I-TASSER based atomic-level protein structure prediction

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DESCRIPTION (provided by applicant): 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.