Proteomics and genomics projects have yielded a detailed inventory of proteins in a cell. However, little is known about how these proteins are spatially and temporally arranged within the cell. Such knowledge is essential to understanding how proteins contribute to the structure and function of a living cell. Just as words must be assembled into sentences, paragraphs, and chapters to make sense, vital cellular functions are performed by structured assemblies (or complexes) of proteins rather than individual molecules. Often, these complexes comprise tens or hundreds of proteins. This proposal describes a set of computational methods that will exploit and integrate several kinds of emerging experimental data to uncover the structure and dynamics of protein complexes, toward the ultimate goal of achieving a mechanistic understanding of the cell. In particular, we will characterize proteome organization on three levels through the following projects. (1) We will develop an efficient computational method to determine the structure of individual protein complexes by simultaneously fitting multiple components to cryo-electron microscopy maps. (2) We will develop advanced pattern mining methods to discover and localize unknown protein complexes in whole-cell cryoelectron tomograms - a prerequisite towards comprehensive visual proteomics. (3) We will develop simulation methods to study the systems dynamics of protein interaction networks on biologically relevant time scales and within realistic cellular environments. With these tools, we are poised to model the spatial and temporal organizations of proteome. We will freely provide software packages and source code for all methods to the scientific community.

Public Health Relevance

(Public Health Relevance) Detailed knowledge concerning the spatial and temporal organization of the proteome is essential to understanding how proteins perform their functions in a cell. Proteins need to appear in exactly in the right places at exactly the right times in order to accomplish their roles. Any discrepancies may lead to diseases. In fact, many diseases are known to be caused by malfunctions in proteins or protein interactions. Our proposed methods will significantly contribute to knowledge in this area, so are highly relevant to public health.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Macromolecular Structure and Function D Study Section (MSFD)
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Wehrle, Janna P
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University of Southern California
Schools of Arts and Sciences
Los Angeles
United States
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Thalassinos, Konstantinos; Pandurangan, Arun Prasad; Xu, Min et al. (2013) Conformational States of macromolecular assemblies explored by integrative structure calculation. Structure 21:1500-8
Xu, Min; Alber, Frank (2013) Automated target segmentation and real space fast alignment methods for high-throughput classification and averaging of crowded cryo-electron subtomograms. Bioinformatics 29:i274-82
Kalhor, Reza; Tjong, Harianto; Jayathilaka, Nimanthi et al. (2012) Genome architectures revealed by tethered chromosome conformation capture and population-based modeling. Nat Biotechnol 30:90-8
Xu, Min; Beck, Martin; Alber, Frank (2012) High-throughput subtomogram alignment and classification by Fourier space constrained fast volumetric matching. J Struct Biol 178:152-64
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Beck, Martin; Topf, Maya; Frazier, Zachary et al. (2011) Exploring the spatial and temporal organization of a cell's proteome. J Struct Biol 173:483-96