Stochastic Prediction of Peptide Secondary Structure Based on Molecular Dynamics Simulation Performed for Nano-second–Effectiveness of the %stickiness Approach Represented by Triangle Map Mode.

Abstract

Nano-second (ns) MD simulations of peptides, which are known to be insufficient to obtain stable structures, were confirmed to provide faint secondary structure (especially, α-helix) images through a novel approach termed triangle map representation of %stickiness (TMR-%σ). %stickiness is a measure formerly introduced to describe dynamic conformation changes of biopolymers. In TMR-%σ representation, the α-helix forming propensity of a peptide was expressed as an off-diagonal dotted line, indicating α-helix intrinsic interactions. The coordinate information derived from %σ and radius of gyration (R_g) of a peptide calculated from ns-MD results could be converted to a probability matrix of secondary peptide structure formation.