Nobel laureate who pioneered computational biology will speak at UB

Michael Levitt, Nobel prize winner, standing with arms folded.

Michael Levitt, who shared the 2013 Nobel Prize for Chemistry, speaks at UB on May 2.

Local researchers have benefitted from Michael Levitt’s discoveries

Release Date: April 21, 2017 This content is archived.

“Anyone doing structural biology at UB – and especially scientists in UB’s Department of Structural Biology, based in the Hauptman-Woodward Medical Research Institute—has been influenced by that work. ”
Ram Samudrala, PhD, Professor and chief, Division of Bioinformatics
UB Department of Biomedical informatics

BUFFALO, N.Y. — Michael Levitt, a 2013 winner of the Nobel Prize in Chemistry, isn’t Swedish but he began his speech at the Nobel Banquet in Stockholm like this:

“Ers Majestäter, Ers Kungliga Högheter, Ers Excellenser, Mina Damer och Herrar. Jag börjar på svenska för att bevisa att jag fortfarande kan lära mig något nytt 45 år efter arbetet som förde mig hit….

“I start in Swedish to prove that I can still learn something 45 years after doing the work that brought me here.”

On May 2, scientists, students and interested community members will hear about that work, which he is still passionately pursuing, when Levitt, a Stanford University School of Medicine biophysicist and professor of structural biology, gives the O.P. Jones Lecture at the University at Buffalo.

Free and open to the public, it takes place at 3:30 p.m. in Butler Auditorium, 150 Farber Hall, on UB’s South Campus.

The talk is sponsored by the UB Clinical and Translational Science Institute (CTSI) and the Department of Biomedical Informatics in the Jacobs School of Medicine and Biomedical Sciences at UB. It is part of the CTSI Science Seminar series.

Levitt shared the 2013 Nobel Prize in Chemistry with Martin Karplus, PhD, of the University of Strasbourg and Harvard University, and Arieh Warshel, PhD, of the University of Southern California.

He said that the work that ultimately resulted in the Nobel Prize started back in 1967. “The simplifications used then, at the dawn of the age of computational structural biology, were mandated by computers that were almost a billion times less cost-effective than those we use today,” he explained.

While Levitt’s talk, titled “The Birth and Future of Multiscale Modeling of Macromolecules” is geared to a scientific audience, his contributions to science have had a dramatic effect on a broad range of fields, from drug development to materials science.

Buffalo-based scientists, in particular, have drawn on Levitt’s advances, according to Ram Samudrala, PhD, professor and chief, Division of Bioinformatics in the UB Department of Biomedical Informatics.

“In a general sense, the Nobel Prize that Levitt won was for being one of the first to do multiscale modeling of complex chemical systems, such as proteins and nucleic acids,” Samudrala said. “It launched the field of computational structural biology. That work has influenced several generations of scientists who, in turn, have influenced others.  Anyone doing structural biology at UB – and especially scientists in UB’s Department of Structural Biology, based in the Hauptman-Woodward Medical Research Institute—has been influenced by that work.”

In his UB talk, Levitt will discuss multiscale modeling of protein folding, structure, dynamics, energetics and structure-function relationships.

“These same multiscale models have become increasingly popular in applications that range from simulation of atomic protein motion to protein folding and explanation of enzyme catalysis,” Levitt explained. “In this talk, I describe the originals of computational structural biology and then go on to show some of the most exciting current and future applications.”

The achievement for which Levitt and his colleagues were awarded the Nobel had to do with techniques they developed to make Newton’s classical physics work side by side with quantum physics. They applied this to the computational modeling of large molecules, a huge advance that allowed scientists for the first time to be able to draw on both types of physics when simulating, for example, how a drug couples to its target protein.  

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