ArticleJournal of cheminformatics2015
Quantitative modeling of dose-response and drug combination based on pathway network.
Article in Journal of cheminformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Rethinking Statin Dosage in Coronary Disease.Pharmacology research & perspectives · 2026Review
- Integrating Network Pharmacology, Quantitative Metabolic Network Analysis,Combinatorial chemistry & high throughput screening · 2025Article
- Preventing postpartum hemorrhage with combined therapy rather than oxytocin alone.American journal of obstetrics & gynecology MFM · 2023Review
- Systematic review of computational methods for drug combination prediction.Computational and structural biotechnology journal · 2022Review
- Prediction and identification of synergistic compound combinations against pancreatic cancer cells.iScience · 2021Article
- ZINC40099027 activates human focal adhesion kinase by accelerating the enzymatic activity of the FAK kinase domain.Pharmacology research & perspectives · 2021Article
- Detecting similar binding pockets to enable systems polypharmacology.PLoS computational biology · 2017Article
- Combination therapeutics in complex diseases.Journal of cellular and molecular medicine · 2016Review
- Herb-target interaction network analysis helps to disclose molecular mechanism of traditional Chinese medicine.Scientific reports · 2016Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundQuantitative description of dose-response of a drug for complex systems is essential for treatment of diseases and drug discovery. Given the growth of large-scale biological data obtained by multi-level assays, computational modeling has become an important approach to understand the mechanism of drug action. However, due to complicated interactions between drugs and cellular targets, the prediction of drug efficacy is a challenge, especially for complex systems. And the biological systems can be regarded as networks, where nodes represent molecular entities (DNA, RNA, protein and small compound) and processes, edges represent the relationships between nodes. Thus we combine biological pathway-based network modeling and molecular docking to evaluate drug efficacy.
resultsNetwork efficiency (NE) and network flux (NF) are both global measures of the network connectivity. In this work, we used NE and NF to quantitatively evaluate the inhibitory effects of compounds against the lipopolysaccharide-induced production of prostaglandin E2. The edge values of the pathway network of this biological process were reset according to the Michaelis-Menten equation, which used the binding constant and drug concentration to determine the degree of inhibition of the target protein in the pathway. The combination of NE and NF was adopted to evaluate the inhibitory effects. The dose-response curve was sigmoid and the EC50 values of 5 compounds were in good agreement with experimental results (R(2) = 0.93). Moreover, we found that 2 drugs produced maximal synergism when they were combined according to the ratio between each EC50.
conclusionsThis quantitative model has the ability to predict the dose-response relationships of single drug and drug combination in the context of the pathway network of biological process. These findings are valuable for the evaluation of drug efficacy and thus provide an effective approach for pathway network-based drug discovery.
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