Explaining how 2013 Nobel Prize in Chemistry impacted biochemistry
October 9, 2013 § 1 Comment
This morning, three scientists heard the news that their work on computer simulations garnered them the 2013 Nobel Prize in Chemistry. Martin Karplus of the Université de Strasbourg, France, and Harvard University, Michael Levitt at Stanford University School of Medicine and Arieh Warshel at the University of Southern California received the honor “for the development of multiscale models for complex chemical systems,” said The Royal Swedish Academy of Sciences in its announcement.
The scientists came up with “methods that solve equations for large complex systems such as proteins by using Newton’s laws with forces that include, in an approximate way, quantum effects. In some cases, the methods use more explicit quantum mechanical calculations for local regions of interest, such as the active site of an enzyme,” explains Jeremy Berg at the University of Pittsburgh and the president of ASBMB. “These methods—molecular dynamics and combined quantum mechanics and molecular mechanics—have had, and will continue to have, a huge influence on biochemistry.”
The Royal Swedish Academy of Sciences explained in its press release that research by “Karplus, Levitt and Warshel is ground-breaking in that they managed to make Newton’s classical physics work side-by-side with the fundamentally different quantum physics. Previously, chemists had to choose to use either or.”
Berg says that work by Karplus, Levitt and Warshel lets scientists carry out simulations of proteins and protein complexes as large as the ribosome. These simulations help us understand how macromolecules function in general, as well as give us insight into specific features that are important for a particular complex of proteins.
“Indeed, since moving to Pittsburgh, my own research has focused on using molecular dynamics calculations to understand specific protein-peptide interactions essential for intracellular protein targeting,” says Berg, who was the former head of the National Institute of General Medical Sciences. “The methods are also used widely in the pharmaceutical industry to help make screening for drug candidates more efficient.”