I-TASSER based atomic-level protein structure prediction

描述(由申请人提供)：最近的CASP实验见证了蛋白质结构预测的长足进步。最先进的算法，包括我 Tasser，可以为~3/4的单域蛋白靶标建立正确折叠的模型，其中模板模型在80%以上的情况下可以更接近自然状态。因此，高效的蛋白质结构建模系统在生物和医学界得到了广泛的应用。然而，对于远距离同源模板的蛋白质的计算模型的准确性通常较低，这对大多数生物医学研究没有实际用途。对于&gt；150残基的蛋白质，从头算模拟不能成功地构建正确的折叠。该项目扩展了基于I-tasser的高分辨率蛋白质结构预测算法的发展，专注于提高大尺寸蛋白质的远距离同源建模和从头计算折叠的能力。它还希望通过稀疏和易于访问的实验数据(包括小角X射线散射)来提高建模精度。该项目建立在成熟的i-tasser和夸克方法的基础上，旨在显著提高蛋白质三级结构预测的水平，特别是对非同源和远端同源蛋白质，使计算结构预测能够真正用于现代药物筛选和基因组中大多数蛋白质的生化功能推断。

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.