PLoS Computational Biology · 2012 · 281 citations · 70 references
Life SciencesBioinformaticsMolecular BiologyComputational BiologyNetwork BiologyProtein BiochemistryDisease Network BiologyMolecular Interaction NetworksProtein Interaction MappingProtein-ligand InteractionsProtein-nucleic Acid InteractionsProtein-protein Interaction NetworksDisease Protein Interaction NetworksHuman Disease ModelsInteractomicsMolecular Network ModelingNetwork-based Interaction AnalysisNetwork-based Protein Function PredictionProtein Interaction PredictionProtein Network Analysis
Protein interactions mediate metabolic, signaling, and cellular processes, and mutations that disrupt binding interfaces or allosteric regulation can cause disease, making interaction networks valuable for elucidating disease mechanisms and guiding prevention, diagnosis, and treatment. The chapter aims to describe computational and experimental methods for predicting, mapping, and applying protein interaction networks to study human disease, while evaluating the challenges associated with these approaches. It outlines computational strategies for predicting and mapping protein interaction networks, reviews experimental detection techniques, and discusses their translational application to human disease.
Proteins do not function in isolation; it is their interactions with one another and also with other molecules (e.g. DNA, RNA) that mediate metabolic and signaling pathways, cellular processes, and organismal systems. Due to their central role in biological function, protein interactions also control the mechanisms leading to healthy and diseased states in organisms. Diseases are often caused by mutations affecting the binding interface or leading to biochemically dysfunctional allosteric changes in proteins. Therefore, protein interaction networks can elucidate the molecular basis of disease, which in turn can inform methods for prevention, diagnosis, and treatment. In this chapter, we will describe the computational approaches to predict and map networks of protein interactions and briefly review the experimental methods to detect protein interactions. We will describe the application of protein interaction networks as a translational approach to the study of human disease and evaluate the challenges faced by these approaches.
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