Deterministic folding: The role of entropic forces and steric specificities.

Autor: da Silva, Roosevelt A., da Silva, M. A. A., Caliri, A.
Předmět:
Zdroj: Journal of Chemical Physics; 3/1/2001, Vol. 114 Issue 9, 2 Diagrams, 2 Graphs
Abstrakt: The inverse folding problem of proteinlike macromolecules is studied by using a lattice Monte Carlo (MC) model in which steric specificities (nearest-neighbors constraints) are included and the hydrophobic effect is treated explicitly by considering interactions between the chain and solvent molecules. Chemical attributes and steric peculiarities of the residues are encoded in a 10-letter alphabet and a correspondent "syntax" is provided in order to write suitable sequences for the specified target structures; twenty-four target configurations, chosen in order to cover all possible values of the average contact order χ (0.2381≤χ≤0.4947 for this system), were encoded and analyzed. The results, obtained by MC simulations, are strongly influenced by geometrical properties of the native configuration, namely χ and the relative number φ of crankshafts-type structures: For χ<0.35 the folding is deterministic, that is, the syntax is able to encode successful sequences: The system presents larger encodability, minimum sequence-target degeneracies and smaller characteristic folding time τ[sub f]. For χ>=0.35 the above results are not reproduced any more: The folding success is severely reduced, showing strong correlation with φ. Additionally, the existence of distinct characteristic folding times suggests that different mechanisms are acting at the same time in the folding process. The results (all obtained from the same single model, under the same "physiological conditions") resemble some general features of the folding problem, supporting the premise that the steric specificities, in association with the entropic forces (hydrophobic effect), are basic ingredients in the protein folding process. © 2001 American Institute of Physics. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index