RECCR Rensselaer Exploratory Center for Cheminformatics Research

Bioseparations

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Homology Modeling

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Co-PI: Steven Cramer

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Bioseparations

Co-Investigator: Steven Cramer

Professor, Department of Chemical and Biological Engineering Rensselaer Polytechnic Institute

The development of efficient bioseparation processes for the production of high-purity biopharmaceuticals is one of the most pressing challenges facing the pharmaceutical and biotechnology industries today. In addition, high-resolution separations for proteomic applications are becoming increasingly important. Developing elution or displacement methodologies to remove closely related impurities often requires a significant amount of experimentation to find the proper combination of stationary phase material, salt type, pH, gradient conditions and/or displacers to achieve sufficient selectivity and productivity in these separation techniques.

Ion-exchange chromatography is perhaps the most widely employed chromatographic mode in the downstream processing of biomolecules. Generally, ion-exchange chromatography is regarded as occurring due to charge-based interactions between the solute, mobile phase components, and the ligands on the stationary phase. However, in addition to electrostatics, non-specific interactions have also been shown to effect separations in ion-exchange systems (Rahman et al. 1990; Law et al. 1993; Shukla et al. 1998b) . Hydrophobic interaction chromatography (HIC) is another technique that is commonly employed in the biotech industry due to the mild conditions employed relative to the harsh, denaturing conditions used in RPLC. However, almost all QSPR work in HPLC has focused on the adsorption of small molecules in reversed-phase systems. Our group has been instrumental in the development of QSRRs for the a priori prediction of the retention behavior of solutes in ion-exchange (Mazza et al. 2002b) and HIC (Mazza 2001) systems. Mazza and co-workers have also developed Quantitative Structure-Efficacy Relationship (QSER) models using percent protein displaced data from high throughput screens for the prediction of displacer efficacy in ion-exchange displacement chromatography (Mazza et al. 2002a; Tugcu et al. 2002b) . Our group was the first to report the development of QSRRs for protein adsorption in ion-exchange systems (Mazza et al. 2001a) .

We have also demonstrated that QSPR modeling can also be employed to aid in the design of novel displacers which can enable simultaneous high resolution separations and concentration. Recent work has demonstrated that displacers can also be used to develop chemically selective separations which can potentially transform non-specific separation systems into pseudo affinity separation systems. The major obstacle to the implementation of displacement chromatography has been the lack of appropriate displacer molecules, which can be addressed through interaction with Chemoselective Displacer Synthesis Module. Again the use of QSPR type models offers the opportunity to dramatically increase the speed of displacer discovery.

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