Graduation Year


Document Type




Degree Granting Department

Biology (Cell Biology, Microbiology, Molecular Biology)

Major Professor

Gary W. Daughdrill


Dynamics, Evolution, Intrinsically Disordered Proteins, NMR, Structural biology, Structure


in numerous disease states, including cancers and neurodegenerative diseases. All proteins are dynamic in nature, occupying a range of conformational flexibilities. This inherent flexibility is required for their function, with ordered proteins and IDPs representing the least flexible, and most flexible, respectively. As such IDPs possess little to no stable tertiary or secondary structure, they instead form broad ensembles of heterogeneous structures, which fluctuate over multiple time scales. Although IDPs often lack stable secondary structure they can assume a more stable structure in the presence of their binding partners in a coupled folding binding reaction.

The phenomenon of the dynamic behavior of IDPs is believed to confer several functional advantages but remains poorly understood. To that end the dynamic and structural properties of a family of IDPs - p53 transactivation domains (TAD) was measured and compared with the sequence divergence. Interestingly we were able to find stronger correlations between the dynamic properties and the sequence divergence than between the structure and sequence, suggesting that the dynamic properties are the primary trait being


conserved by evolution. These correlations were strongest within clusters of the IDPs that correlated with known protein binding sites. Additionally, we show strong correlations between the several available disorder predictors and the backbone dynamics of this family of IDPs. This indicates the potential of predicting the dynamic behavior of proteins, which may be beneficial in future drug design.

The limited number of atomic models currently determined for IDPs hampers understanding of how their amino acid sequences dictate the structural ensembles they adopt. The current dearth of atomic models for IDPs makes it difficult to test the following hypotheses:

1. The structural ensembles of IDPs are dictated by local interactions.

2. The structural ensembles of IDPs will be similar above a certain sequence identity threshold.

Based on the premise that sequence determines structure, structural ensembles were determined and compared for a set of homologous IDPs. Utilizing orthologues allows for the identification of important structural features and behaviors by virtue of their conservation. A new methodology of creating ensembles was implemented that broadly samples conformational space. This allowed us to find recurring local structural features within the structural ensembles even between the more distantly related homologues that were processed. This method of ensemble creation is also the first method to show convergence of secondary structural characteristics between discrete ensembles.