Network Biology editorial 2013.

Recent advances in high throughput methods make it possible to study the behaviour of biomolecules that make up entire biological systems. This recent interest in whole systems comes from the belief that they have functions that none of the entities of the systems have, and that ‘‘the total is more than the sum of its parts’’. The rules that govern the behaviour of biological systems are currently the focus of intense research in the field of ‘‘Systems Biology’’. The resulting models are expected to be predictive of different healthy and pathological conditions. Theymight provide synthetic biologists with the general principles for the (re)engineering of biological systems for particular purposes. In this blooming field, many groups have pioneered the development and use of biochemical methods, coupled to quantitative mass-spectrometry with the aim of systematically linking dynamic protein interaction networks to various phenotypes in model organisms, human cell lines and human pathogens. Our long term goals are to advance network biology & medicine through integration of quantitative biochemistry/proteomics, genetics and whenever possible structural data. We intend to define system-wide mechanistic models explaining complex phenotypes and human diseases. Our effort will ultimately contribute new strategies for targeting human pathologies and simultaneously provide insight into the fundamental principles and rules guiding biomolecular recognition. The availability of the growing number of sequenced genomes from diverse organisms has fundamentally changed the way we address biological questions. This paradigm shift motivated the development of various follow-ups, accompanying technologies for global interrogation of gene activity and function. This so called ‘‘genomics revolution’’ broadly influences life science research; scientists from all fields now routinely measure, characterize and localize an ever-growing number of molecular players at the level of entire biological systems. While these ‘‘omics’’ approaches are still in full expansion, increasingly contributing to the editing of systemslevel networks, we still poorly understand how discrete biological activities are organized in space and time, and integrated within entire systems, producing coherent phenotypes. The way biological systems organize themselves in dynamic, functional assemblies with varying levels of complexity, such as protein complexes, molecular circuits, pathways, organelles, etc., remains largely elusive. Deciphering the molecular mechanisms of cell function – or dysfunction – relies to a large extent on tracing the multitude of physical interactions between the numerous components of living cells. Decades of singleprotein studies, and more recent efforts devoted to the large-scale charting of physical interaction networks, contributed to the characterization of a variety of modular binding domains with specificity for distinct linear sequence motifs or for different metabolites. These constitute the basic syntax principles for a still largely elusive biomolecular assembly code. In the absence of systematic and comprehensive analyses we still frequently miss the mechanistic or structural determinants responsible for the specificity and the precision of biomolecular recognition. The remarkable functional relevance of biomolecular interactions is particularly evident from the major phenotypic effects caused by their disruptions. In humans, among the 43000 human monogenic syndromes with a known molecular basis, mutations that affect biomolecular interactions are not uncommon. For instance, immunodeficiency, centromeric instability, facial anomalies syndrome, are caused by defects in DNMT3B, a DNA methyltransferase. The missense mutations have been mapped not only within the catalytic site, but also affect an N-terminal PWWP domain of DNMT3B, involved in protein–protein interactions. Mutations have been characterised that prevent the assembly of functional multiprotein complexes. A good example is a RFXANK gene mutant that fails to assemble the regulatory factor X complex (an obligate transcription factor required a Department of Chemistry & Biochemistry, The University of Texas at Austin 1 University Station A5300, Austin, TX 78712-0165, USA b EMBL Heidelberg, Meyerhofstraße 1, 69117 Heidelberg, Germany c Boone Lab, University of Toronto, Donnelly Centre, Room 1330, 160 College Street, Toronto, Ontario, M5S 3E1, Canada MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge, CB2 0QH, UK DOI: 10.1039/c3mb90018e