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Background: The investigation of the cellular components, their interactions and related functions constitute the major conditions in order to understand the cell as an integrated system. More specifically, the Protein-Protein Interactions and the obtained networks are very important in the majority of biological functions and processes, while most of the proteins appear to activate their functionalities through their interaction. Methods: Our in depth review analysis, include Sixty-five peer-reviewed research and review studies from several bibliographic databases. The most significant components were fully described, filtered, combined and analyzed in order to provide documented proofs on the Protein-Protein Interaction Network' applications in biomedicine. Results: The Protein-Protein Interaction Network' alignment and mapping give the opportunity of further knowledge extraction concerning the evolutionary relationships between the species through conserved pathways and protein complexes. Additionally, Protein-Protein Interaction Network information has been demonstrated to be able to predict functionally orthologous proteins within sequence homology clusters. Our review analysis concluded that, while Protein-Protein Interaction was used to be characterized just by their large and plain interacting surfaces, they were considered inapplicable for drug discovery studies for a long time. Conclusion: The present review explores multiple technologies implicated in Protein-Protein Interaction Networks, implicating their potential role in drug discovery mechanisms.

Protein to protein interactions (PPI) have been studied in great detail during the last decade. The informations derived from PPI analysis can be very helpful for large scale construction of different networks and the disambiguation of functional orthologs within of homologous sequence complexes. Several experimental techniques offered great tools for high throughput network mapping applications, although as long as the data increases massively, new computational methods arise to overcome the processing requirements for time and cost. Computational PPI network alignment tools have been used on comparative studies between various species to detect evolutionary pathways and investigate the topological features of the proteins’ networks, a crucial information that can give the opportunity to develop new therapeutic strategies for several diseases in the future. In this manuscript, we have analyzed different methods and techniques that are currently being used for the identification, construction and alignment of the PPI networks, and have explored their great potential in drug discovery purposes.