Network Pharmacology: The Next Paradigm in Drug Discovery

Division of Biological Chemistry and Drug Discovery, College of Life Science, University of Dundee, Dundee, UK.
Nature Chemical Biology (Impact Factor: 13). 11/2008; 4(11):682-90. DOI: 10.1038/nchembio.118
Source: PubMed


The dominant paradigm in drug discovery is the concept of designing maximally selective ligands to act on individual drug targets. However, many effective drugs act via modulation of multiple proteins rather than single targets. Advances in systems biology are revealing a phenotypic robustness and a network structure that strongly suggests that exquisitely selective compounds, compared with multitarget drugs, may exhibit lower than desired clinical efficacy. This new appreciation of the role of polypharmacology has significant implications for tackling the two major sources of attrition in drug development--efficacy and toxicity. Integrating network biology and polypharmacology holds the promise of expanding the current opportunity space for druggable targets. However, the rational design of polypharmacology faces considerable challenges in the need for new methods to validate target combinations and optimize multiple structure-activity relationships while maintaining drug-like properties. Advances in these areas are creating the foundation of the next paradigm in drug discovery: network pharmacology.

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    • "These failures are a major factor in the high total costs of drug development and increase the societal burden in developing new and effective therapies. While an initial focus on target activity often yields highly effective small molecules, it may lead to lack of depth and resolution in the characterization of potential polypharmacology (Hopkins, 2008). In addition , even in cases when the targets of a drug are well defined, unanticipated dependencies on specific genetic backgrounds can limit its application. "
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    ABSTRACT: Small molecules often affect multiple targets, elicit off-target effects, and induce genotype-specific responses. Chemical genetics, the mapping of the genotype dependence of a small molecule's effects across a broad spectrum of phenotypes can identify novel mechanisms of action. It can also reveal unanticipated effects and could thereby reduce high attrition rates of small molecule development pipelines. Here, we used high-content screening and image analysis to measure effects of 1,280 pharmacologically active compounds on complex phenotypes in isogenic cancer cell lines which harbor activating or inactivating mutations in key oncogenic signaling pathways. Using multiparametric chemical-genetic interaction analysis, we observed phenotypic gene-drug interactions for more than 193 compounds, with many affecting phenotypes other than cell growth. We created a resource termed the Pharmacogenetic Phenome Compendium (PGPC), which enables exploration of drug mode of action, detection of potential off-target effects, and the generation of hypotheses on drug combinations and synergism. For example, we demonstrate that MEK inhibitors amplify the viability effect of the clinically used anti-alcoholism drug disulfiram and show that the EGFR inhibitor tyrphostin AG555 has off-target activity on the proteasome. Taken together, this study demonstrates how combining multiparametric phenotyping in different genetic backgrounds can be used to predict additional mechanisms of action and to reposition clinically used drugs.
    Preview · Article · Dec 2015 · Molecular Systems Biology
    • "All rights reserved. " polypharmacology " concept, now becoming of considerable importance in the discovery of new drugs [24]. "
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    ABSTRACT: The mechanisms of cell-cell communications are now under intense study by proteomic approaches. Proteomics has unraveled changes in protein profiling as the result of cell interactions mediated by ligand/receptor, hormones, soluble factors and the content of extracellular vesicles. Besides being a brief overview of the main and profitable methodologies now available (evaluating theory behind the methods, their usefulness and pitfalls), this review focuses on - from a proteome perspective - some signaling pathways and post-translational modifications, which are essential for understanding ischemic lesions and their recovery in 2 vital organs in mammals, the heart and the kidney. Knowledge of misdirection of the proteome during tissue recovery, such as represented by the convergence between fibrosis and cancer, emerges as an important tool in prognosis. Proteomics of cell-cell interaction is also especially useful for understanding how stem cells interact in injured tissues, anticipating clues for rational therapeutic interventions. In the effervescent field of induced pluripotency and cell reprogramming, proteomic studies have shown what proteins from specialized cells contribute to the recovery of infarcted tissues. Overall, we conclude that proteomics is at the forefront in helping us to understand the mechanisms that underpin prevalent pathological processes. This article is protected by copyright. All rights reserved.
    No preview · Article · Nov 2015 · Proteomics
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    • "/Chin J Nat Med, 2015, 13(10): 751759 – 752 –pharmacology properties of various natural product-target networks demonstrated that polypharmacology was highly relevant for compounds with a large degree of chemical divers ity and high betweenness centrality (a measure of the load and importance of an identified drug target node)[13]. Currently, network pharmacology is regarded as the next paradigm in drug dis covery[9]. Indeed, network description and analysis permits a systems-level understanding of drug actions and dis ease complexity that is heretofore unachievable[14]. The aim of the present study was to facilitate a sy stems-level understanding of the drug targets and molecular mechanisms of Tanshinone IIA. "
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    ABSTRACT: Tanshinone IIA is a pharmacologically active compound isolated from Danshen (. Salvia miltiorrhiza), a traditional Chinese herbal medicine for the management of cardiac diseases and other disorders. But its underlying molecular mechanisms of action are still unclear. The present investigation utilized a data mining approach based on network pharmacology to uncover the potential protein targets of Tanshinone IIA. Network pharmacology, an integrated multidisciplinary study, incorporates systems biology, network analysis, connectivity, redundancy, and pleiotropy, providing powerful new tools and insights into elucidating the fine details of drug-target interactions. In the present study, two separate drug-target networks for Tanshinone IIA were constructed using the Agilent Literature Search (ALS) and STITCH (search tool for interactions of chemicals) methods. Analysis of the ALS-constructed network revealed a target network with a scale-free topology and five top nodes (protein targets) corresponding to Fos, Jun, Src, phosphatidylinositol-4, 5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA), and mitogen-activated protein kinase kinase 1 (MAP2K1), whereas analysis of the STITCH-constructed network revealed three top nodes corresponding to cytochrome P450 3A4 (CYP3A4), cytochrome P450 A1 (CYP1A1), and nuclear factor kappa B1 (NFκB1). The discrepancies were probably due to the differences in the divergent computer mining tools and databases employed by the two methods. However, it is conceivable that all eight proteins mediate important biological functions of Tanshinone IIA, contributing to its overall drug-target network. In conclusion, the current results may assist in developing a comprehensive understanding of the molecular mechanisms and signaling pathways of in a simple, compact, and visual manner.
    Full-text · Article · Oct 2015 · Chinese Journal of Natural Medicines
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