Probabilistic Algorithms for Modeling Protein Structure and Dynamics
Date
2015
Authors
Molloy, Kevin Patrick
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Abstract
Specifically, this thesis addresses three main problems that permeate protein model- ing research. The first problem, known as “from-structure-to-function,” asks how to infer the function of a protein from knowledge of its active structure. The second problem, known as “from-sequence-to-structure,” relates to the open question of how to predict the biologically-active structure of a protein when provided information on the identities and or- der of constitutive building blocks. The third problem advances the current computational treatment of proteins to alleviate assumptions of their rigidity and instead model them as dynamic macromolecules switching between structures to tune their biological activity. The objective here is to model protein dynamics efficiently by computing the molecular motions employed in structural transitions among diverse functionally-relevant states of a protein.
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Keywords
Computer science, Robotics, Computational biology, Protein motion, Stochastic optimization