Two-Component Polypeptides Modeled with Effective Pair Potentials

Abstract

We present Monte Carlo simulations performed within a model based on a set of distance-dependent effective potentials which are used to describe the interactions between a pair of distinct amino acids. These effective potentials are extracted from experimental correlation functions through the Ornstein-Zernike equations and adequate closure approximations. We focus our attention on the sequences of two specific residues, namely, alanine and glycine. The studied sequences are (a) (Ala)(12)-(Gly)(4)-(Ala)(12) and (b) three interacting chains of alternating alanines and glycines (with five residues per chain). The resulting structures are combinations of known secondary structures. More importantly, we verify that our simulated structures are in thermodynamic equilibrium by means of an estimation of the density of states.

Photochromism from wavelength-selective colloidal phase segregation

“…As shown in Supplementary Fig. 5 , the radial distribution function g ( r ) can be calculated from scores of statistical location information from the recorded data, according to the general expression equation ( 13 ) 49 – 51 . where r is separation distance, N ( r ) is the number of colloidal pairs at separation distance r , N is the total number of colloids in each frame, A is the area of the frame, ρ = N/A is the number density of the particles, 2 πr d r is the bin area.…”

Extraction of an Effective Pairwise Potential for Amino Acids

“…So far, most statistical analyses have used a representative set of proteins. Usually, protein representatives are chosen by specifying an upper limit for sequence identity [47] or structural similarity [48,49]. However, it is not clear what value is best as an upper limit of similarity in protein representatives.…”