<p>Structural bioinformatics deals with the analysis, classification and prediction of three-dimensional structures of biomacromolecules. It is becoming increasingly important as the number of structures is growing rapidly. This thesis describes three studies concerned with protein-function prediction and two studies about protein structure validation.</p><p>New protein structures are often compared to known structures to find out if they have a known fold, which may provide hints about their function. The functionality and performance of eleven fold-comparison servers were evaluated. None of the tested servers achieved perfect recall, so in practise a combination of servers should be used.</p><p>If fold comparison does not provide any hints about the function of a protein, structural motif searches can be employed. A survey of left-handed helices in known protein structures was carried out. The results show that left-handed helices are rare motifs, but most of them occur in active or ligand-binding sites. Their identification can therefore help to pinpoint potentially important residues.</p><p>Sometimes all available methods fail to provide hints about the function of a protein. Therefore, the potential of using docking techniques to predict which ligands are likely to bind to a particular protein has been investigated. Initial results show that it will be difficult to build a reliable automated docking protocol that will suit all proteins.</p><p>The effect of various phenomena on the precision of accessible surface area calculations was also investigated. The results suggest that it is prudent to report such values with a precision of 50 to 100 Å<sup>2</sup>.</p><p>Finally, a survey of register shifts in known protein structures was carried out. The identified potential register shifts were analysed and classified. A machine-learning approach ("rough sets") was used in an attempt to diagnose register errors in structures.</p>
| Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:uu-7593 |
| Date | January 2007 |
| Creators | Novotny, Marian |
| Publisher | Uppsala University, Department of Cell and Molecular Biology, Uppsala : Acta Universitatis Upsaliensis |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Doctoral thesis, comprehensive summary, text |
| Relation | Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, 1651-6214 ; 275 |
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