Recent CASP experiments have witnessed considerable progress in protein structure prediction. The state of the art algorithms, including I TASSER, can build models of correct fold for ~3/4 of single-domain protein targets, where template models can be driven closer to the native state in more than 80% of cases. As a consequence, the highly efficient protein structure modeling systems have been widely used by the biological and medical communities. Nevertheless, the accuracy of computational models for the proteins of distant-homology templates is usually low, which are of no practical use to most of biomedical studies. For proteins of >150 residues, ab initio modeling cannot successfully construct the correct fold. This project extends the development of the I-TASSER-based algorithms for high-resolution protein structure predictions, with the focus on improving the ability of distant-homology modeling and ab initio folding for large-size proteins. It also sees to increase the modeling accuracy by the aid of sparse and easily accessible experiment data including small-angle X-ray scattering. Built on the strength of the well-established I-TASSER and QUARK methods, the project aims to significantly improving the state of the art of tertiary protein structure prediction, especially for the non- and distant-homology proteins, so that the computational structure prediction can be of real use to modern drug screening and biochemical functional inference for the majority of proteins in genomes.

Public Health Relevance

In the contemporary drug discovery industry, scientists need to use detailed knowledge of 3-dimensional structure of proteins associated with particular diseases to design synthetic compounds that fight against the diseases. But the structures of many important proteins are not available from experimental solutions. The development of computer algorithms by this project, which are able to generate atomic protein structures, will speed up the screening of putative chemical compounds and result in significant impact on drug discovery and public health.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
3R01GM083107-08S1
Application #
8773031
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Wehrle, Janna P
Project Start
2008-04-01
Project End
2017-06-30
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
8
Fiscal Year
2014
Total Cost
$65,606
Indirect Cost
$19,609
Name
University of Michigan Ann Arbor
Department
Biostatistics & Other Math Sci
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
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