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.”
Tiffany Lohwater | EurekAlert!
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The quantum world is fragile; error correction codes are needed to protect the information stored in a quantum object from the deteriorating effects of noise. Quantum physicists in Innsbruck have developed a protocol to pass quantum information between differently encoded building blocks of a future quantum computer, such as processors and memories. Scientists may use this protocol in the future to build a data bus for quantum computers. The researchers have published their work in the journal Nature Communications.
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