Recent developments of sequence-based prediction of protein-protein interactions

被引:5
|
作者
Murakami, Yoichi [1 ]
Mizuguchi, Kenji [2 ,3 ]
机构
[1] Tokyo Univ Informat Sci, 4-1 Onaridai,Wakaba Ku, Chiba 2658501, Japan
[2] Osaka Univ, Inst Prot Res, 3-2 Yamadaoka, Suita, Osaka 5650871, Japan
[3] Natl Inst Biomed Innovat Hlth & Nutr, 7-6-8 Saito Asagi, Osaka, Ibaraki 5670085, Japan
关键词
Protein-protein interactions; Protein feature; Computational prediction; Machine learning; INTERACTION NETWORKS; DATABASE; COEVOLUTION; ANNOTATION; GENERATION; COMPLEXES; CURATION; AAINDEX; WEB;
D O I
10.1007/s12551-022-01038-1
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
The identification of protein-protein interactions (PPIs) can lead to a better understanding of cellular functions and biological processes of proteins and contribute to the design of drugs to target disease-causing PPIs. In addition, targeting host-pathogen PPIs is useful for elucidating infection mechanisms. Although several experimental methods have been used to identify PPIs, these methods can yet to draw complete PPI networks. Hence, computational techniques are increasingly required for the prediction of potential PPIs, which have never been seen experimentally. Recent high-performance sequence-based methods have contributed to the construction of PPI networks and the elucidation of pathogenetic mechanisms in specific diseases. However, the usefulness of these methods depends on the quality and quantity of training data of PPIs. In this brief review, we introduce currently available PPI databases and recent sequence-based methods for predicting PPIs. Also, we discuss key issues in this field and present future perspectives of the sequence-based PPI predictions.
引用
收藏
页码:1393 / 1411
页数:19
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