Biological nanomachines are the assemblies that carry out all the basic biological processes in a living organism. Electron cryo-microscopy (cryoEM) is the most appropriate structural tool to determine molecular structures of biological nanomachines that generally consist of multiple protein subunits and/or nucleic acids with a total mass greater than 0.5 million Daltons. The goal is to develop information discovery and integration methodologies for deriving atomic models of nanomachines. Such models will be derived from 3-dimensional (3-D) cryoEM mass density function (i.e. a volumetric density map) in conjunction with physics of protein folding and informatics data. This project is made possible by an integration of the expertise of five investigators in computer graphics, computational biophysics, structural informatics and cryoEM. The intellectual merit of this research is highlighted by the computational approaches of extracting structural information from low-resolution, complex cryoEM volume densities and integrating this information into classical protein structure modeling paradigms, such as comparative modeling and ab initio modeling, for understanding biological nanomachines. The three research goals involve information discovery, information integration and validation of the proposed algorithms. The proposed research will have significant impacts in three disparate disciplines: computer science, molecular modeling, and cryoEM. Furthermore, the team will disseminate their resulting tools freely to the academic community and will host a workshop towards the end of the project. To enhance the impact of their research, the investigators will integrate research with education at each member institution with an eye towards diversity. In particular, these investigators will develop a virtual didactic course in modeling of biological nanomachines for graduate and senior undergraduate students at the five participating institutions.

Agency
National Science Foundation (NSF)
Institute
Division of Information and Intelligent Systems (IIS)
Type
Standard Grant (Standard)
Application #
0706347
Program Officer
Sylvia J. Spengler
Project Start
Project End
Budget Start
2007-08-01
Budget End
2009-07-31
Support Year
Fiscal Year
2007
Total Cost
$165,000
Indirect Cost
Name
University of Washington
Department
Type
DUNS #
City
Seattle
State
WA
Country
United States
Zip Code
98195