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Interaction network
About: Interaction network is a research topic. Over the lifetime, 2700 publications have been published within this topic receiving 113372 citations.
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TL;DR: A new framework is described that uses experimental evidence on structural complexes, the atomic details of binding interfaces and evolutionary conservation to map the human protein interactome, and is highly modular and more functionally coherent compared with experimental interaction networks derived from multiple literature citations.
Abstract: Although the identification of protein interactions by highthroughput (HTP) methods progresses at a fast pace, ‘interactome’ data sets still suffer from high rates of false positives and low coverage. To map the human protein interactome, we describe a new framework that uses experimental evidence on structural complexes, the atomic details of binding interfaces and evolutionary conservation. The structurally inferred interaction network is highly modular and more functionally coherent compared with experimental interaction networks derived from multiple literature citations. Moreover, structurally inferred and high-confidence HTP networks complement each other well, allowing us to construct a merged network to generate testable hypotheses and provide valuable experimental leads.
49 citations
TL;DR: This work has identified three phenomena that have contributed to neofunctionalization being erroneously identified as a significant factor in protein interaction network evolution and believes that protein interaction evolution is more persuasively characterized by subfunctionalization and self-interactions.
Abstract: Gene duplication provides much of the raw material from which functional diversity evolves. Two evolutionary mechanisms have been proposed that generate functional diversity: neofunctionalization, the de novo acquisition of function by one duplicate, and subfunctionalization, the partitioning of ancestral functions between gene duplicates. With protein interactions as a surrogate for protein functions, evidence of prodigious neofunctionalization and subfunctionalization has been identified in analyses of empirical protein interactions and evolutionary models of protein interactions. However, we have identified three phenomena that have contributed to neofunctionalization being erroneously identified as a significant factor in protein interaction network evolution. First, self-interacting proteins are underreported in interaction data due to biological artifacts and design limitations in the two most common high-throughput protein interaction assays. Second, evolutionary inferences have been drawn from paralog analysis without consideration for concurrent and subsequent duplication events. Third, the theoretical model of prodigious neofunctionalization is unable to reproduce empirical network clustering and relies on untenable parameter requirements. In light of these findings, we believe that protein interaction evolution is more persuasively characterized by subfunctionalization and self-interactions.
49 citations
TL;DR: An algorithm is described that starts from an interacting pair and designs dozens of new pairs with diverse backbone conformations at the binding site as well as new binding orientations and sequences, generating a large and complex interaction network.
Abstract: Protein networks in all organisms comprise homologous interacting pairs. In these networks, some proteins are specific, interacting with one or a few binding partners, whereas others are multispecific and bind a range of targets. We describe an algorithm that starts from an interacting pair and designs dozens of new pairs with diverse backbone conformations at the binding site as well as new binding orientations and sequences. Applied to a high-affinity bacterial pair, the algorithm results in 18 new ones, with cognate affinities from pico- to micromolar. Three pairs exhibit 3-5 orders of magnitude switch in specificity relative to the wild type, whereas others are multispecific, collectively forming a protein-interaction network. Crystallographic analysis confirms design accuracy, including in new backbones and polar interactions. Preorganized polar interaction networks are responsible for high specificity, thus defining design principles that can be applied to program synthetic cellular interaction networks of desired affinity and specificity. The molecular basis of ultrahigh specificity in protein-protein interactions remains obscure. The authors present a computational method to design atomically accurate new pairs exhibiting >100,000-fold specificity switches, generating a large and complex interaction network.
49 citations
TL;DR: Experimental results demonstrate that a global, system-wide approach-such as IRAP that considers the entire interaction network instead of merely local neighbors-is a much more promising approach for assessing the reliability of PPIs.
49 citations
TL;DR: Peptide chips, pull down assays, SPOT synthesis and phage display experiments have allowed us to further characterize the specificity and promiscuity of proline-rich binding domains and to map their interaction network.
49 citations