Protein–protein interactions: switch from classical methods to proteomics and bioinformatics-based approaches

Wetie, Armand G. Ngounou; Sokolowska, Izabela; Woods, Alisa G.; Roy, Urmi; Deinhardt, Katrin; Darie, Costel C.

doi:10.1007/s00018-013-1333-1

Cited by 121 publications

(85 citation statements)

References 254 publications

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“…These methods are often complex, expensive, time consuming and require a significant level of expertise for performing them in a reliable manner. AP-MS and CoAP-MS (co-affinity purification mass spectroscopy) are actively studied today from separations point of view as well [39][40][41], while MS-based mapping of protein-protein interactions is progressing more slowly [42,43].…”

Section: Challenges In Separation/purification Of Human Proteins In Tmentioning

confidence: 99%

Challenges in Separations of Proteins and Small Biomolecules and the Role of Modern Mass Spectroscopy Tools for Solving Them, as Well as Bypassing Them, in Structural Analytical Studies of Complex Biomolecular Mixtures

Haramija

2018

Separations

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State-of-the-art purification of biomolecules, as well as separation of complex omic mixtures, is crucial for modern biomedical research. Mass spectroscopy (MS) represents a technique that both requires very clean biomedical samples and can substantially assist liquid chromatography (LC) separations, using either LC-MS or LC-MS/MS methods available. Here, a brief overview of the applicability of LC-MS/MS methodology for structural analyses of complex omic mixtures without prior purification of each sample component will be given. When necessary bioinformatic tools are available, these can be carried out quite quickly. However, manual data analysis of such complex mixtures is typically very slow. On the other hand, the need for high-level purity of protein samples for modern biomedical research will be discussed. Often, modification of protein purification protocols is needed, or additional purification steps may be either required or preferred. In the context of mass spectroscopy-related biomedical research, purification of pmol and subpmol amounts of biomedical samples, as well as commercial availability of pmol amounts of purified standards will be discussed.

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Section: Challenges In Separation/purification Of Human Proteins In Tmentioning

confidence: 99%

Challenges in Separations of Proteins and Small Biomolecules and the Role of Modern Mass Spectroscopy Tools for Solving Them, as Well as Bypassing Them, in Structural Analytical Studies of Complex Biomolecular Mixtures

Haramija

2018

Separations

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“…Biological networks can be inferred using omic datasets by mapping the data to models of all known protein-protein or -genetic interactions and generating a much larger model of the interactome (Stark et al 2011, Ngounou Wetie et al 2013; Fig. 1).…”

Section: Analysis Of Omic Datasets: Towards Integrated Analysismentioning

confidence: 99%

Network analysis: a new approach to study endocrine disorders

Stevens¹,

Leonibus²,

Hanson³

et al. 2013

Journal of Molecular Endocrinology

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Systems biology is the study of the interactions that occur between the components of individual cells -including genes, proteins, transcription factors, small molecules, and metabolites, and their relationships to complex physiological and pathological processes. The application of systems biology to medicine promises rapid advances in both our understanding of disease and the development of novel treatment options. Network biology has emerged as the primary tool for studying systems biology as it utilises the mathematical analysis of the relationships between connected objects in a biological system and allows the integration of varied 'omic' datasets (including genomics, metabolomics, proteomics, etc.). Analysis of network biology generates interactome models to infer and assess function; to understand mechanisms, and to prioritise candidates for further investigation. This review provides an overview of network methods used to support this research and an insight into current applications of network analysis applied to endocrinology. A wide spectrum of endocrine disorders are included ranging from congenital hyperinsulinism in infancy, through childhood developmental and growth disorders, to the development of metabolic diseases in early and late adulthood, such as obesity and obesity-related pathologies. In addition to providing a deeper understanding of diseases processes, network biology is also central to the development of personalised treatment strategies which will integrate pharmacogenomics with systems biology of the individual.

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“…Proteins are the active effectors of biological processes [6][7][8][9][10][11]. Protein biomarkers are understudied in neurodevelopmental disorders, and may have several advantages.…”

Section: Introductionmentioning

confidence: 99%