Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA.
Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.
Methods Mol Biol. 2023;2627:41-59. doi: 10.1007/978-1-0716-2974-1_3.
The ability to successfully predict the three-dimensional structure of a protein from its amino acid sequence has made considerable progress in the recent past. The progress is propelled by the improved accuracy of deep learning-based inter-residue contact map predictors coupled with the rising growth of protein sequence databases. Contact map encodes interatomic interaction information that can be exploited for highly accurate prediction of protein structures via contact map threading even for the query proteins that are not amenable to direct homology modeling. As such, contact-assisted threading has garnered considerable research effort. In this chapter, we provide an overview of existing contact-assisted threading methods while highlighting the recent advances and discussing some of the current limitations and future prospects in the application of contact-assisted threading for improving the accuracy of low-homology protein modeling.
近年来,成功地根据蛋白质的氨基酸序列预测其三维结构取得了相当大的进展。这一进展得益于基于深度学习的残基间接触图预测器的准确性提高,以及蛋白质序列数据库的不断增长。接触图编码了原子间相互作用的信息,即使对于不能直接进行同源建模的查询蛋白质,也可以通过接触图穿线来进行高度准确的蛋白质结构预测。因此,接触辅助穿线得到了相当多的研究关注。在本章中,我们提供了现有接触辅助穿线方法的概述,同时强调了最近的进展,并讨论了在应用接触辅助穿线来提高低同源性蛋白质建模准确性方面的一些当前限制和未来前景。