A new configurational bias scheme for sampling supramolecular structures

TL;DR

This paper introduces a novel simulation algorithm that efficiently samples reconfigurable supramolecular structures by combining configurational bias Monte Carlo with multi-scale modeling, enabling detailed analysis of complex polymer networks.

Contribution

The paper presents a new configurational bias Monte Carlo scheme that allows topology changes in supramolecular structures, integrating coarse-grained simulations with experimental free energy data.

Findings

Successfully applied to DNA coated colloids to compute hybridization free energy.

Analyzed receptor-ligand binding on polymers and surface interactions.

Results agree with mean field theoretical predictions.

Abstract

We present a new simulation scheme which allows an efficient sampling of reconfigurable supramolecular structures made of polymeric constructs functionalized by reactive binding sites. The algorithm is based on the configurational bias scheme of Siepmann and Frenkel and is powered by the possibility of changing the topology of the supramolecular network by a non-local Monte Carlo algorithm. Such plan is accomplished by a multi-scale modelling that merges coarse-grained simulations, describing the typical polymer conformations, with experimental results accounting for free energy terms involved in the reactions of the active sites. We test the new algorithm for a system of DNA coated colloids for which we compute the hybridisation free energy cost associated to the binding of tethered single stranded DNAs terminated by short sequences of complementary nucleotides. In order to demonstrate the versatility of our method, we also consider polymers functionalized by receptors that bind a surface decorated by ligands. In particular we compute the density of states of adsorbed polymers as a function of the number of ligand-receptor complexes formed. Such a quantity can be used to study the conformational properties of adsorbed polymers useful when engineering adsorption with tailored properties. We successfully compare the results with the predictions of a mean field theory. We believe that the proposed method will be a useful tool to investigate supramolecular structures resulting from direct interactions between functionalized polymers for which efficient numerical methodologies of investigation are still lacking.