Macromolecular assemblies are the basic functional units of biological cells; they furnish targets for drug design, as deficiencies in their architecture are frequently linked to health problems. The overall goal of the proposed research is the development of computational quantitative fitting tools for electron microscopy (EM) that combine low-resolution image reconstructions of large assemblies with complementary atomic resolution data of individual subunits for routine determination of the large-scale structure of aggregates. Key questions to be addressed include: (i) How can one accurately include experimental geometric constraints in the docking of single molecules? (ii) Are the features present in EM maps of assemblies sufficiently well-defined for a rapid, coarse-grained registration of template structures based on density estimation? (iii) Is a six-dimensional rigid-body search efficient and robust under experimental data limitations such as unaccounted parts in the compared structures? We will use topology representing neural networks for a coarse estimation of density maps and for determining suitable landmarks for the registration of multi-resolution data. Complementary to this indirect approach an exhaustive rigid body search will be performed in reciprocal space using parallel computing architectures (for computational speed) based in part on the gradient of the compared data sets (for accuracy). A computational laboratory supported by this project will be used extensively for software development and for fitting applications in EM. Collaborative efforts will include the refinement of actin filaments and microtubules, and the study of their interactions with motors and with factors promoting their disassembly, and the modeling of elongation factors on the ribosome. The results of these developments will be new computer codes that provide a comprehensible and flexible approach to the multi-resolution modeling of large assemblies. The algorithmic and methodological developments will be distributed freely through the established internet-based mechanisms employed for the Situs docking package.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM062968-04
Application #
6744391
Study Section
Special Emphasis Panel (ZRG1-SSS-U (05))
Program Officer
Deatherage, James F
Project Start
2001-04-01
Project End
2006-03-31
Budget Start
2004-04-01
Budget End
2005-03-31
Support Year
4
Fiscal Year
2004
Total Cost
$222,750
Indirect Cost
Name
University of Texas Health Science Center Houston
Department
Type
Schools of Allied Health Profes
DUNS #
800771594
City
Houston
State
TX
Country
United States
Zip Code
77225
Kovacs, Julio A; Galkin, Vitold E; Wriggers, Willy (2018) Accurate flexible refinement of atomic models against medium-resolution cryo-EM maps using damped dynamics. BMC Struct Biol 18:12
Islam, Tunazzina; Poteat, Michael; He, Jing (2018) Quantification of Twist from the Central Lines of ?-Strands. J Comput Biol 25:114-120
Chen, Lin; He, Jing; Sazzed, Salim et al. (2018) An Investigation of Atomic Structures Derived from X-ray Crystallography and Cryo-Electron Microscopy Using Distal Blocks of Side-Chains. Molecules 23:
Sazzed, Salim; Song, Junha; Kovacs, Julio A et al. (2018) Tracing Actin Filament Bundles in Three-Dimensional Electron Tomography Density Maps of Hair Cell Stereocilia. Molecules 23:
Si, Dong; He, Jing (2017) Modeling Beta-Traces for Beta-Barrels from Cryo-EM Density Maps. Biomed Res Int 2017:1793213
Biswas, Abhishek; Ranjan, Desh; Zubair, Mohammad et al. (2017) An Effective Computational Method Incorporating Multiple Secondary Structure Predictions in Topology Determination for Cryo-EM Images. IEEE/ACM Trans Comput Biol Bioinform 14:578-586
Zeil, Stephanie; Kovacs, Julio; Wriggers, Willy et al. (2017) Comparing an Atomic Model or Structure to a Corresponding Cryo-electron Microscopy Image at the Central Axis of a Helix. J Comput Biol 24:52-67
Kovacs, Julio A; Helmick, Cailee; Wriggers, Willy (2017) A Balanced Approach to Adaptive Probability Density Estimation. Front Mol Biosci 4:25
Alamo, Lorenzo; Qi, Dan; Wriggers, Willy et al. (2016) Conserved Intramolecular Interactions Maintain Myosin Interacting-Heads Motifs Explaining Tarantula Muscle Super-Relaxed State Structural Basis. J Mol Biol 428:1142-1164
Kovacs, Julio A; Wriggers, Willy (2016) Spatial Heat Maps from Fast Information Matching of Fast and Slow Degrees of Freedom: Application to Molecular Dynamics Simulations. J Phys Chem B 120:8473-84

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