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Evolution of sequence-based bioinformatics tools for protein-protein interaction prediction
Current Genomics ( IF 2.6 ) Pub Date : 2020-09-16 , DOI: 10.2174/1389202921999200625103936
Mst Shamima Khatun 1 , Watshara Shoombuatong 1 , Md Mehedi Hasan 1 , Hiroyuki Kurata 1
Affiliation  

Protein-protein interactions (PPIs) are the physical connections between two or more proteins via electrostatic forces or hydrophobic effects. Identification of the PPIs is pivotal, which contributes to many biological processes including protein function, disease incidence, and therapy design. The experimental identification of PPIs via high-throughput technology is time-consuming and expensive. Bioinformatics approaches are expected to solve such restrictions. In this review, our main goal is to provide an inclusive view of the existing sequence-based computational prediction of PPIs. Initially, we briefly introduce the currently available PPI databases and then review the state-of-the-art bioinformatics approaches, working principles, and their performances. Finally, we discuss the caveats and future perspective of the next generation algorithms for the prediction of PPIs.

中文翻译:

用于蛋白质-蛋白质相互作用预测的基于序列的生物信息学工具的演变

蛋白质-蛋白质相互作用 (PPI) 是两个或多个蛋白质之间通过静电力或疏水效应实现的物理连接。PPI 的鉴定至关重要,它有助于许多生物过程,包括蛋白质功能、疾病发生率和治疗设计。通过高通量技术进行 PPI 的实验鉴定既耗时又昂贵。生物信息学方法有望解决这些限制。在这篇综述中,我们的主要目标是提供现有基于序列的 PPI 计算预测的包容性观点。首先,我们简要介绍当前可用的 PPI 数据库,然后回顾最先进的生物信息学方法、工作原理及其性能。最后,我们讨论了下一代 PPI 预测算法的注意事项和未来前景。
更新日期:2020-09-16
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