Nmr Structure Refinement by Nonlinear Estimation

We will demonstrate the applicability of nonlinear recursive filtering techniques for the improvedmolecular structures from NMR data. These techniques evolved from well-known and widely used estimatfor precise navigation and control of aircraft and satellites. Through preliminary examples, the metfavorably with existing NMR approaches and converges properly while maintaining reasonable computatiAdditionally, the algorithms are robust to major gaps in measured data and generate a set of structucompatible with the data. The algorithm takes particular advantage of the structure of the NMR data,highorder multiple-local-minima optimization process by a series of simple non-linear recursive stepnew tool that promises to improve the resolution of refined structures. Direct refinement through thbecomes practical for very large molecules by a refinement wave implementation that scales linearlystructural parameters. In Phase I, the methods will be tested on large protein molecules (200 residuwith various error models. In Phase II, the estimation algorithms will be modified as necessary andcommercial structure determination code such as X-PLOR.