Herein, we develop a statistical framework that is not affected by the parameters used in the structural comparison process, and which takes into account the individual properties of the query motif. We test our statistical model, coupled with a successful structural search and comparison algorithm (Match Augmentation), on a dataset consisting of 20 structural motifs representing a range of distinct enzymatic active sites in un-mutated protein structures. We find that our approach exhibits high sensitivity and reasonable specificity. We also apply the approach to a real biological problem in an effort to predict a possible function of a protein, called Rad21, involved in chromosome segregation.Unfortunately, experimental methods for protein function identification and small ligand cross-reactivity assays remain expensive and ... Chen et al, 2005; Stark et al, 2003) can, at least in theory, guide or in some cases replace wet-lab experimental approaches (Hermann et al, 2007). ... These methods seek to identify functional similarity by seeking instances of chemical and geometric similarity (matches)anbsp;...
|Title||:||Statistical Models in Protein Structural Alignments|
|Publisher||:||ProQuest - 2008|