through simulation studies and real data analysis.Comment: 35 pages, 5 figure
Field-Induced Order and Magnetization Plateaux in Frustrated Antiferromagnets
We argue that collinearly ordered states which exist in strongly frustrated
spin systems for special rational values of the magnetization are stabilized by
thermal as well as quantum fluctuations. These general predictions are tested
by Monte Carlo simulations for the classical and Lanczos diagonalization for
the S=1/2 frustrated square-lattice antiferromagnet.Comment: 4 pages, 2 PostScript figures included; to appear in the proceedings
of SCES2001, Ann Arbor, August 6-10, 2001 (Physica B
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