Multiscale simulation of small peptides: Consistent conformational sampling in atomistic and coarse‐grained models

Abstract

A bottom-up coarse-graining procedure for peptides in aqueous solution is presented, where the interactions in the coarse-grained (CG) model are determined such that the CG peptide samples conformations according to a high-resolution (atomistic) model. It is shown that important aspects of conformational sampling, such as correlated degrees of freedom (DOF) which play an important role in secondary structure formation, can be reproduced in the CG description. In some cases, microscopic structural/conformational details are lost in the coarse-graining process. We show that these "lost" properties can be recovered in a backmapping procedure which reintroduces atomistic DOF into CG structures - as long as the overall conformational sampling of the molecule is correctly represented in the CG level of resolution. Thus, it is possible to link an existing all-atom model of a biomolecular system with a CG description such that after inverse mapping one can recover structures at high resolution with the correctly sampled (according to the atomistic model) conformational properties.

Scalability of Coarse‐Grained Potentials Generated from Iterative Boltzmann Inversion for Polymers: Case Study on Polycarbonates

“…The CG potentials for 3‐mer, 5‐mer, and 10‐mer BPA‐PC melt were obtained by the IBI methodology ,–. In this method the CG potentials were improved in successive iterations.…”

“…Based on the desired system properties one can choose the degree of coarse graining and decide on a method for deriving interbead potentials. In the structure‐based methods (e.g., iterative Boltzmann inversion (IBI),,– inverse Monte Carlo, and Newton inversion methods), the link between the atoms and CG beads is through the effective bonded and nonbonded potentials. In the force matching methods by Voth and co‐workers, the forces in the CG systems are determined such that they are mapped to the corresponding sum of the forces in the corresponding atomistic system.…”

Computational Studies of Protein Aggregation: Methods and Applications

“…These methods are ideal for studying the self-assembly of many identical molecules, as the inter-and intramolecular potentials are typically obtained from a system of fewer molecules (assuming that the optimal potentials do not include direct manybody interactions between several molecules). Many systematic coarse-grained methods have been applied to aggregation (24,55,150,152). 7:48 Carmichael & Shell (24) applied the relative entropy method to the self-assembly of polyalanine, (Ala) 15 .…”

A program for automatically predicting supramolecular aggregates and its application to urea and porphin

“…The selection of aggregates of sufficiently small size to be treated with high‐accuracy methods from a large chunk of molecules is not unambiguous. This is even worse in the case of coarse‐grained simulations as not all methods allow an easy back‐mapping of the coarse structure onto the underlying atomistic structure . A second approach is the explicit sampling of the energy hypersurface of the essential molecular aggregate of interest.…”