Date of Award
Physics and Astronomy
Electrostatics, Evolution, Intrinsically disordered proteins, Sequence patterning metrics, Theoretical polymer physics, Thermal stability
The central dogma of molecular biology dictates that a DNA sequence codes for an RNA sequence, which in turn codes for a sequence of amino acids that comprises a protein. Proteins are responsible with performing myriad functions within living organisms and most proteins require a folded structure in order to perform their function. The protein's structure is the direct link from sequence to function. This is known as the sequence - structure - function paradigm. However, this does not mean that the unfolded state is unimportant. In order to properly model the stability of the folded state, one needs to pay attention to the thermodynamics of the unfolded state, in particular electrostatics. We are able to study the role of electrostatics in protein stability by using all-atom molecular dynamics (MD) and Monte-Carlo (MC) simulations. A global strategy emerges where proteins have improved their thermal stability using electrostatics, when modifying electrostatics is not harmful to their function.
A recently discovered set of proteins can perform their function without a folded structure. Instead, these proteins form a disordered conformational ensemble of states. These proteins are known as Intrinsically Disordered Proteins (IDPs) and are both biologically functional and abundant. Recent advances in heteropolymer theory unveiled a powerful set of sequence patterning metrics that bridge the gap between intra-molecular interaction and chain conformation. Specifically - charge patterning has been identified as a dominant mechanism behind IDP conformation. These mathematical relations have also helped us explore the conformational response to biologically relevant variables, like pH, salt, and post-translational modifications (PTMs). I present our work studying these sequence based metrics utilizing theoretical polymer physics, all-atom simulation, and experimental data, when available.
Functionally similar IDPs often have little sequence similarity. This is in stark contrast to folded proteins which can easily be functionally assigned by directly comparing their sequences. The question is then raised - how do we draw the connection between IDP sequences to their function? This work then highlights how sequence specific metrics lead to a physical understanding of the mechanisms behind IDP conformation and function. We notice the emergence of a sequence metric - ensemble - function paradigm for IDPs.
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Huihui, Jonathan, "Modeling Disorder in Proteins Yields Insights into the Evolution of Stability and Function" (2021). Electronic Theses and Dissertations. 1940.
Received from ProQuest