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Protein folding poses unique challenges for large, disordered proteins due to the low resolution of structural data accessible in experiment and on the basis of short time scales and limited sampling attainable in computation. Such molecules are uniquely suited to accelerated-sampling molecular dynamics algorithms due to a flat-energy landscape. We apply these methods to report here the folded structure in water from a fully extended chain of tropoelastin, a 698-amino acid molecular precursor to elastic fibers that confer elasticity and recoil to tissues, finding good agreement with experimental data. We then study a series of artificial and disease-related mutations, yielding molecular mechanisms to explain structural differences and variation in hierarchical assembly observed in experiment. The present model builds a framework for studying assembly and disease and yields critical insight into molecular mechanisms behind these processes. These results suggest that proteins with disordered regions are suitable candidates for characterization by this approach.

Molecular model of human tropoelastin and implications of associated mutations