The scientists say the new multi-scale protein modelling approach may have significant implications for an array of biotechnology applications, including bioprocessing, drug discovery, and proteomics, the study of protein structure and function.
The approach, known as predictive modelling, "takes information from lab analysis and concentrates it in predictive models that may be evaluated on a computer," according to Curt Breneman, professor of chemistry and chemical biology at Rensselaer.
"The ability to predict the separation behaviour of a particular protein directly from its structure has considerable implications for biotechnology processes," added Steven Cramer, professor of chemical and biological engineering at Rensselaer.
The research results thus far indicate that this modelling approach can be used to determine protein behaviour for use in bioseparations, including the protein purification methods used in drug discovery.
"This could potentially reduce the development time required to bring biopharmaceuticals to market," said Cramer.
The modelling 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 16 August issue of Proceedings of the National Academy of Sciences.