Analysis and simulation of frontal affinity chromatography of proteins

Early potential evaluation of lead compounds from a DNA-encoded library by the determination of their thermodynamics through a chromatographic method based on immobilized β2-adrenoceptor

Early potential evaluation of lead compounds is critical to decrease downstream lead-optimization cycle times and clinical attrition rates for drug development. This increasingly necessitates the methodologies for accurately evaluating the potential compounds. This work immobilized β₂-adrenoceptor (β₂-AR) onto microspheres through Halo-tag mediated reaction. Characterizing the resulting microspheres by elemental and functional analysis, we utilized the immobilized receptor to determine the thermodynamics of terbutaline, tulobuterol, clorprenaline, salbutamol, and methoxyphenamine. The association constants correlated to their capacity factors on the column containing the immobilized β₂-AR, thus providing a possibility for early potential evaluation of lead compounds from complex matrices like a DNA-encoded library. By this model, the lead compound (XC267) was predicted to have an association constant higher than terbutaline, salbutamol, and methoxyphenamine, but lower than tulobuterol and clorprenaline. The binding interaction between XC267 and β₂-AR is a spontaneous endothermic process with an association constant of (6.62 ± 0.13) × 10⁴ M^-1 at 37 °C. The change of Gibbs free energy(ΔG^θ), enthalpy change (ΔH^θ), and entropy change (ΔS^θ) was -28.49 kJ/mol, -10.58 kJ/mol, and 57.79 J/moL·K at 37 °C. By the semi-empirical rule of Ross, the driving force of the interaction between XC267 and β₂-AR was electrostatic interaction. Such binding force was also achieved by molecular docking. These results suggested that XC267 is a candidate to treat asthma by specific binding to β₂-AR. We reasoned that receptor chromatography is able to the early potential evaluation of lead compounds from complex matrices.

Use of the Dispersion Coefficient as the Sole Structural Parameter to Model Membrane Chromatography

The characterization and modelling of membrane chromatography processes require the axial dispersion coefficient as a relevant and effective intrinsic property of porous media, instead of arbitrary assumptions on pore size distribution. The dispersion coefficient can be easily measured by experiments completely independent of chromatographic tests. The paper presents the prediction of experimentally obtained breakthrough curves using B14-TRZ-Epoxy2 membranes as a test case; the mathematical model implemented is based on the use of the experimentally measured axial dispersion coefficient as an input parameter. Application of the model and its comparison with the data demonstrate that alternative ways of explaining the shape of breakthrough curves, based on unverified assumptions about the membrane pore size distribution, are not feasible and not effectively supported by experimental evidence. In contrast, the axial dispersion coefficient is the only measurable parameter that accounts for all the different contributions to the dispersion phenomenon that occurs in the membrane chromatography process, including the effects due to porous structure and pore size distribution. Therefore, mathematical models that rely on the mere assumption of pore size distribution, regardless of the role of the axial dispersion coefficient, are in fact arbitrary and ultimately misleading.

Application of agent-based system for bioprocess description and process improvement

Modeling plays an important role in bioprocess development for design and scale-up. Predictive models can also be used in biopharmaceutical manufacturing to assist decision-making either to maintain process consistency or to identify optimal operating conditions. To predict the whole bioprocess performance, the strong interactions present in a processing sequence must be adequately modeled. Traditionally, bioprocess modeling considers process units separately, which makes it difficult to capture the interactions between units. In this work, a systematic framework is developed to analyze the bioprocesses based on a whole process understanding and considering the interactions between process operations. An agent-based approach is adopted to provide a flexible infrastructure for the necessary integration of process models. This enables the prediction of overall process behavior, which can then be applied during process development or once manufacturing has commenced, in both cases leading to the capacity for fast evaluation of process improvement options. The multi-agent system comprises a process knowledge base, process models, and a group of functional agents. In this system, agent components co-operate with each other in performing their tasks. These include the description of the whole process behavior, evaluating process operating conditions, monitoring of the operating processes, predicting critical process performance, and providing guidance to decision-making when coping with process deviations. During process development, the system can be used to evaluate the design space for process operation. During manufacture, the system can be applied to identify abnormal process operation events and then to provide suggestions as to how best to cope with the deviations. In all cases, the function of the system is to ensure an efficient manufacturing process. The implementation of the agent-based approach is illustrated via selected application scenarios, which demonstrate how such a framework may enable the better integration of process operations by providing a plant-wide process description to facilitate process improvement.

A new general approach to purify proteins from complex mixtures

The selection of chromatography media and their sequential use represent a major difficulty to isolate a single protein from very crude protein extracts. The process described here consists of two main steps: (i) a rational selection of few media from a relatively large collection and (ii) the definition of the sequence of columns to get the best purity of the target protein. From the first step, one sorbent is selected for its properties to capture the protein to purify, regardless whether other protein impurities are also co-adsorbed; then 5-7 other complementary sorbents are identified to remove impurities but without interacting with the target protein under the same buffering conditions. The second step consists in superimposing sorbents under a cascade manner with the sorbent in charge to capture the target protein located in the last position. Non-adsorbed proteins are eliminated in the flowthrough; other impurities are progressively removed by the sorbent sequence and the target protein is finally desorbed and isolated from the last sorbent using an optimized gradient. All operations are performed with a single adsorption buffer for all columns and all monitoring performed by means of mass spectrometry associated with ProteinChip arrays and polyacrylamide gel electrophoresis. Examples of protein isolation/identification from human serum are described namely thyroxin-binding proteins and transferrin. The first is isolated thanks to a series of dye chromatography media, the second (transferrin) using current chromatographic media. In both cases the target proteins were purified at a level estimated of about 95% and 85%, respectively. Isolated proteins were pure enough for the purpose of formal identification by either peptide fingerprinting or sequencing.

Variation analysis of affinity-membrane model based on Freundlich adsorption

The variation analysis of membrane properties including membrane thickness and pore-size was carried out theoretically by using affinity-membrane model based upon the Freundlich adsorption equation. As the percentage variation of membrane thickness and distribution of pore-size increase, we find that (1) the time of total saturation is delayed; (2) the loading capacity at the point of breakthrough are decreased; (3) solute recovery efficiency and ligand utilization efficiency is decreased; (4) the thickness of unused membrane is increased. The results show that even small variations of thickness and distribution of pore size may severely degrade the membrane performance.