alexa Modeling the Chain Entropy of Biopolymers: Unifying Two Different Random Walk Models under One Framework

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Recommended Conferences

16th World Congress on Structural Biology

Amsterdam, Netherlands
Modeling the Chain Entropy of Biopolymers: Unifying Two Different Random Walk Models under One Framework

Entropy plays a critical role in the long range structure of biopolymers. To model the coarse-grained chain entropy of the residues in biopolymers, the lattice model or the Gaussian polymer chain (GPC) model is typically used. Both models use the concept of a random walk to find the conformations of an unstructured polymer. However, the entropy of the lattice model is a function of the coordination number, whereas the entropy of the GPC is a function of the root-mean square separation distance between the ends of the polymer. This can lead to inconsistent predictions for the coarse-grained entropy. Here we show that the GPC model and the lattice model both are consistent under transformations using the cross-linking entropy (CLE) model and that the CLE model generates a family of equations that include these two models at important limits. We show that the CLE model is a unifying approach to the thermodynamics of biopolymers that links these incompatible models into a single framework, elicits their similarities and differences, and expands beyond the models allowing calculation of variable flexibility and incorporating important corrections such as the worm-like-chain model. The CLE model is also consistent with the contact-order model and, when combined with existing local pairing potentials, can predict correct structures at the minimum free energy.

Citation: Dawson W, Kawai G (2009). Modeling the Chain Entropy of Biopolymers: Unifying Two Different Random Walk Models under One Framework. J Comput Sci Syst Biol 2: 001-023. doi: 10.4172/jcsb.1000014

  • Share this page
  • Facebook
  • Twitter
  • LinkedIn
  • Google+
  • Pinterest
  • Blogger
Top