scholarly journals Using protease inhibitors to improve protein stability in the presence of skin: A case study on the stability of insulin like growth factor 1

2021 ◽  
Vol 158 ◽  
pp. 379-381
Author(s):  
S. Dubey ◽  
R. Perozzo ◽  
L. Scapozza ◽  
Y.N. Kalia
Keyword(s):  
Growth Factor ◽  
Protein Stability ◽  
Protease Inhibitors ◽  
Insulin Like Growth Factor ◽  
The Stability

scholarly journals Prediction of the stability of proteins by computational approaches: a case report

2018 ◽  
Author(s):  
Bernardina Scafuri ◽  
Angelo Facchiano ◽  
Anna Marabotti
Keyword(s):  
Case Report ◽  
Protein Stability ◽  
Protein Sequence ◽  
Genotypic Variation ◽  
Missense Mutations ◽  
Computational Approaches ◽  
The Past ◽  
The Stability ◽  
The Impact

The prediction of the stability of a protein is a very important issue in computational biology. Indeed, missense mutations are frequently associated to a change in protein stability, leading usually to destabilization, unfolding and aggregation. However, the direct measurement of the effect of mutations on proteins' stability is often impaired by the large number of mutations that can affect a protein sequence. Therefore, predicting the impact of a mutation on this feature is of remarkable interest to infer the phenotypic effects associated to a genotypic variation. For this reason, many different predictors of the effects of mutations on protein stability have been developed during the past years, and they are available online as Web servers. In the present work, we applied several tools based on different approaches to predict the stability of three proteins involved in the different forms of the rare disease galactosemia, and we compare their different results, describing also the problems that we had to face, the solutions that we have adopted and the lessons learnt from this case study.

scholarly journals Insulin-Like Growth Factor Binding Protein-3 Exerts Its Anti-Metastatic Effect in Aerodigestive Tract Cancers by Disrupting the Protein Stability of Vimentin

Cancers ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 1041
Author(s):  
Huong Thuy Le ◽  
Ho Jin Lee ◽  
Jaebeom Cho ◽  
Hye-Young Min ◽  
Ji-Sun Lee ◽  
...  
Keyword(s):  
Growth Factor ◽  
Protein Stability ◽  
Binding Protein ◽  
Migration And Invasion ◽  
Insulin Like Growth Factor ◽  
Factor Binding ◽  
Local Invasion ◽  
Igfbp 3

The proapoptotic, antiangiogenic, and antimetastatic activities of insulin-like growth factor binding protein-3 (IGFBP-3) through IGF-dependent or -independent mechanisms have been suggested in various types of human cancers. However, a mechanistic explanation of and downstream targets involved in the antimetastatic effect of IGFBP-3 is still lacking. In this study, by applying various in vitro and in vivo models, we show that IGFBP-3 suppresses migration and invasion of human head and neck squamous carcinoma (HNSCC) and non-small cell lung cancer (NSCLC) cells. Silencing IGFBP-3 expression elevated the migration and invasion of NSCLC and HNSCC cells in vitro and their local invasion and metastasis in vivo, whereas overexpression of IGFBP-3 decreased such prometastatic changes. Local invasion of 4-nitroquinoline-1-oxide (4-NQO)-induced HNSCC tumors was consistently significantly potentiated in Igfbp3 knockout mice compared with that in wild-type mice. Mechanistically, IGFBP-3 disrupted the protein stability of vimentin via direct binding and promoting its association with the E3 ligase FBXL14, causing proteasomal degradation. The C-terminal domain of IGFBP-3 and the head domain of vimentin are essential for their interaction. These results provide a molecular framework for IGFBP-3′s IGF-independent antimetastatic and antitumor activities.

scholarly journals Cooperative Repression of Insulin-Like Growth Factor Type 2 Receptor Translation by MicroRNA 195 and RNA-Binding Protein CUGBP1

2017 ◽  
Vol 37 (19) ◽  
Author(s):  
Yuan Zhang ◽  
Yun Zhang ◽  
Lan Xiao ◽  
Ting-Xi Yu ◽  
Jun-Zhe Li ◽  
...  
Keyword(s):  
Growth Factor ◽  
Mammalian Cells ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Binding Protein ◽  
Insulin Like Growth Factor ◽  
Factor Type ◽  
Mucosal Adaptation ◽  
The Stability

ABSTRACT Insulin-like growth factor type 2 (IGF2) receptor (IGF2R) recognizes mannose 6-phosphate-containing molecules and IGF2 and plays an important role in many pathophysiological processes, including gut mucosal adaptation. However, the mechanisms that control cellular IGF2R abundance are poorly known. MicroRNAs (miRNAs) and RNA-binding proteins (RBPs) critically regulate gene expression programs in mammalian cells by modulating the stability and translation of target mRNAs. Here we report that miRNA 195 (miR-195) and RBP CUG-binding protein 1 (CUGBP1) jointly regulate IGF2R expression at the posttranscriptional level in intestinal epithelial cells. Both miR-195 and CUGBP1 interacted with the 3′ untranslated region (3′-UTR) of Igf2r mRNA, and the association of CUGBP1 with Igf2r mRNA enhanced miR-195 binding to Igf2r mRNA. Ectopically expressed CUGBP1 and miR-195 repressed IGF2R translation cooperatively without altering the stability of Igf2r mRNA. Importantly, the miR-195- and CUGBP1-repressed levels of cellular IGF2R led to a disruption in the structure of the trans-Golgi network. These findings indicate that IGF2R expression is controlled posttranscriptionally by two factors that associate with Igf2r mRNA and suggest that miR-195 and CUGBP1 dampen IGF signaling by inhibiting IGF2R translation.

scholarly journals Repeated Insulin-Like Growth Factor 1 Treatment in a Patient with Rett Syndrome: A Single Case Study

2014 ◽  
Vol 2 ◽  
Author(s):  
Giorgio Pini ◽  
M. Flora Scusa ◽  
Alberto Benincasa ◽  
Ilaria Bottiglioni ◽  
Laura Congiu ◽  
...  
Keyword(s):  
Growth Factor ◽  
Rett Syndrome ◽  
Single Case ◽  
Insulin Like Growth Factor ◽  
Single Case Study

scholarly journals Prediction of the stability of proteins by computational approaches: a case report

2018 ◽  
Author(s):  
Bernardina Scafuri ◽  
Angelo Facchiano ◽  
Anna Marabotti
Keyword(s):  
Case Report ◽  
Protein Stability ◽  
Protein Sequence ◽  
Genotypic Variation ◽  
Missense Mutations ◽  
Computational Approaches ◽  
The Past ◽  
The Stability ◽  
The Impact

The prediction of the stability of a protein is a very important issue in computational biology. Indeed, missense mutations are frequently associated to a change in protein stability, leading usually to destabilization, unfolding and aggregation. However, the direct measurement of the effect of mutations on proteins' stability is often impaired by the large number of mutations that can affect a protein sequence. Therefore, predicting the impact of a mutation on this feature is of remarkable interest to infer the phenotypic effects associated to a genotypic variation. For this reason, many different predictors of the effects of mutations on protein stability have been developed during the past years, and they are available online as Web servers. In the present work, we applied several tools based on different approaches to predict the stability of three proteins involved in the different forms of the rare disease galactosemia, and we compare their different results, describing also the problems that we had to face, the solutions that we have adopted and the lessons learnt from this case study.

scholarly journals The Variations of Insulin-like Growth Factor 1 Measured between Siemens Immulite, DiaSorin Liaison and IDS iSYS

2021 ◽  
Vol 156 (Supplement_1) ◽  
pp. S52-S52
Author(s):  
J K Lee ◽  
S Li
Keyword(s):  
Regression Analysis ◽  
Growth Factor ◽  
Insulin Like Growth Factor ◽  
Positive Bias ◽  
Hormone Activity ◽  
Bland Altman Method ◽  
Deming Regression ◽  
Hypothalamic Pituitary Axis ◽  
Potential Impact

Abstract Introduction/Objective Insulin-like Growth Factor 1 (IGF-1) is a biomarker for the evaluation of growth hormone activity in the hypothalamic-pituitary axis. The current most common methodology for IGF-1 measurement is automated immunometric assays. In this study, we compared the IGF-1 on Siemens Immulite 2000, DiaSorin Liaison XL and IDS iSYS. Methods/Case Report Residual 30-110 serum specimens were randomly selected from routine hospital orders. IGF- 1 was measured on these three platforms and compared with Passing-Bablok regression. Bias was evaluated using the Bland-Altman method. Results (if a Case Study enter NA) Weighted Deming regression analysis showed approximately 80% and 56% positive bias on IDS iSYS and DiaSorin Liaison, compared with Siemens Immulite (iSYS=1.81*Immulite-117.65, r=0.91; Liaison=1.56*Immulite-4.58, r=0.98). There was approximately 8% positive bias on Liaison, compared with iSYS (Liaison=1.08*iSYS+0.56, r=0.99). The Passing-Bablok regression analysis revealed approximately 67% and 54% positive bias (iSYS=1.67*Immulite-75, r=0.91; Liaison=1.54*Immulite-3.44, r=0.91). Approximately 8% positive bias on Liaison was observed, compared with iSYS (Liaison=1.08*iSYS+5.65, r=0.99). The Bland-Altman plot showed the agreement between iSYS and Immulite IGF-1 was on average 129.6±123.3 ng/mL, 98.6±148.8 ng/mL between Liaison and Immulite and 37.0±46.5 ng/mL between Liaison and iSYS. Conclusion Immunoassays rely on the specificity of antibodies. There are wide variations between different immunoassay platforms for IGF-1 measurement. The standardization of IGF-1 assay is lack. It would be a challenge for clinicians to monitor IGF-1 or treat the patients with pituitary disorders, when switching to another platform. The potential impact of the variations in IGF-1 measurement between different immunoassay platforms should be aware.

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