A Novel Algorithm for Detecting Co-evolutionary Domains in Protein and Nucleotide Sequences

作者：Zhang, Xiaoyu; Liao, Xiangke; Zhu, Hao^*; Li, Kenli; Shi, Benyun^*; Peng, Shaoliang^*

来源：IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), 2017-11-13 To 2017-11-16.

DOI：10.1109/bibm.2017.8217624

• coevolution
• evolution
• positive selection
• purifying selection

Co-evolution exists ubiquitously in biological systems. At the molecular level, interacting proteins, such as ligands and their receptors and components in protein complexes, co-evolve to maintain their structural and functional interactions. Many proteins contain multiple functional domains interacting with different partners, making co-evolution of interacting domains occur more prominently. Multiple methods have been developed to predict interacting proteins or domains within proteins by detecting their co-variation. This strategy neglects the fact that interacting domains can be highly co-conserved due to their functional interactions. Here we report a novel algorithm to detect signals of both co-positive selection (co-variation) and co-purifying selection (co-conservation). Preliminary results show that our algorithm performs well and outperforms the popular co-variation analysis program CAPS. Our algorithm can be widely used to predict interacting domains in protein and nucleotide sequences and to analyze protein-ncRNA complexes.

• 出版日期2017
• 单位湖南大学; 中国人民解放军国防科学技术大学; 南方医科大学; 杭州电子科技大学