The efficiency of multi-target drugs: the network approach might help drug design.

By Peter Csermely, Vilmos Ágoston, Sándor Pongor. TIPS - Trends in Pharmacological Sciences, 2004

801 citations recorded by the source corpus.

Despite considerable progress in genome- and proteome-based high-throughput screening methods and rational drug design, the number of successful single-target drugs did not increase appreciably during the past decade. Network models suggest that partial inhibition of a surprisingly small number of targets can be more efficient than the complete inhibition of a single target. This and the success stories of multi-target drugs and combinatorial therapies led us to suggest that systematic drug-design strategies should be directed against multiple targets. We propose that the final effect of partial, but multiple, drug actions might often surpass that of complete drug action at a single target. The future success of this novel drug-design paradigm will depend not only on a new generation of computer models to identify the correct multiple targets and their multi-fitting, low-affinity drug candidates but also on more-efficient in vivo testing.

Subfields: Economics and Econometrics, General Health Professions, Health

View Paper: https://www.semanticscholar.org/paper/d23195e61e2fa439af42f06337438c3a6052d768

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Citations in the corpus

Network Medicine: A Network-based Approach to Human Disease (2011, background): “Increasing attention is therefore being given to therapies that involve multiple targets, which may be more effective in reversing the disease phenotype than are single drug”
Network target for screening synergistic drug combinations with application to traditional Chinese medicine (2011, background): “The second newly developing direction is to measure the efficacy of drugs, especially multi-target drugs, by using network biology approaches [14].”
How Can Synergism of Traditional Medicines Benefit from Network Pharmacology? (2017, background): “Thus, identification and proof of combined nodes in a biological network with synergistic effects will produce a desired therapeutic outcome [87,88].”
Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology (2013, background): “Compared with single-target agents, drugs that regulate multiple proteins have the potential to improve the balance of efficacy and safety [5], although minimizing their toxicity remains challenging.”
Network Pharmacology: A New Approach for Chinese Herbal Medicine Research (2013, background): “Hindawi Publishing Corporation Evidence-Based Complementary and Alternative Medicine Volume 2013, Article ID 621423, 9 pages http://dx.doi.org/10.1155/2013/621423”
Mechanisms of drug combinations: interaction and network perspectives (2009, background): “With such issues in mind, systems-oriented drug design has been increasingly emphasized as a potentially more productive strateg”
Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics (2019, background): “microRNAs, transcription factors and interacting proteins) is useful for drug discovery tasks (Supplementary Table S1) such as the investigations of target druggability (6,30), systems pharmacology (31) and the discovery of multi-target and combination therapies (32,33).”
Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics (2017, background): “and the novel treatment strategies such as multitarget drugs (25,26,31), drug combinations (27,28,52), monoclonal antibodies (61) and RNA therapeutics (62) for enhanced therapeutics and for overcoming drug resistances (21,22).”
Natural products and drug discovery (2009, background): “This new strategy could have several advantages as it would modulate biological networks rather modestly and might therefore be more efficient in dealing with complex diseases”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, background): “• 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).”
In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling (2007, background): “This type of network approach may also help in designing drugs with affinity for multiple targets (Csermely et al ., 2005) or avoid anti-targets.”
Network pharmacology: the next paradigm in drug discovery. (2008, background): “Network biology analysis predicts that if, in most cases, deletion of individual nodes has little effect on disease networks, modulating multiple proteins may be required to perturb robust phenotype”
Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing (2010, background): “1)? Multi-targeted compounds are low-affinity binders and could become more prominent for a specific target, provided they are exposed to an external conformationally- favored functional group [28].”