title: Minimalist Model for the Dynamics of Helical Polypeptides: A Statistic-Based Parametrization.
abstract: Low-resolution models are often used to address macroscopic time and size scales in molecular dynamics simulations of biomolecular systems. Coarse graining is often coupled to knowledge-based parametrization to obtain empirical potentials able to reproduce the system thermodynamic behavior. Here, a minimalist coarse grained (GC) model for the helical structures of proteins is reported. A knowledge-based parametrization strategy is coupled to the explicit inclusion of hydrogen-bonding-related terms, resulting in an accurate reproduction of the structure and dynamics of each single helical type, as well as the internal conformational variables correlation. The proposed strategy of basing the force field terms on real physicochemical interactions is transferable to different secondary structures. Thus, this work, though conclusive for helices, is to be considered the first of a series devoted to the application of the knowledge-based, physicochemical model to extended secondary structures and unstructured proteins.
authors.affiliation: NEST, Istituto Nanoscienze-CNR and Scuola Normale Superiore , Piazza San Silvestro 12-56127 Pisa, Italy.
authors.forename: Giulia Lia Beatrice
authors.initials: GL
authors.lastname: Spampinato
authors.affiliation: Center for Nanotechnology and Innovation @NEST, Istituto Italiano di Tecnologia , Piazza San Silvestro 12-56127 Pisa, Italy.
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Maccari
authors.affiliation: NEST, Istituto Nanoscienze-CNR and Scuola Normale Superiore , Piazza San Silvestro 12-56127 Pisa, Italy.
authors.forename: Valentina
authors.initials: V
authors.lastname: Tozzini