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

Date

2016-04-27

Author

Keskin, Ozlem
Tunçbağ, Nurcan
Gursoy, Attila

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

Subject Keywords

Interfaces, Peptides and proteins, Genetics, Biological databases, Protein structure

URI

https://hdl.handle.net/11511/32287

Journal

CHEMICAL REVIEWS

DOI

https://doi.org/10.1021/acs.chemrev.5b00683

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Graduate School of Informatics, Article

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Citation Formats

O. Keskin, N. Tunçbağ, and A. Gursoy, “Predicting Protein-Protein Interactions from the Molecular to the Proteome Level,” CHEMICAL REVIEWS, pp. 4884–4909, 2016, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32287.