Predicting protein structure using its primary sequence has always been a
challenging topic in biochemistry. Although it seems as simple as finding the minimal
energy conformation, it has been quite difficult to provide an accurate yet reliable
solution for the problem. On the one hand, the lack of understanding of the hydrophobic
effect as well as the relationship between different stabilizing forces, such as
hydrophobic interaction, hydrogen bonding and electronic static interaction prevent the
scientist from developing potential functions to estimate free energy. On the other hand,
structure databases are limited with redundant structures, which represent a noncontinuous,
sparsely-sampled conformational space, and preventing the development of
a method suitable for high-resolution, high-accuracy structure prediction that can be
applied for functional annotation of an unknown protein sequence. Thus, in this study,
we use molecular dynamics simulation as a tool to sample conformational space.
Structures were generated with physically realistic conformations that represented the
properties of ensembles of native structures. First, we focused our study on the relationship among different factors that stabilize protein structure. Using a wellcharacterized
mutation system of the B-hairpin, a fundamental building block of protein,
we were able to identify the effect of terminal ion-pairs (salt-bridges) on the stability of
the beta-hairpin, and its relationship with hydrophobic interactions and hydrogen bonds. In
the same study, we also correlated our theoretical simulations qualitatively with
experimental results. Such analysis provides us a better understanding of beta-hairpin
stability and helps us to improve the protein engineering method to design more stable
hairpins. Second, with large-scale simulations of different representative protein folds,
we were able to conduct a fine-grained analysis by sampling the continuous
conformational space to characterize the relationship among backbone conformation,
side-chain conformation and side-chain packing. Such information is valuable for
improving high-resolution structure prediction. Last, with this information, we
developed a new prediction algorithm using packing information derived from the
conserved relative packing groups. Based on its performance in CASP7, we were able to
draw the conclusion that our simulated dataset as well as our packing-oriented prediction method are useful for template based structure prediction.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2009-12-7234 |
| Date | 2009 December 1900 |
| Creators | Qu, Xiaotao |
| Contributors | Tsai, Jerry, Scholtz, Martin |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | application/pdf |
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