Department of Chemical and Biological EngineeringDepartment of Computer Engineering2024-11-0920160009-266510.1021/acs.chemrev.5b006832-s2.0-84966908145http://dx.doi.org/10.1021/acs.chemrev.5b00683https://hdl.handle.net/20.500.14288/13257Identification 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.ChemistryReview1520-6890375244000004Q14568