Proteins are dynamic and interconvert between different conformations to perform their biological functions. Simulation methodology drawing upon principles from classical mechanics - molecular dynamics (MD) simulation - can be used to simulate protein dynamics and reconstruct the conformational ensemble at a level of atomic detail that is inaccessible to experiment. We use the dynamic insight achieved through simulation to enhance our understanding of protein structures solved by X-ray crystallography. Protein X-ray structures provide the most important information for structural biology, yet they depict just a single snapshot of the solution ensemble, which is under the influence of the confined crystal medium. Thus, we ask a fundamental question - how well do static X-ray structures represent the dynamic solution state of a protein? To understand how the crystal environment affects both global and local protein conformational dynamics, we consider two model systems. We first examine the variation in global conformation observed in several solved X-ray structures of the λ Cro dimer by reconstructing the solution ensemble using the replica exchange enhanced sampling method, and show that one X-ray conformation is unstable in solution. Subsequent simulation of Cro in the crystal environment quantitatively assesses the strength of packing interfaces and reveals that mutation in the lattice affects the stability of crystal forms. We also evaluate the Cro models solved by nuclear magnetic resonance spectroscopy and demonstrate that they represent unstable solution states. In addition to our studies of the Cro dimer, we investigate the effect of crystal packing on side-chain conformational dynamics through solution and crystal MD simulation of the HIV microbicide Cyanovirin-N. We find that long, polar surface side-chains can undergo a strong reduction in conformational entropy upon incorporation into crystal contacts, which supports the application of surface engineering to facilitate protein crystallization. Finally, we outline a general framework for using network visualization to aid in the functional interpretation of conformational ensembles generated from MD simulation. Our results will enhance the understanding of X-ray data in establishing protein structure-function-dynamics relationships.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/255200 |
| Date | January 2012 |
| Creators | Ahlstrom, Logan Sommers |
| Contributors | Miyashita, Osamu, Brown, Michael, Monti, Oliver, Sanov, Andrei, Tama, Florence, Miyashita, Osamu |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | text, Electronic Dissertation |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
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