Precursory signatures of protein folding/unfolding: from time series correlation analysis to atomistic mechanisms.

Folded conformations of proteins in thermodynamically stable states have long lifetimes. Before it folds into a stable conformation, or after unfolding from a stable conformation, the protein will generally stray from one random conformation to another leading thus to rapid fluctuations. Brief structural changes therefore occur before folding and unfolding events. These short-lived movements are easily overlooked in studies of folding/unfolding for they represent momentary excursions of the protein to explore conformations in the neighborhood of the stable conformation. The present study looks for precursory signatures of protein folding/unfolding within these rapid fluctuations through a combination of three techniques: (1) ultrafast shape recognition, (2) time series segmentation, and (3) time series correlation analysis. The first procedure measures the differences between statistical distance distributions of atoms in different conformations by calculating shape similarity indices from molecular dynamics simulation trajectories. The second procedure is used to discover the times at which the protein makes transitions from one conformation to another. Finally, we employ the third technique to exploit spatial fingerprints of the stable conformations; this procedure is to map out the sequences of changes preceding the actual folding and unfolding events, since strongly correlated atoms in different conformations are different due to bond and steric constraints. The aforementioned high-frequency fluctuations are therefore characterized by distinct correlational and structural changes that are associated with rate-limiting precursors that translate into brief segments. Guided by these technical procedures, we choose a model system, a fragment of the protein transthyretin, for identifying in this system not only the precursory signatures of transitions associated with α helix and ß hairpin, but also the important role played by weaker correlations in such protein folding dynamics.

Melting behavior of Ag14 cluster: an order parameter by instantaneous normal modes.

This paper studies the melting behavior of Ag(14) cluster employing the instantaneous normal mode (INM) analysis that was previously developed for bimetallic cluster Ag(17)Cu(2). The isothermal Brownian-type molecular dynamics simulation is used to generate atom configurations of Ag(14) at different temperatures up to 1500 K. At each temperature, these atomic configurations are then analyzed by the INM technique. To delve into the melting behavior of Ag(14) cluster which differs from Ag(17)Cu(2) by the occurrence of an anomalous prepeak in the specific heat curve in addition to the typical principal peak, we appeal to examining the order parameter τ(T) defined in the context of the INM method. Two general approaches are proposed to calculate τ(T). In one, τ(T) is defined in terms of the INM vibrational density of states; in another, τ(T) is defined considering the cluster as a rigid body with its rotational motions described by three orthogonal eigenvectors. Our results for Ag(14) by these two methods indicate the mutual agreement of τ(T) calculated and also the consistent interpretation of the melting behavior with the specific heat data. The order parameter τ(T) provides in addition an insightful interpretation between the melting of clusters and the concept of broken symmetry which has been found successful in studies of the melting transition of bulk systems.

Comparative study of cluster Ag17Cu2 by instantaneous normal mode analysis and by isothermal Brownian-type molecular dynamics simulation.

We perform isothermal Brownian-type molecular dynamics simulations to obtain the velocity autocorrelation function and its time Fourier-transformed power spectral density for the metallic cluster Ag(17)Cu(2). The temperature dependences of these dynamical quantities from T = 0 to 1500 K were examined and across this temperature range the cluster melting temperature T(m), which we define to be the principal maximum position of the specific heat is determined. The instantaneous normal mode analysis is then used to dissect the cluster dynamics by calculating the vibrational instantaneous normal mode density of states and hence its frequency integrated value I(j) which is an ensemble average of all vibrational projection operators for the jth atom in the cluster. In addition to comparing the results with simulation data, we look more closely at the entities I(j) of all atoms using the point group symmetry and diagnose their temperature variations. We find that I(j) exhibit features that may be used to deduce T(m), which turns out to agree very well with those inferred from the power spectral density and specific heat.

Bakuchiol, an antibacterial component of Psoralidium tenuiflorum.

Bioactivity guided fractionation of an EtOAc extract from Psoralidium tenuiflorum (Pursh) Rydb. (family : Fabaceae) yielded the known compound bakuchiol as a racemic mixture. This compound was purified by liquid-liquid partitioning and chromatography followed by NMR and GCMS characterisation. This compound exhibited Staphylococcus epidermidis cytotoxicity. COSY and HETCOR spectra of the isolated bakuchiol indicated two disagreements with previously reported NMR structural assignments; reassignments are described herein. Long-term storage of bakuchiol resulted in degradation to 4-hydroxybenzaldehyde, which was purified and characterised.

Melting scenario in metallic clusters.

The isothermal Brownian-type molecular dynamics simulation has been applied to study the melting behavior of bimetallic clusters. It was found that the specific heat and Lindermann-like parameter customarily used in bulk system to describe solid-liquid transition show incongruity in the predicted melting temperature T(melt). The underlying mechanisms that lead to the incompatibility of T(melt) separately deduced from these two quantities were analyzed further. To gain insight into the melting behavior, we calculated in addition the velocity autocorrelation function and its Fourier transform, the power spectrum, and extracted from them the T(melt). It appears that the T(melt) inferred from the latter quantities is closer to that deduced from the principal peak position of specific heat. Two bimetallic clusters, namely, Ag(1)Cu(13) and Au(1)Cu(13), were selected for a thorough investigation. In the context of cluster morphology, we scrutinized the atomic distributions of Ag(1)Cu(13), Au(1)Cu(13), and Cu(14) and effected a comparative study between a bimetallic cluster and a pure cluster so as to learn from comparison the differences in the thermal reaction of atoms, in particular, the impurity atom in the bimetallic cluster. On analyzing the dynamical data, we observed at a lower temperature (T<

Structures of bimetallic clusters.

We report an optimization algorithm for studying bimetallic nanoclusters. The algorithm combines two state-of-the-art methods, the genetic algorithm and the basin hopping approach, widely employed in the literature for predicting structures of pure metallic and nonmetallic clusters. To critically test the present algorithm and its use in determining the lowest-energy structures of bimetallic nanoclusters, we apply it to study the bimetallic clusters Cu(n)Au(38-n) (0< or =n< or =38). It is predicted that the Au atoms, being larger in size than the Cu atoms, prefer to occupy surface sites showing thus the segregating behavior. As the atom fraction of Cu increases, the bimetallic cluster Cu(n)Au(38-n), as a whole, first takes on an amorphous structure and is followed by dramatic changes in structure with the Cu atoms revealing hexagonal, then assuming pentagonal, and finally shifting to octahedral symmetry in the Cu-rich range.

Multicanonical basin hopping: a new global optimization method for complex systems.

We introduce a new optimization algorithm that combines the basin-hopping method, which can be used to efficiently map out an energy landscape associated with minima, with the multicanonical Monte Carlo method, which encourages the system to move out of energy traps during the computation. As an example of implementing the algorithm for the global minimization of a multivariable system, we consider the Lennard-Jones systems containing 150-185 particles, and find that the new algorithm is more efficient than the original basin-hopping method.

Nasal alar reconstruction with free "accessory auricle".

A case of basal cell epithelioma of the nasal ala is presented that was managed by local excision of the tumor. The alar defect was reconstructed by a microvascular accessory auricle with excellent outcome.