Identification of polycystic ovary syndrome potential drug targets based on pathobiological similarity in the protein-protein interaction network

Abstract

Polycystic ovary syndrome (PCOS) is one of the most common endocrinological disorders in reproductive aged women. PCOS and Type 2 Diabetes (T2D) are closely linked in multiple levels and possess high pathobiological similarity. Here, we put forward a new computational approach based on the pathobiological similarity to identify PCOS potential drug target modules (PPDT-Modules) and PCOS potential drug targets in the protein-protein interaction network (PPIN). From the systems level and biological background, 1 PPDT-Module and 22 PCOS potential drug targets were identified, 21 of which were verified by literatures to be associated with the pathogenesis of PCOS. 42 drugs targeting to 13 PCOS potential drug targets were investigated experimentally or clinically for PCOS. Evaluated by independent datasets, the whole PPDT-Module and 22 PCOS potential drug targets could not only reveal the drug response, but also distinguish the statuses between normal and disease. Our identified PPDT-Module and PCOS potential drug targets would shed light on the treatment of PCOS. And our approach would provide valuable insights to research on the pathogenesis and drug response of other diseases.

Exploring the Mechanism of Wenshen Huatan Quyu Decotion for PCOS Based on Network Pharmacology and Molecular Docking Verification

“…Pathway analysis shows that the AGE-RAGE pathway is significantly active, which may promote inflammation, apoptosis, and vascular dysfunction [ 30 , 31 ]. In addition, highly active steroid hormone pathways include androgen receptor (AR) and progestin (PGR), reflecting hormonal disturbances in PCOS patients [ 32 , 33 ]. The pharmacological effects of WHQD involve several signaling pathways that are responsible for steroid hormone production, insulin resistance, and anovulation in women with polycystic ovary syndrome [ 34 , 35 ].…”

Repurposing new drug candidates and identifying crucial molecules underlying PCOS Pathogenesis Based On Bioinformatics Analysis

“…Hao Huang et al also reported a new computational approach to determine PPDT-Modules and PCOS potential drug targets in protein–protein interaction networks (PPIN). In their study, one PPDT-Module and 21 PCOS drug targets were identified, which 42 drugs targeting 13 PCOS drug targets (ESR1, RXRA, NCOA1, ESR2, THRB, RARA, PPARA, PPARG, PGR, ESRRG, RXRB, RARG, and VDR) were reported to be previously investigated experimentally [ 80 ]. Yu Wang et al also attempted to predict candidate target proteins related to PCOS and its known targets for clinical drugs and suggested some potential candidate targets, including ESR1, PGR, AR, AKR1C3, INSR, THRB, PTPN1, DPP4, NR3C1, HSD11B1, and METAP2 for berberine and other drugs related to PCOS.…”

Network‐Wide Screen Identifies Variation of Novel Precise On‐Module Targets Using Conformational Modudaoism

“…The equilibrium in a biomolecular system results from a balance between energy and entropy, and entropy‐driven structural and energy variations may be a critical factor to identify the active modules in biological networks. Many previous studies have discussed the conserved gene expressions or modules, but few methods have been exploited to measure the structural and energy variations of modules. Methods based on overlapping nodes or edges may not reflect the modular topological properties globally, and optimized models are required to quantitatively evaluate module variation from a topological structure and energy perspective.…”