Rensselaer Researchers Develop Approach That Predicts Protein Separation Behavior
Applying math and computers to the drug discovery process,
researchers at Rensselaer have developed a method to predict
protein separation behavior directly from protein structure.
This new multi-scale protein modeling approach may reduce the
time it takes to bring pharmaceuticals to market and may have
significant implications for an array of biotechnology
applications, including bioprocessing, drug discovery, and
proteomics, the study of protein structure and function.
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A computational representation of protein
135L, with electrostatic potential encoded on its solvent
accessible surface.
Image by: RPI/Curt M. Breneman |
"Predictive modeling is a new approach to drug discovery
that takes information from lab analysis and concentrates it in
predictive models that may be evaluated on a computer," said
Curt Breneman, professor of chemistry and chemical
biology.
"The ability to predict the separation behavior of a
particular protein directly from its structure has considerable
implications for biotechnology processes," said Steven Cramer,
professor of chemical and biological engineering. "The research
results thus far indicate that this modeling approach can be
used to determine protein behavior for use in bioseparation
applications, such as the protein purification methods used in
drug discovery. This could potentially reduce the development
time required to bring biopharmaceuticals to market."
The modeling technique is based on methods previously
developed by Breneman's group for rapidly predicting the
efficacy and side effects of small drug-like molecules. The
newly developed model successfully predicted the amount of a
protein that binds to a material under a range of conditions by
using molecular information obtained from the protein
structure. These predicted adsorption isotherm parameters then
replicated experimental results by predicting the actual
separation profile of proteins in chromatographic columns.
Chromatography techniques are used to identify and purify
molecules, in this case, particular proteins.
"We intend to test the model against more complicated protein
structures as part of its further development," said Breneman.
"The outcome of this work will yield fundamental information
about the complex relationship between a protein's structural
features and its chemical binding properties, and also aid in
evaluating its potential biomedical applications."
The research findings are reported in the Aug. 16 issue of
Proceedings of the National Academy of Sciences in a
paper titled "A Priori Prediction of Adsorption Isotherm
Parameters and Chromatographic Behavior in Ion-Exchange
Systems."
In addition to Breneman and Cramer, the collaborative research
team includes Asif Ladiwala and Kaushal Rege, who both recently
earned doctorates in chemical and biological engineering at
Rensselaer. The work was supported by the National Science
Foundation and GE Healthcare.
Read the
press release.
Published
August 22,
2005
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