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Detalle de: Phase Transitions of Single Semistiff Polymer Chains

Title Phase Transitions of Single Semistiff Polymer Chains
Abstract

We study numerically a lattice model of semiflexible homopolymers with nearest neighbor (nn) attraction and energetic preference for straight joints between bonded monomers. For this we use a new Monte Carlo algorithm, the “prunedenriched Rosenbluth Method” (PERM). It is very efficient both for relatively open configurations at high temperatures and for compact and frozen-in low-T states. This allows us to study in detail the phase diagram as a function of nn attractionε and stiffnessx. It shows aθ-collapse line with a transition from open coils (smallε) to molten compact globules (largeε) and a freezing transition toward a state with orientational global order (large stiffnessx). Qualitatively this is similar to a recently studied mean-field theory [S. Doniach, T. Garel, and H. Orland (1996),J. Chem. Phys. 105(4), 1601], but there are important differences in details. In contrast to the mean-field theory and to naive expectations, theθ-temperatureincreases with stiffnessx. The freezing temperature increases even faster, and reaches theθ-line at a finite value ofx. For even stiffer chains, the freezing transition takes place directly, without the formation of an intermediate globular state. Although being in conflict with mean-field theory, the latter had been conjectured already by Doniachet al. on the basis of heuristic arguments and of low-statistics Monte Carlo simulations. Finally, we discuss the relevance of the present model as a very crude model for protein folding.

Apa Reference Bastolla, U., & Grassberger, P. (1997). Phase Transitions of Single Semistiff Polymer Chains. Journal of Statistical Physics, 89(5–6), 1061–1078. 10.1007/bf02764222
Doi 10.1007/bf02764222
Publication Date Dec 1997
Publication Type Article
Researcher Ugo Bastolla
Ontology Functional annotation, Function prediction, Structural bioinformatics, Molecular flexibility, Molecular evolution, Conservation Analysis, Evolutionary modelling, Ecological modelling, Sequence Alignment, Phylogenetic Analysis, Mutation Analysis and design, Network Biology, Structure-function relationship, Evolutionary rates, Microbial communities, Population dynamics
Research Groups Computational biology and Bioinformatics (CBM): from Proteins to Ecosystems
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