Our broad goal is to contribute to a comprehensive structural characterization of large macromolecular assemblies, such as the ribosome and the nuclear pore complex. Detailed structural characterization of assemblies is generally impossible by any single existing experimental or computational method. We suggest that this barrier can be overcome by hybrid approaches that integrate data from diverse biochemical and biophysical experiments (eg, x-ray crystallography, NMR spectroscopy, electron microscopy, immuno-electron microscopy, footprinting, chemical cross-linking, FRET spectroscopy, small angle X-ray scattering, immunoprecipitation, and genetic interactions). Even a coarse characterization of the configuration of macromolecular components in a complex (ie, the molecular architecture) helps to elucidate the principles that underlie cellular processes, in addition to providing a necessary starting point for a higher resolution description. We formulate the hybrid approach to structure determination as an optimization problem, the solution of which requires three main components: the representation of the assembly, the scoring function, and the optimization method. The ensemble of solutions to the optimization problem embodies the most accurate structural characterization given the available information. A preliminary version of this approach was used to determine the configuration of the 456 proteins in the yeast nuclear pore complex. The key challenges remain translating experimental data into restraints on the structure of the assembly, combining these spatial restraints into a single scoring function, optimizing the scoring function, and analyzing the resulting ensemble of solutions. To address these challenges, we propose the Integrated Modeling Platform (IMP). IMP is designed to allow mixing and matching of existing modeling components as well as easy adding of new functionality. It will support a wide variety of assembly representations and input data. We will also provide infrastructure that encourages and supports contributions from other laboratories. This proposal complements our development of the underlying biological and algorithmic theory supported elsewhere. Here, the specific aims cover the design, implementation, support, and distribution of the corresponding software platform. We propose to design a computer program that will be helpful for describing the three-dimensional shapes of large macromolecular machines. These structures will allow us to better understand the workings of the cell, both under normal and disease conditions.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM083960-02
Application #
7582313
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Lyster, Peter
Project Start
2008-04-01
Project End
2012-03-31
Budget Start
2009-04-01
Budget End
2010-03-31
Support Year
2
Fiscal Year
2009
Total Cost
$278,100
Indirect Cost
Name
University of California San Francisco
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
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