Computational modeling of structural heterogeneity in folded proteins
- Proteins are biomolecules that play a key role in a wide diversity of vital functions, such as metabolism and signal transmission. Each protein is a linear chain of amino acids that folds into a flexible three-dimensional structure. Protein's flexibility is widely believed to be essential for its function. Motion of a protein occurs at timescales that span several orders of magnitude. Thermal fluctuations, which occur in picoseconds, are small-amplitude, uncorrelated, harmonic motions of the individual atoms. In contrast, conformational deformations closely related to the protein's function occur in microseconds to milliseconds. These slow deformations are usually large-scale, correlated, anharmonic motions that correspond to transitions between meta-stable states, such as binding and non-binding states. In this dissertation we are mainly interested in modeling structural heterogeneity associated with such slow deformations. This dissertation presents new computational methods to study the flexibility of folded protein in the context of three important biological problems: (a) Loop sampling, (b) Interpretation of electron density maps, and (c) Determination of allosteric pathways. Computational modeling of structural heterogeneity in the folded state of a protein is a challenging problem, mainly because of the high-dimensionality of the protein's conformation space and the very small relative volume of its feasible motion space. Although our methods are specific to each of the three problems, they share the same sample and select approach: they combine efficient sampling algorithms that allow us to represent structural heterogeneity in a folded protein by a collection of sampled conformations and selection algorithms that allow us to reliably pick the sampled conformations that provide a solution to the problem. This dissertation demonstrates the power of geometric computation and efficient sampling to model structural heterogeneity in the folded protein.
|Type of resource
|electronic; electronic resource; remote
|1 online resource.
|Stanford University, Department of Mechanical Engineering
|Statement of responsibility
|Submitted to the Department of Mechanical Engineering.
|Thesis (Ph.D.)--Stanford University, 2010.
- © 2010 by Ankur Dhanik
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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