Predicting Protein-Protein Interactions from the Molecular to the Proteome Level

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Abstract

Identification of protein-protein interactions (PPIs) is at the center of molecular biology considering the unquestionable role of proteins in cells. Combinatorial interactions result in a repertoire of multiple functions; hence, knowledge of PPI and binding regions naturally serve to functional proteomics and drug discovery. Given experimental limitations to find all interactions in a proteome, computational prediction/modeling of protein interactions is a prerequisite to proceed on the way to complete interactions at the proteome level. This review aims to provide a background on PPIs and their types. Computational methods for PPI predictions can use a variety of biological data including sequence-, evolution-, expression-, and structure-based data. Physical and statistical modeling are commonly used to integrate these data and infer PPI predictions. We review and list the state-of-the-art methods, servers, databases, and tools for protein-protein interaction prediction.

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Keskin, O., Tuncbag, N., & Gursoy, A. (2016, April 27). Predicting Protein-Protein Interactions from the Molecular to the Proteome Level. Chemical Reviews. American Chemical Society. https://doi.org/10.1021/acs.chemrev.5b00683

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