Extracting Coevolutionary Features from Protein Sequences for Predicting Protein-Protein Interactions

IEEE/ACM Transactions on Computational Biology and Bioinformatics
Lun Hu, Keith Chan

Abstract

Knowing the ways proteins interact with each other are crucial to our understanding of the functional mechanisms of proteins. It is for this reason that different approaches have been developed in attempts to predict protein-protein interactions (PPIs) computationally. Among them, the sequence-based approaches are preferred to the others as they do not require any information about protein properties to perform their tasks. Instead, most sequence-based approaches make use of feature extraction methods to extract features directly from protein sequences so that for each protein sequence, we can construct a feature vector. The feature vectors of every pair of proteins are then concatenated to form two classes of interacting and non-interacting proteins. The prediction of whether or not two proteins interact with each other is then formulated as a classification problem. How accurate PPI predictions can be made therefore depends on how good the features are that can be extracted from the protein sequences to allow interacting or non-interacting to be best distinguished. To do so, instead of extracting such features from individual protein sequences independently of the other protein in the same pair, we propose to jointly consider...Continue Reading

Citations

Oct 18, 2019·Database : the Journal of Biological Databases and Curation·Rui Antunes, Sérgio Matos
Jul 10, 2020·International Journal of Molecular Sciences·Albros Hermes Poot VelezGabriel Del Rio
Jun 20, 2020·Evolutionary Bioinformatics Online·Ji-Yong AnYu-Jun Zhao
Mar 12, 2021·Briefings in Bioinformatics·Lun HuZhu-Hong You
Apr 20, 2021·Frontiers in Genetics·Zhenfeng LiCheng Zhao
May 25, 2021·Frontiers in Molecular Biosciences·Sundeep Chaitanya VedithiTom L Blundell

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