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December 3, 2015 15:53
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| \chapter{ProIntVar}\label{Chapter2} | |
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| \section{Summary}\label{Chapter-Summary} | |
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| In this chapter I will describe in depth the main computational framework developed in this project to allow the study of protein structures, protein sequences and genetic variation. Thus this chapter focuses on the methods developed to process and combine structure and sequence data to enable the study of genetics variant on protein interaction interfaces. | |
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| \section{Introduction}\label{Chapter-Introduction} | |
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| \section{Methods}\label{Chapter-Methods} | |
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| \subsection{Generating biological assemblies} | |
| The number of protein interactions observed in the protein structures was improved by using biological assemblies from PISA. Biological assemblies are ranked in PISA by applying a set of operations to the crystallographic asymmetric units and have been shown to provide a rich source of novel protein-protein interfaces that are not considered when using the coordinates deposited in the PDBe (Jefferson et al., 2006). Unsurprisingly, the majority of structures in the PDBe are monomeric, as compared to the structures in PISA, which are mainly dimeric. Nonetheless, the scope of the PPI analysis is currently limited to the complexes for which there are structures of directly bound protein partners in the PDBe or PISA. | |
| Expand this and add a figure. | |
| \subsection{Defining protein interaction interfaces} | |
| \subsection{Mapping protein structure to protein sequence} | |
| \subsection{Mapping protein genetic variation to protein sequence} | |
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| \section{Results and discussion}\label{Chapter-Results-Discussion} | |
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| \section{Conclusions and future work}\label{Chapter-Conclusions-Future} | |
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