Martin Karplus, Michael Levitt, And Arieh Warshel Honored For Their Computational Methods To Study Complex Chemical Systems In Action | Chemical & Engineering News
Volume 91 Issue 51 | pp. 18-19
Issue Date: December 23, 2013

Cover Stories: Research Year In Review

Martin Karplus, Michael Levitt, And Arieh Warshel Honored For Their Computational Methods To Study Complex Chemical Systems In Action

2013 Nobel Prize In Chemistry
Department: Science & Technology
News Channels: Biological SCENE
Keywords: molecular mechanics, quantum mechanics, Nobel Prize, theoretical chemistry
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Karplus
Credit: Stephanie Mitchell/Harvard
Karplus
 
Karplus
Credit: Stephanie Mitchell/Harvard
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Warshel
Credit: Courtesy of Arieh Warshel
Warshel
 
Warshel
Credit: Courtesy of Arieh Warshel
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Levitt
Credit: L.A. Cicero
Levitt
 
Levitt
Credit: L.A. Cicero

Theoretical chemists are sometimes misunderstood and often underappreciated. But this year, the Royal Swedish Academy of Sciences had a clear understanding of the achievements of three prominent theoreticians on whom it bestowed the Nobel Prize in ChemistryMartin Karplus of the University of Strasbourg, in France, and Harvard University; Michael Levitt of Stanford University School of Medicine; and Arieh Warshel of the University of Southern California (C&EN, Oct. 14, page 5). The academy honored this gang of three “for the development of multiscale models for complex chemical systems.” This phrase refers to key contributions made by Karplus, Levitt, and Warshel over four decades to developing computational methods that predict how chemical reactions occur and proteins fold—without the need to first run any actual reactions or fold any actual proteins to find out. From a technical standpoint, they combined two things: quantum mechanics (QM), a rigorous mathematical description of how atoms and electrons move and interact, and molecular mechanics (MM), a method that uses mathematical approximations to model molecular behavior. The resulting combination, called QM/MM, predicts the behavior of chemical reactions and processes quite accurately without requiring a lifetime of computer crunching to do so, as QM alone would necessitate. QM/MM is now a state-of-the-art approach that scientists and engineers use for simulating chemical processes—not only for drug discovery and tracking reaction mechanisms but also to improve fundamental understanding of chemical structure and bonding. It’s information that would be hard to ferret out any other way.

 
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