Conformational Ensembles from Experimental Data and Computer Simulations

Conformational Ensembles from Experimental Data and Computer Simulations

Poster Abstracts

34-POS Board 34 Multiscale simulations of partially disordered systems: Representing environment-induced helix-coil transitions Christoph Globisch 1 , Cahit Dalgicdir 2 , Mehmet Sayar 3 , Christine Peter 1 . 1 University of Konstanz, Konstanz, Germany, 2 University of Darmstadt, Darmstadt, Germany, 3 Koç University, Istanbul, Turkey. Coarse grained (CG) models are widely used to study peptide self-assembly and nanostructure formation. One of the recurrent challenges in CG modeling is the problem of limited transferability. A crucial question for peptides is whether a model reproduces the molecule's conformational response to a change in its molecular environment. Examples are conformational transitions between a rather disordered and an ordered state upon a change in pH value or due to the presence of a soft apolar/polar interface. To handle such transitions CG models mostly utilize auxiliary interactions to aid secondary structure formation. Such interactions take care of properties of the real system that are per se lost in the coarse graining process such as dihedral- angle correlations along the backbone or backbone hydrogen bonding. Since the CG models are designed to emphasize certain conformational propensities they may destroy the ability of the model to respond to stimuli and environment changes. This points out how important it is to investigate whether they impede transferability. To analyze such processes in combined atomistic/CG manner a common characterization of the shallow conformational free energy landscapes is needed which is dominated by a huge number of metastable and often ill-defined minima. Dimensionality reduction methods such as multidimensional scaling-like embedding (sketch-map) can be applied to compare the phase space sampled at both resolutions (atomistic/CG), either to judge the success of elevated sampling techniques and possibly guide further simulations, or to monitor the response of the systems to external stimuli.

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