Open AccessQuantitative Identification of Compound‐Dependent On‐Modules and Differential Allosteric Modules From Homologous Ischemic Networks
Author(s) -
Li B,
Liu J,
Zhang YY,
Wang PQ,
Yu YN,
Kang RX,
Wu HL,
Zhang XX,
Wang Z,
Wang YY
Publication year - 2016
Publication title -
cpt: pharmacometrics and systems pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.53
H-Index - 37
ISSN - 2163-8306
DOI - 10.1002/psp4.12127
Subject(s) - allosteric regulation , modular design , computational biology , pairwise comparison , identification (biology) , differential (mechanical device) , chemistry , biology , computer science , biochemistry , physics , artificial intelligence , receptor , thermodynamics , operating system , botany
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 Z summary 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.