Applying math and computers to the drug-discovery process, researchers at Rensselaer Polytechnic Institute 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.
"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 M. Breneman, professor of chemistry and chemical biology at Rensselaer.
"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 at Rensselaer. "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.