Network target for screening synergistic drug combinations with application to traditional Chinese medicine

By Shao Li, Ningbo Zhang. BMC Systems Biology, 2011

349 citations recorded by the source corpus.

BackgroundMulticomponent therapeutics offer bright prospects for the control of complex diseases in a synergistic manner. However, finding ways to screen the synergistic combinations from numerous pharmacological agents is still an ongoing challenge.ResultsIn this work, we proposed for the first time a “network target”-based paradigm instead of the traditional "single target"-based paradigm for virtual screening and established an algorithm termed NIMS (Network target-based Identification of Multicomponent Synergy) to prioritize synergistic agent combinations in a high throughput way. NIMS treats a disease-specific biological network as a therapeutic target and assumes that the relationship among agents can be transferred to network interactions among the molecular level entities (targets or responsive gene products) of agents. Then, two parameters in NIMS, Topology Score and Agent Score, are created to evaluate the synergistic relationship between each given agent combinations. Taking the empirical multicomponent system traditional Chinese medicine (TCM) as an illustrative case, we applied NIMS to prioritize synergistic agent pairs from 63 agents on a pathological process instanced by angiogenesis. The NIMS outputs can not only recover five known synergistic agent pairs, but also obtain experimental verification for synergistic candidates combined with, for example, a herbal ingredient Sinomenine, which outperforms the meet/min method. The robustness of NIMS was also showed regarding the background networks, agent genes and topological parameters, respectively. Finally, we characterized the potential mechanisms of multicomponent synergy from a network target perspective.ConclusionsNIMS is a first-step computational approach towards identification of synergistic drug combinations at the molecular level. The network target-based approaches may adjust current virtual screen mode and provide a systematic paradigm for facilitating the development of multicomponent therapeutics as well as the modernization of TCM.

Subfields: Computational Theory and Mathematics, Molecular Biology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/8af47d6c0f4e51e651c797b522196a325f03440e

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Citations in the corpus

Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine (2023, background): “The essence of studying the compatibility law of formulas is also to explore the modular law of component–target relationships, and to further establish the association rules of formulas by identifying the herb–herb relationships [108–112].”
How Can Synergism of Traditional Medicines Benefit from Network Pharmacology? (2017, background): “[79] The molecular mechanism of the multiple components, targets and pathways in tou-gu-xiao-tong capsules were revealed by analyzing the networks of the compound and drug targets [80,81].”
Network Pharmacology: A New Approach for Chinese Herbal Medicine Research (2013, methodology): “[60] applied a network target-based identification of multicomponent synergy (NIMS) algorithms to calculate”
TCMSP: a database of systems pharmacology for drug discovery from herbal medicines (2014, positive): “This systems/network pharmacology methodology has been successfully applied to dissect basic TCM theories such as yin-yang theory [9], qi-blood [5], herbal synergy [10,11], as well as to develop new drugs [7].”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, methodology): “• Network efficiency (Latora & Marchiori, 2001), or critical node detection (Boginski & Commander, 2009) may serve as a starting measure to judge network integrity after multi-target action (Agoston et al., 2005; Csermely et al., 2005; Li et al., 2011c).”