Quantitative Identification of Compound‐Dependent On‐Modules and Differential Allosteric Modules From Homologous Ischemic Networks

• Published in: CPT: pharmacometrics and systems pharmacology 2016-10, Vol.5 (10), p.575-584
• Main Authors: Li, B, Liu, J, Zhang, YY, Wang, PQ, Yu, YN, Kang, RX, Wu, HL, Zhang, XX, Wang, Z, Wang, YY
• Format: Article
• Language: English
• Subjects: Animals; Biomarkers; Brain Ischemia - drug therapy; Disease; Drugs; Flavonoids - administration & dosage; Flavonoids - pharmacology; Gene expression; Gene Expression Profiling; Gene Regulatory Networks - drug effects; Humans; Identification; Iridoids - administration & dosage; Iridoids - pharmacology; Ischemia; Kinases; Mice; Original; Proteins; Stroke; Studies; Ursodeoxycholic Acid - administration & dosage; Ursodeoxycholic Acid - pharmacology
• ISSN: 2163-8306; 2163-8306
• DOI: 10.1002/psp4.12127

Module‐based methods have made much progress in deconstructing biological networks. However, it is a great challenge to quantitatively compare the topological structural variations of modules (allosteric modules [AMs]) under different situations. A total of 23, 42, and 15 coexpression modules were identified in baicalin (BA), jasminoidin (JA), and ursodeoxycholic acid (UA) in a global anti‐ischemic mice network, respectively. Then, we integrated the methods of module‐based consensus ratio (MCR) and modified Zsummary module statistic to validate 12 BA, 22 JA, and 8 UA on‐modules based on comparing with vehicle. The MCRs for pairwise comparisons were 1.55% (BA vs. JA), 1.45% (BA vs. UA), and 1.27% (JA vs. UA), respectively. Five conserved allosteric modules (CAMs) and 17 unique allosteric modules (UAMs) were identified among these groups. In conclusion, module‐centric analysis may provide us a unique approach to understand multiple pharmacological mechanisms associated with differential phenotypes in the era of modular pharmacology.