![]() ![]() In contrast to proteins in general, mutational effects in proteases are not additive and their magnitude is strongly dependent on the location of the mutation. However, rather than stabilizing the whole protein against global unfolding, only a small region has to be protected against local unfolding. Despite the particular nature of the thermal denaturation process, normal rules for protein stability can be applied to NPs. From this it has been conjectured that local unfolding of (surface) loops, which renders the protein susceptible to autolysis, is the rate-limiting step. It has been shown that this denaturation process is independent of the protease activity and concentration and that the inactivation follows first-order kinetics. At elevated temperatures NPs are irreversibly inactivated as a result of autolysis. Many stabilizing mutations were predicted and produced: improvement of hydrogen bonding, exclusion of buried water molecules, capping helices, improvement of hydrophobic interactions and entropic stabilization have been applied successfully. Predictions were made using several novel computational techniques, such as position-specific rotamer searching, packing quality analysis and property-profile database searches. The NP models have been used for the prediction of site-directed mutations aimed at improving the thermostability of the enzymes. ![]() Also a model-building by mutagenesis' strategy was used, in which mutants were designed just to shed light on parts of the structures that were particularly hard to model. Several new techniques have been developed to improve the model-building procedures. The three-dimensional (3D) structures of several of these enzymes have been modelled on the basis of the crystal structures of the NPs of B. Prediction and analysis of structure, stability and unfolding of thermolysin-like proteasesīacillus neutral proteases (NPs) form a group of well-characterized homologous enzymes, that exhibit large differences in thermostability. Feasibility of the method is shown for processing flight data from time- varying nonstationary test points. ![]() Guidelines and computation times are presented to show the efficiency and practical aspects of these procedures for on-line implementation. The F-18 High Alpha Research Vehicle aeroservoelastic flight test data demonstrates improved robust stability prediction by extension of the stability boundary beyond the flight regime. Computation of robust stability margins for stability boundary prediction depends on uncertainty descriptions derived from the data for model validation. Parametric estimates of modal stability are also extracted using the wavelet transform. Nonparametric wavelet processing of data is used to reduce the effects of external disturbances and unmodeled dynamics. The conservatism of the robust stability margins is reduced with parametric and nonparametric time- frequency analysis of flight data in the model validation process. Wavelet analysis for filtering and system identification has been used to improve the estimation of aeroservoelastic stability margins. On-Line Robust Modal Stability Prediction using Wavelet Processing
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