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A temperature-insensitive method for measuring protein concentration in aqueous solutions using near-infrared spectroscopy is described. The method, which is based on identification of the net analyte signal of single-beam spectra, can be calibrated using a single protein absorbance measurement and is thus well suited for crystallization monitoring where the quantity of protein is limited. The method is applied to measurements of glucose-isomerase concentration in a sodium phosphate buffer that is actively varied over the temperature range of 4-24 degrees C. The standard error of prediction using the optimized spectral range of 4670-4595 cm(-1) is 0.12 mg/mL with no systematic trend in the residuals with solution temperature. The method is also applied to previously collected spectra of hen egg-white lysozyme and yields a standard error of prediction of 0.14 mg/mL. Spectra sampled at discrete wavelengths can also be used for calibration and prediction with performance comparable to that obtained with spectral bands. A set of four wavelengths are identified that can be used to predict concentrations of both proteins with a standard error less than 0.14 mg/mL.

Digital Fourier filtering is used to produce a temperatureinsensitive univariate calibration model for measuring lysozyme in aqueous solutions. Absorbance spectra over the 5000-4000 cm -1 spectral range are collected for lysozyme standards maintained at 14 °C. These spectra are used to compute the calibration model while a set of spectra collected at temperatures ranging from 4 to 24 °C are used to validate the accuracy of this model. The root-mean-square error of prediction (RMSEP) is 0.279 mg/mL over a tested lysozyme concentration range of 0.036-51.6 mg/mL. The detection limit is 0.68 mg/mL. In addition, multivariate calibration models based on partial least-squares regression (PLS) are evaluated and compared to the results from the univariate model. PLS outperforms the univariate model by providing a RMSEP of 0.090 mg/mL. Analysis of variance showed that both calibration methods effectively eliminate the adverse affects created by variations in solution temperature.Optimized protein crystal growth rates are necessary to provide large, high-quality crystals for X-ray diffraction analysis. Temperature can be used to control crystal growth rates by regulating protein saturation levels and, thereby, controlling the extent of supersaturation. The effectiveness of using temperature to control crystal growth rates has been established for selected proteins for which an appropriate temperature-time profile can be developed. 1,2 Such a profile requires detailed knowledge of the temperature-dependent solubility properties of the protein as well as an understanding of the kinetic parameters that govern nucleation and crystal growth for this protein. Such details are not generally known a priori, thereby limiting the utility of this approach.Alternatively, in situ crystal growth rates can be used to drive a temperature-controlled protein crystallization process. In this method, in situ crystal growth rates are obtained by measuring changes in the soluble protein concentration in real time during the crystallization process. Consumption of soluble protein during crystal formation results in lower soluble protein concentrations. Accurate measurement of the soluble protein concentration permits computation of the crystal growth rate from simple mass balance, and this information can be used as a feedback-control parameter for adjusting system temperature. This approach demands a suitable analytical method to provide accurate in situ protein concentrations in a nondestructive, continuous, and temperature-insensitive manner.Near-infrared (NIR) spectroscopy is proposed as a method for monitoring soluble protein levels in situ during crystallization. Conceptually, the measurement is made by passing a selected beam of NIR radiation through the sample of interest and extracting the desired analytical information from the resulting spectral information. Unlike other analytical methods for protein measurements in aqueous solutions, 3,4 NIR spectroscopic measurements are reagentless and nondestructive. Both of these properties are c...

Proteins possess strong absorption features in the combination range (5000-4000 cm(-1)) of the near infrared (NIR) spectrum. These features can be used for quantitative analysis. Partial least squares (PLS) regression was used to analyze NIR spectra of lysozyme with the leave-one-out, full cross-validation method. A strategy for spectral range optimization with cross-validation PLS calibration was presented. A five-factor PLS model based on the spectral range between 4720 and 4540 cm(-1) provided the best calibration model for lysozyme in aqueous solutions. For 47 samples ranging from 0.01 to 10 mg/mL, the root mean square error of prediction was 0.076 mg/mL. This result was compared with values reported in the literature for protein measurements by NIR absorption spectroscopy in human serum and animal cell culture supernatants.

Large, high-quality protein crystals are required for the structural determination of proteins via X-ray diffraction. In this article, we propose a technique to facilitate the production of such crystals and validate its feasibility through simulations. An analytical method for protein aqueous solution based on a Fourier transform infrared (FTIR) spectroscopy is combined with a temperature control strategy to manipulate the extent of supersaturation during crystal growth, thus impacting crystal quality. The technique requires minimal knowledge about the growth kinetics a priori. The simulations show that, under ideal conditions, the design can be as effective as predesigned temperature programs for crystallization based on known growth kinetics. Two kinds of errors might be encountered with this design. Error in the estimated number of seed crystals can result in a growth rate deviating from the desired one. Nevertheless, the deviation is usually tolerable and system instability is unlikely to occur. Based on the standard error of our FTIR method, errors in concentration measurement are simulated. Measurement error can result in system instability and impair the control algorithm. Such errors may be compensated by limiting the temperature change taken by the control action, or by improving the measurement precision through the use of regressed concentrations. Through simulations, it is shown that the proposed design is practical and represents a significant improvement over the commonly used isothermal crystallization technique.