PMID- 36518037
OWN - NLM
STAT- MEDLINE
DCOM- 20230307
LR  - 20230321
IS  - 1873-4286 (Electronic)
IS  - 1381-6128 (Linking)
VI  - 29
IP  - 1
DP  - 2023
TI  - Insulin Signaling Pathway Model in Adipocyte Cells.
PG  - 37-47
LID - 10.2174/1381612829666221214122802 [doi]
AB  - BACKGROUND: Worldwide, type 2 diabetes mellitus (T2DM) is one of the most 
      pervasive and fastgrowing disorders, bringing long-term adverse effects. T2DM 
      arises from pancreatic beta-cells deficiency to produce enough insulin or when the 
      body cannot effectively use the insulin produced by such cells. Accordingly, 
      early diagnosis will decrease the long-term effects and high-healthcare costs of 
      diabetes. OBJECTIVE: The objective is developing an integrated mathematical model 
      of the insulin signaling network based on Brannmark's model, which can simulate 
      the signaling events more comprehensively with the added key components. METHODS: 
      In this study, a thorough mathematical model of the insulin signaling network was 
      developed by expanding the previously validated model and incorporating the 
      glycogen synthesis module. Parameters (69 parameters) of the integrated model 
      were evaluated by a genetic algorithm by fitting the model predictions to eighty 
      percent of experimental data from the literature. Twenty percent of the 
      experimental data were used to evaluate the final optimized model. RESULTS: The 
      time-response curves indicate that the GS phosphorylation reaches its maximum in 
      response to 10(-7) M insulin after 4 min, while the maximum phosphorylated GSK3 
      is attained within ~50 min. The doseresponse curves for the GSP and GSK3 of the 
      insulin signaling intermediaries in response to the increased concentration of 
      insulin, after 10 min, in the input from 0-100 nM exhibits a decreasing trend, 
      whereas an increasing trend was observed for the GS and GSK3P. The GSK and GS 
      phosphorylation sensitivity was enhanced by increasing the initial insulin 
      concentration level from 0.001 to 100 nM. However, the sensitivity of GSK3 to 
      insulin concentration changes (from 0.001 to 100 nM) was 3-fold higher than GS 
      sensitivity. CONCLUSION: Considerably, the trends of all signaling components 
      simulated by the expanded model shows high compatibility with experimental data 
      (R2 >/= 0.9), which approves the accuracy of the proposed model. The proposed 
      mathematical model can be used in many biological systems and combined with the 
      whole-body model of the blood glucose regulation system for a better 
      understanding of the causes and potential treatment of type 2 diabetes. Although, 
      this model is not a complete description of insulin signaling, yet it can make 
      profound contributions to improvements regarding other important components and 
      signaling branches such as epidermal growth factor (EGF) signaling, as well as 
      signaling in other cell types in the model structure of future works.
CI  - Copyright(c) Bentham Science Publishers; For any queries, please email at 
      epub@benthamscience.net.
FAU - Sheibani, Monir
AU  - Sheibani M
AD  - Pharmaceutical Engineering Laboratory, Pharmaceutical Process Centers of 
      Excellence, School of Chemical Engineering, College of Engineering, University of 
      Tehran, Tehran, Iran.
FAU - Jalali-Farahani, Farhang
AU  - Jalali-Farahani F
AD  - Pharmaceutical Engineering Laboratory, Pharmaceutical Process Centers of 
      Excellence, School of Chemical Engineering, College of Engineering, University of 
      Tehran, Tehran, Iran.
FAU - Zarghami, Reza
AU  - Zarghami R
AD  - Pharmaceutical Engineering Laboratory, Pharmaceutical Process Centers of 
      Excellence, School of Chemical Engineering, College of Engineering, University of 
      Tehran, Tehran, Iran.
FAU - Sadrai, Sima
AU  - Sadrai S
AD  - Department of Pharmaceutics, School of Pharmacy, Tehran University of Medical 
      Sciences, Tehran, Iran.
LA  - eng
PT  - Journal Article
PL  - United Arab Emirates
TA  - Curr Pharm Des
JT  - Current pharmaceutical design
JID - 9602487
RN  - 0 (Insulin)
RN  - EC 2.7.11.26 (Glycogen Synthase Kinase 3)
SB  - IM
MH  - Humans
MH  - Insulin
MH  - *Diabetes Mellitus, Type 2/metabolism
MH  - Glycogen Synthase Kinase 3
MH  - Signal Transduction/physiology
MH  - Phosphorylation
MH  - Adipocytes/metabolism
MH  - *Insulin Resistance/genetics
OTO - NOTNLM
OT  - Insulin signaling
OT  - adipocyte cells
OT  - diabetes
OT  - epidermal growth factor
OT  - glycogen
OT  - mathematical modeling
EDAT- 2022/12/16 06:00
MHDA- 2023/03/08 06:00
CRDT- 2022/12/15 01:32
PHST- 2022/04/02 00:00 [received]
PHST- 2022/11/14 00:00 [accepted]
PHST- 2022/12/16 06:00 [pubmed]
PHST- 2023/03/08 06:00 [medline]
PHST- 2022/12/15 01:32 [entrez]
AID - CPD-EPUB-128258 [pii]
AID - 10.2174/1381612829666221214122802 [doi]
PST - ppublish
SO  - Curr Pharm Des. 2023;29(1):37-47. doi: 10.2174/1381612829666221214122802.