Axel T. Brunger (born November 25, 1956) is a German American biophysicist and Professor of Molecular and Cellular Physiology, and Neurology and Neurological Sciences at Stanford University, and an Howard Hughes Medical Institute Investigator.
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Brunger was born in Leipzig, Germany on November 25, 1956. He graduated with a degree in Physics and Mathematics from the University of Hamburg in 1977. He completed his Diplom in Physics from the University of Hamburg in 1980. He completed his PhD in Biophysics from Technical University of Munich in 1982.
Brunger held a NATO postdoctoral fellowship and subsequently became a research associate in the Department of Chemistry, Harvard University before joining the faculty at Yale University in 1987. From 1993 to 2000, he was a professor Molecular Biophysics and Biochemistry at Yale University. He joined the faculty at Stanford in 2000.
Brunger is known for developing a computer program used for solving structures based on X-ray diffraction data or solution NMR data. The program is widely used because of its various features. The program is a major extension of the program his team developed called X-PLOR, which came out in 1987. The program made use of a method called simulated annealing to refine X-ray crystal structures.
That was the first time a modern optimization technique was applied to this problem of refinement. Before that program had become available, it often took people years to refine crystal structures. It was a manually intense process. When Brunger introduced simulated annealing to crystallographic refinement in his 1987 paper, the time to refine crystal structures was significantly reduced and it had a tremendous impact in the crystallographic community.
X-PLOR also featured a technique to cross-validate the model given the observed data, and it came out in 1992. In the mid-1990s, his team decided to extend X-PLOR into a complete system to solve structures, which then became CNS. X-PLOR was limited to the step of refining crystal structures, which is the step where one changes the model to get the best match with the observed refraction data. CNS does everything from obtaining phases from experimental data to molecular replacement phasing from known homologous structures.
He also works to understand the molecular mechanism of synaptic neurotransmission. He is mainly interested in the structure, function, and dynamics of key players in the synaptic vesicle fusion machinery.