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Using MSMs to study the effect of tryptophan mutations on folding

posted Apr 26, 2015, 2:29 PM by Vincent Voelz   [ updated Apr 26, 2015, 2:30 PM ]
In a new paper, we describe our efforts to use Markov State Models (MSMs) to study the how tryptophan mutations affect the folding and conformational dynamics of a series of model beta-hairpin peptides.  

This work represents the most extensive explicit-solvent simulations of β-hairpins to date (9.4 ms in aggregate), a feat made possible through the Folding@home distributed computing platform. The large-scale trajectory data made possible the construction of high-resolution MSMs, where we used the same set of metastable conformational states for multiple sequences.  Thus, we could ask how tryptophan mutations perturb the transitions between individual states, as well as the global folding kinetics and stability.

Our study predicts that sequences with tryptophans near the hairpin termini (a so-called beta-cap motif) fold much more cooperatively and are more stable than the “wild-type” sequence, consistent with experimental studies.   Also consistent with experiment, we find that a sequence with four tryptophans (trpzip4) has slower folding kinetics than wild-type.  Our models show that this is in part due to many non-native “traps” that slow down folding, consisting of many inverted topologies of the hairpin.   The existence of these traps may help explain why tryptophan-rich proteins are rare in nature, despite their ability of tryptophan to stabilize folds.  Overall, we believe that MSM-based studies like this one are a great tool for studying the relationship of sequence to structure and function, and we expect them to find increasing relevance toward protein design.