The understanding at an atomic level of a broad range of cellular functions is a vital and strategic goal in biology. In many instances, these functions are performed by large macromolecular complexes, which have become known as """"""""molecular nano-machines."""""""" Naturally, these complexes show a large degree of molecular flexibility, or structural plasticity/heterogeneity, inherently associated with their tasks. This structural plasticity, in itself the key to the functional success of the molecular nano-machines, is a major cause of problems in the task of experimentally determining their three-dimensional (3D) structure. It has been postulated that three-dimensional electron microscopy (3D EM), and in particular its """"""""single-particle"""""""" and """"""""Tomography"""""""" variants, combined with the fitting of atomic-resolution structures, could be the right method to study these different conformational states. However, the image processing methodologies in the 3D EM field are not yet sufficiently developed so as to correctly overcome the difficulties that arise in the electron microscopic imaging, reconstruction and analysis of molecular nano-machines in the presence of structural flexibility. The need to develop a new set of image processing methodologies to address this issue is the central motivation for the proposed work. We will take a multi-disciplinary approach, which is based on a combination of understanding the techniques and applications of 3D EM with biological knowledge and mathematical and engineering expertise, to develop new technologies (in single particle 3D EM and in Tomography) to overcome outstanding problems of 3D EM imaging in the presence of structural heterogeneity. The proposed effort will concentrate on 3 interrelated lines of research in Image Preparation, Image Reconstruction, and Image Analysis, complemented by a rigorous approach to validating claims of superiority of any of the newly developed methods over those used in current practice. From the point of view of contribution to public health, we will be developing image processing methodologies for obtaining more accurate structural information by 3D EM (which is an essential instrumental tool of structural biology) than what can be achieved currently. This will contribute to our understanding of the detailed molecular mechanisms of some of the key cell functions and, consequently, impact on the field of drug discovery. The work is relevant in particular to cardiovascular and pulmonary disease and health and to blood research.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL070472-07
Application #
7279193
Study Section
Special Emphasis Panel (ZRG1-MI (01))
Program Officer
Buxton, Denis B
Project Start
2001-09-01
Project End
2009-08-31
Budget Start
2007-09-01
Budget End
2008-08-31
Support Year
7
Fiscal Year
2007
Total Cost
$328,970
Indirect Cost
Name
CUNY Graduate School and University Center
Department
Biostatistics & Other Math Sci
Type
Other Domestic Higher Education
DUNS #
620128194
City
New York
State
NY
Country
United States
Zip Code
10016
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