Some problems in protein structure pattern matching

Reliable methods are needed to obtain structural information on proteins encoded in the genome in the absence of high sequence homology. NMR residual dipolar couplings have the potential to provide rapid structural information for proteins in the solution state. In Chapter 2, we describe a novel approach to the structural interpretation of dipolar couplings based on structural motif pattern recognition, where a predefined gapless structural template for a motif is used to search a set of residual dipolar couplings for good matches. We demonstrate the applicability of the method using synthetic and experimental data.; In Chapter 3, we describe an approach to the construction of protein backbone folds using experimental dipolar couplings based on a bounded tree search through a structural database. We filter out false positives via an overlap similarity measure that insists that protein fragments assigned to overlapping regions of the sequence must have self-consistent structures. This greatly increases the robustness of our method and allows us to determine a backbone fold using only residual dipolar coupling data obtained from one ordering medium.; To what extent there exist structurally similar fragments in the database of known structures for short fragments of a novel protein is fundamentally important to the above approach in Chapter 3 and for other fragment-based methods to construct novel protein structures. In Chapter 4, by comparing structures of fragments from known proteins, we found that the probability is over 96% that there exists a similar fragment for seven- and nine-residue loop fragments, while for 15-residue fragments there is a 91% probability that a fragment within 2 A RMSD exists. That leads to our work in the last chapter to predict loop structures using fragments in the database for 15-residue loops. We first select fragments similar to the native from a fragment database with a statistical filter, then attach the fragments to the protein frame, followed by sidechain placement and energy evaluation. We obtained good to medium loop prediction results 7 out of 12 target loops.