PROVIDED. The long-term goal of this research is to provide significant speed-ups in understanding proteins through development of novel physics-based models in informatics. Proteins are involved in a large array of biological functions and their association with numerous diseases and disorders makes the timely understanding of their structure a subject with significant relevance to human health. As a step toward understanding proteins, the development of a broad inventory of protein structures and their rapid analysis is designated as a critical goal of structural biology. Experimental methods will continue to play a critical role, as a large number of novel protein folds remain unexplored. NMR spectroscopy is a key experimental tool in analyzing protein structures and a strong need for streamlining and extending its reach exists. The primary research focus of this work is the investigation and advancement of tools that will lead to significant speed- ups in understanding protein structures by building a probabilistic framework that integrates informatics and physical models. The strategy is to combine the use of informatics tools and physical modeling that is needed in order to rapidly evaluate, merge multiple data sources, and facilitate efficient building and analysis of protein inventories. The proposed approach, has already lead to innovative tools that have demonstrated quantifiable advances in the practice of NMR structure determination. The applicant has three research goals during this grant period: 1) investigate approaches to combining present tools developed by the PI into a complete paradigm with the aim of addressing fast and robust structure determination of small to moderate size proteins, 2) investigate distillation and extension of methods into a set of core tools that could form the basis for novel tools for rapid determination of protein folds and structure of larger proteins, and 3) take exploratory steps toward understanding the question of """"""""how much each new tool contributes to our understanding of protein space."""""""" The basic idea behind these methods is to devise a family of physical models and use informatics tools to find the most 'successful' model. These tools will facilitate production of timely information regarding proteins' functions by speeding up and streamlining the use of experimental data in structure determination. The accelerated progress toward understanding proteins will have a direct and significant impact on advancing the safeguards of human health.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Career Transition Award (K22)
Project #
5K22LM008992-03
Application #
7359619
Study Section
Special Emphasis Panel (ZLM1-HS-K (O1))
Program Officer
Ye, Jane
Project Start
2006-02-15
Project End
2008-06-30
Budget Start
2008-02-15
Budget End
2008-06-30
Support Year
3
Fiscal Year
2008
Total Cost
$29,322
Indirect Cost
Name
University of Wisconsin Madison
Department
Biochemistry
Type
Schools of Earth Sciences/Natur
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
Nielsen, Jakob T; Eghbalnia, Hamid R; Nielsen, Niels Chr (2012) Chemical shift prediction for protein structure calculation and quality assessment using an optimally parameterized force field. Prog Nucl Magn Reson Spectrosc 60:1-28
Bahrami, Arash; Assadi, Amir H; Markley, John L et al. (2009) Probabilistic interaction network of evidence algorithm and its application to complete labeling of peak lists from protein NMR spectroscopy. PLoS Comput Biol 5:e1000307
Wang, Liya; Eghbalnia, Hamid R; Markley, John L (2007) Nearest-neighbor effects on backbone alpha and beta carbon chemical shifts in proteins. J Biomol NMR 39:247-57
Cornilescu, Gabriel; Bahrami, Arash; Tonelli, Marco et al. (2007) HIFI-C: a robust and fast method for determining NMR couplings from adaptive 3D to 2D projections. J Biomol NMR 38:341-51