Elastic energy of proteins and the stages of protein folding

We propose a universal elastic energy for proteins, which depends only on the radius of gyration $R_{g}$ and the residue number $N$. It is constructed using physical arguments based on the hydrophobic effect and hydrogen bonding. Adjustable parameters are fitted to data from the computer simulation of the folding of a set of proteins using the CSAW (conditioned self-avoiding walk) model. The elastic energy gives rise to scaling relations of the form $R_{g}\sim N^{\nu}$ in different regions. It shows three folding stages characterized by the progression with exponents $\nu = 3/5, 3/7, 2/5$, which we identify as the unfolded stage, pre-globule, and molten globule, respectively. The pre-globule goes over to the molten globule via a break in behavior akin to a first-order phase transition, which is initiated by a sudden acceleration of hydrogen bonding

Computational analysis of gene expression space associated with metastatic cancer

<p>Abstract</p> <p>Background</p> <p>Prostate carcinoma is among the most common types of cancer affecting hundreds of thousands people every year. Once the metastatic form of prostate carcinoma is documented, the majority of patients die from their tumors as opposed to other causes. The key to successful treatment is in the earliest possible diagnosis, as well as understanding the molecular mechanisms of metastatic progression. A number of recent studies have identified multiple biomarkers for metastatic progression. However, most of the studies consider only direct comparison between metastatic and non-metastatic classes of samples.</p> <p>Results</p> <p>We propose an alternative concept of analysis that considers the entire multidimensional space of gene expression and identifies the partition of this space in which metastatic development is possible. To apply this concept in cancer gene expression studies we utilize a modification of high-dimension natural taxonomy algorithm FOREL. Our analysis of microarray data containing primary and metastatic cancer samples has revealed not only differentially expressed genes, but also relations between different groups of primary and metastatic cancer. Metastatic samples tend to occupy a distinct partition of gene expression space. Further pathway analysis suggests that this partition is delineated by a specific pattern of gene expression in cytoskeleton remodeling, cell adhesion and apoptosis/cell survival pathways. We compare our findings with both report of original analysis and recent studies in molecular mechanism of metastasis.</p> <p>Conclusion</p> <p>Our analysis indicates a single molecular mechanism of metastasis. The new approach does not contradict previously reported findings, but reveals important details unattainable with traditional methodology.</p

Entropically driven transition to a liquid-crystalline polymer globule

A self-consistent-field theory (SCFT) in the grand canonical ensemble formulation is used to study transitions in a helix-coil multiblock copolymer globule. The helices are modeled as stiff rods. In addition to the established coil-globule transition we show for the first time that, even without explicit rod-rod alignment interaction, the system undergoes a transition to a nematic liquid-crystalline (LC) globular state. The LC-globule formation is driven by the hydrophobic helical segment attraction and the anisotropy of the globule surface energy. The full phase diagram of the copolymer was calculated. It discriminates between an open chain, amorphous globule and LC-globule. This model provides a relatively simple example of the interplay between secondary and tertiary structures in homopolypeptides. Moreover, it gives a simple explanation for the formation of helix bundles in certain globular proteins.Comment: 5 pages, 5 figures, submitted to Europhys. Let

Freezing Transition of Random Heteropolymers Consisting of an Arbitrary Set of Monomers

Mean field replica theory is employed to analyze the freezing transition of random heteropolymers comprised of an arbitrary number ($q$) of types of monomers. Our formalism assumes that interactions are short range and heterogeneity comes only from pairwise interactions, which are defined by an arbitrary $q \times q$ matrix. We show that, in general, there exists a freezing transition from a random globule, in which the thermodynamic equilibrium is comprised of an essentially infinite number polymer conformations, to a frozen globule, in which equilibrium ensemble is dominated by one or very few conformations. We also examine some special cases of interaction matrices to analyze the relationship between the freezing transition and the nature of interactions involved.Comment: 30 pages, 1 postscript figur

Do Natural Proteins Differ from Random Sequences Polypeptides? Natural vs. Random Proteins Classification Using an Evolutionary Neural Network

Are extant proteins the exquisite result of natural selection or are they random sequences slightly edited by evolution? This question has puzzled biochemists for long time and several groups have addressed this issue comparing natural protein sequences to completely random ones coming to contradicting conclusions. Previous works in literature focused on the analysis of primary structure in an attempt to identify possible signature of evolutionary editing. Conversely, in this work we compare a set of 762 natural proteins with an average length of 70 amino acids and an equal number of completely random ones of comparable length on the basis of their structural features. We use an ad hoc Evolutionary Neural Network Algorithm (ENNA) in order to assess whether and to what extent natural proteins are edited from random polypeptides employing 11 different structure-related variables (i.e. net charge, volume, surface area, coil, alpha helix, beta sheet, percentage of coil, percentage of alpha helix, percentage of beta sheet, percentage of secondary structure and surface hydrophobicity). The ENNA algorithm is capable to correctly distinguish natural proteins from random ones with an accuracy of 94.36%. Furthermore, we study the structural features of 32 random polypeptides misclassified as natural ones to unveil any structural similarity to natural proteins. Results show that random proteins misclassified by the ENNA algorithm exhibit a significant fold similarity to portions or subdomains of extant proteins at atomic resolution. Altogether, our results suggest that natural proteins are significantly edited from random polypeptides and evolutionary editing can be readily detected analyzing structural features. Furthermore, we also show that the ENNA, employing simple structural descriptors, can predict whether a protein chain is natural or random

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.Comment: 4 pages, RevTex, 4 eps figure

A Large Hadron Electron Collider at CERN

This document provides a brief overview of the recently published report on the design of the Large Hadron Electron Collider (LHeC), which comprises its physics programme, accelerator physics, technology and main detector concepts. The LHeC exploits and develops challenging, though principally existing, accelerator and detector technologies. This summary is complemented by brief illustrations of some of the highlights of the physics programme, which relies on a vastly extended kinematic range, luminosity and unprecedented precision in deep inelastic scattering. Illustrations are provided regarding high precision QCD, new physics (Higgs, SUSY) and electron-ion physics. The LHeC is designed to run synchronously with the LHC in the twenties and to achieve an integrated luminosity of O(100) fb$^{-1}$. It will become the cleanest high resolution microscope of mankind and will substantially extend as well as complement the investigation of the physics of the TeV energy scale, which has been enabled by the LHC