Coarse grained (CG) simulation models have become very popular tools to accelerate the sampling of complex, high-dimensional free energy landscapes and to reach length and timescales that are inaccessible to simulations at atomistic resolution. Unfortunately, the reduced resolution description naturally results in transferability and representability limitations. This means that the CG model does not reproduce all properties of the system, in particular capturing the system’s response to a change in thermodynamic state point or system composition is often problematic. One aspect of this more general representability challenge is the question whether a CG model correctly describes all relevant conformational states of a bio-macromolecule (peptide, protein, RNA, …) as well as the transition between these states. Related to this is one crucial transferability question, namely whether a system shows the correct conformational response to a change in a molecule’s environment, resulting in a shift of the population of conformationas states depending on external conditions. Examples for such scenarios are conformational transitions in peptides or proteins between a disordered and an ordered state upon a change in pH value or due to the presence of a soft apolar/polar interface. In this talk I will address various problems related to the representation of conformational and configurational states in CG simulations and the consistency of sampling of high-dimensional free energy landscapes in different simulation models (e.g. with an atomistic and a CG level of resolution). It should be noted that in particular for (only) partially ordered systems such as intrinsically disordered proteins or polymorphous/polyamorphous materials the characterization of states becomes becomes a challenge on its own that precludes such a comparison.
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