Network pharmacology: the next paradigm in drug discovery.

By A. Hopkins. Nature Chemical Biology, 2008

4,073 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/73e76358965bcadf6a1e23a9ca2b4f4c99a7e925

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Citations in the corpus

Drug Discovery Using Chemical Systems Biology: Repositioning the Safe Medicine Comtan to Treat Multi-Drug and Extensively Drug Resistant Tuberculosis (2009, background): “If it is proven in future studies that entacapone can inhibit multiple targets simultaneously, the potential of entacapone as an anti-tubercular drug is even more promising, as ‘‘dirty’’ drugs lessen the likelihood of emergent resistance and higher clinical efficacy than exquisitely selective drugs ”
Targeting the cancer kinome through polypharmacology (2010, neutral): “As there are practical challenges associated with developing both multi-targeted single agents and multi-drug cocktails 50 , it will be interesting to see which approach emerges as the most successful from these clinical trials.”
Toward more realistic drug–target interaction predictions (2014, neutral): “means, for instance, toward streamlining drug repositioning strategies for predicting new therapeutic targets for existing drugs through network pharmacology approaches [9–12].”
Virtual screening: an endless staircase? (2010, background): “In this context, advances in chemogenomics, bioinformatic molecular network analysis and integrative data models will support the computer-assisted design of compounds with a desired activity and property profil”
Studying protein^protein interaction networks: a systems view on diseases (2012, background): “Major applications include drug design [6] and systems medicine [7].”
Synergistic drug combinations improve therapeutic selectivity (2009, neutral): “For each pair of assays in a screen, we compared four SI distributions: (1) the synergies with Scut > Scut, all combinations without synergy filtering, and most selective single agent from each combination (Fig.”