Andrej Sali
University of California, San Francisco
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Primary Section: 29, Biophysics and Computational Biology Secondary Section: 21, Biochemistry Membership Type:
Member
(elected 2018)
Photo Credit: majedophoto.com |
Biosketch
Andrej Sali is a computational structural biologist recognized for his work on the modeling and analysis of protein structures. He is known particularly for his development and application of comparative protein structure modeling and integrative structure modeling, including the determination of the structures of a number of key macromolecular machines such as the proteasome and the nuclear pore complex. Sali was born in Kranj, Slovenia. He graduated from University of Ljubljana, Slovenia, with a degree in Chemistry; and from Birkbeck College, University of London, in 1991 with a PhD in molecular biophysics. He was a postdoctoral fellow in biophysics at Harvard University and joined the faculty of Rockefeller University in 1995. He moved to University of California, San Francisco, in 2003. He is a member of the National Academy of Sciences.
Research Interests
Andrej Sali’s laboratory develops and applies modeling methods for computing structures of biomolecular assemblies that are consistent with all available information from experimental methods, physical theories, statistical inference, and prior models. This integrative approach maximizes accuracy, precision, and completeness of the resulting models. The current version of the corresponding program, Integrative Modeling Platform (IMP), is being used to determine the structures of a number of macromolecular assemblies, in collaboration with experimentalists. Most prominently, the approach already enabled the determination of the configuration of the 550 proteins in the yeast Nuclear Pore Complex and 19 proteins in the 19S subunit of the 26S proteasome. This research was also a major contributing factor to the establishment of PDB-Development, the nascent worldwide Protein Data Bank archive for integrative structures. Finally, the integrative modeling approach is being expanded to the mapping of biomolecular networks and spatiotemporal modeling of entire cellular neighbourhoods.
