Mapping the disease protein interactome: toward a molecular medicine GPS to accelerate drug and biomarker discovery

Characterization of a Protein Interactome by Co-Immunoprecipitation and Shotgun Mass Spectrometry

Identifying the partners of a given protein (the interactome) may provide leads about the protein's function and the molecular mechanisms in which it is involved. One of the alternative strategies used to characterize protein interactomes consists of co-immunoprecipitation (co-IP) followed by shotgun mass spectrometry. This enables the isolation and identification of a protein target in its native state and its interactome from cells or tissue lysates under physiological conditions. In this chapter, we describe a co-IP protocol for interactome studies that uses an antibody against a protein of interest bound to protein A/G plus agarose beads to isolate a protein complex. The interacting proteins may be further fractionated by SDS-PAGE, followed by in-gel tryptic digestion and nano liquid chromatography high-resolution tandem mass spectrometry (nLC ESI-MS/MS) for identification purposes. The computational tools, strategy for protein identification, and use of interactome databases also will be described.

Advances in biomarkers of major depressive disorder

Major depressive disorder (MDD) is characterized by mood, vegetative, cognitive, and even psychotic symptoms and signs that can cause substantial impairments in quality of life and functioning. Biomarkers are measurable indicators that could help diagnosing MDD or predicting treatment response. In this chapter, lipid profiles, immune/inflammation, and neurotrophic factor pathways that have long been implicated in the pathogenesis of MDD are discussed. Then, pharmacogenetics and epigenetics of serotonin transport and its metabolism pathway, brain-derived neurotrophic factor, and abnormality of hypothalamo-pituitary-adrenocortical axis also revealed new biomarkers. Lastly, new techniques, such as proteomics and metabolomics, which allow researchers to approach the studying of MDD with new directions and make new discoveries are addressed. In the future, more data are needed regarding pathophysiology of MDD, including protein levels, single nucleotide polymorphism, epigenetic regulation, and clinical data in order to better identify reliable and consistent biomarkers for diagnosis, treatment choice, and outcome prediction.

Proteomics, metabolomics, and protein interactomics in the characterization of the molecular features of major depressive disorder

Omics technologies emerged as complementary strategies to genomics in the attempt to understand human illnesses. In general, proteomics technologies emerged earlier than those of metabolomics for major depressive disorder (MDD) research, but both are driven by the identification of proteins and/or metabolites that can delineate a comprehensive characterization of MDD's molecular mechanisms, as well as lead to the identification of biomarker candidates of all types—prognosis, diagnosis, treatment, and patient stratification. Also, one can explore protein and metabolite interactomes in order to pinpoint additional molecules associated with the disease that had not been picked up initially. Here, results and methodological aspects of MDD research using proteomics, metabolomics, and protein interactomics are reviewed, focusing on human samples.

Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review

Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only give a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The "central hit strategy" selectively targets central nodes/edges of the flexible networks of infectious agents or cancer cells to kill them. The "network influence strategy" works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved by targeting the neighbors of central nodes/edges. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach.

Systems biology for molecular life sciences and its impact in biomedicine

Modern systems biology is already contributing to a radical transformation of molecular life sciences and biomedicine, and it is expected to have a real impact in the clinical setting in the next years. In this review, the emergence of systems biology is contextualized with a historic overview, and its present state is depicted. The present and expected future contribution of systems biology to the development of molecular medicine is underscored. Concerning the present situation, this review includes a reflection on the "inflation" of biological data and the urgent need for tools and procedures to make hidden information emerge. Descriptions of the impact of networks and models and the available resources and tools for applying them in systems biology approaches to molecular medicine are provided as well. The actual current impact of systems biology in molecular medicine is illustrated, reviewing two cases, namely, those of systems pharmacology and cancer systems biology. Finally, some of the expected contributions of systems biology to the immediate future of molecular medicine are commented.