The Dead-End Elimination method was used to identify 40 low energy microconformations of 16 tryptophan residues in eight proteins. Single Trp-mutants of these proteins all show a double- or triple-exponential fluorescence decay. For ten of these lifetimes the corresponding rotameric state could be identified by comparing the bimolecular acrylamide quenching constant (k(q)) and the relative solvent exposure of the side chain in that microstate. In the absence of any identifiable quencher, the origin of the lifetime heterogeneity is interpreted in terms of the electron transfer process from the indole C epsilon 3 atom to the carbonyl carbon of the peptide bond. Therefore it is expected that a shorter [C epsilon 3-C[double bond]O] distance leads to a shorter lifetime as observed for these ten rotamers. Applying the same rule to the other 30 lifetimes, a link with their corresponding rotameric state could also be made. In agreement with the theory of Marcus and Sutin, the nonradiative rate constant shows an exponential relationship with the [C epsilon 3-C[double bond]O] distance for the 40 datapoints.

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In this study, the feasibility of spatial filter velocimetry (SFV) as Process Analytical Technology tool for the in-line monitoring of the particle size distribution during top spray fluidized bed granulation was examined. The influence of several process (inlet air temperature during spraying and drying) and formulation variables (HPMC and Tween 20 concentration) upon the particle size distribution during processing, and the end product particle size distribution, tapped density and Hausner ratio was examined using a design of experiments (DOE) (2-level full factorial design, 19 experiments). The trend in end granule particle size distributions of all DOE batches measured with in-line SFV was similar to the offline laser diffraction (LD) data. Analysis of the DOE results showed that mainly the HPMC concentration and slightly the inlet air temperature during drying had a positive effect upon the average end granule size. The in-line SFV particle size data, obtained every 10 s during processing, further allowed to explain and better understand the (in)significance of the studied DOE variables, which was not possible based on the LD data as this technique only supplied end granule size information. The variation in tapped density and Hausner ratio among the end granules of the different DOE batches could be explained by their difference in average end granule size. Univariate, multivariate PLS and multiway N-PLS models were built to relate these end granule properties to the in-line measured particle size distribution. The multivariate PLS tapped density model and the multiway N-PLS Hausner ratio model showed the highest R 2 values in combination with the lowest RMSEE values (R 2 of 82% with an RMSEE of 0.0279 for tapped density and an R 2 of 52% with an RMSEE of 0.0268 for Hausner ratio, respectively).

We investigated the native-state dynamics of the Bacillus caldolyticus cold-shock protein mutant Bc-Csp L66E, using fluorescence and appropriate molecular dynamics methods. Two fluorescence lifetimes were found, the amplitudes of which agree very well with tryptophan rotamer populations, obtained from parallel tempering calculations. Rotamer lifetimes were predicted by transition-state theory from high-temperature simulations. Transition pathways were extracted from the transition rates between individual rotameric states. The molecular dynamics also reveal the loop fluctuations in the native state.

Fluid bed granulation is a batch process, which is characterized by the processing of raw materials for a predefined period of time, consisting of a fixed spraying phase and a subsequent drying period. The present study shows the multivariate statistical modeling and control of a fluid bed granulation process based on in-line particle size distribution (PSD) measurements (using spatial filter velocimetry) combined with continuous product temperature registration using a partial least squares (PLS) approach. Via the continuous in-line monitoring of the PSD and product temperature during granulation of various reference batches, a statistical batch model was developed allowing the real-time evaluation and acceptance or rejection of future batches. Continuously monitored PSD and product temperature process data of 10 reference batches (X-data) were used to develop a reference batch PLS model, regressing the X-data versus the batch process time (Y-data). Two PLS components captured 98.8% of the variation in the X-data block. Score control charts in which the average batch trajectory and upper and lower control limits are displayed were developed. Next, these control charts were used to monitor 4 new test batches in real-time and to immediately detect any deviations from the expected batch trajectory. By real-time evaluation of new batches using the developed control charts and by computation of contribution plots of deviating process behavior at a certain time point, batch losses or reprocessing can be prevented. Immediately after batch completion, all PSD and product temperature information (i.e., a batch progress fingerprint) was used to estimate some granule properties (density and flowability) at an early stage, which can improve batch release time. Individual PLS models relating the computed scores (X) of the reference PLS model (based on the 10 reference batches) and the density, respectively flowabililty as Y-matrix, were developed. The scores of the 4 test batches were used to examine the predictive ability of the model.