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Abstract

Background

Type 2 diabetes (T2D) is a disease of high prevalence that is expected to continue increasing despite the pharmacological treatments available; in most cases, it is difficult to control. Therefore, more research on experimental drugs is necessary to propose better treatments.

Objective

This study aimed to identify the molecular alterations of pancreatic islets in type 2 diabetes through multi-omics data integration and possible pharmacological targets using bioinformatics methods.

Methods

In this study, the OmicsNet tool was used to integrate the multi-omics data associated with T2D, and the protein-protein interaction was visualized. Then, gene ontology and KEGG pathways analyses were carried out. Using the DrugRep server, the hub genes obtained underwent a virtual screening with experimental drugs, and twelve experimental drugs were selected to execute the molecular docking by CB-Dock2. Finally, the interactions were displayed in BIOVIA software.

Results

Our results showed that the main molecular alterations of pancreatic islets in T2D were enzyme binding, mitochondrial metabolism, transcription factors, They were involved in glucose uptake, receptor insulin signaling, and secretion. The molecular docking showed that SRC, AKT1, CREBBP, and HSP90AA1 were therapeutic targets for DB02729, DB04877, DB07970, DB07789, and DB03373.

Conclusion

We identified some alterations in the pancreas of patients with T2D, ten hub genes, and five experimental drugs that could potentially correct gene expression abnormalities. However, further studies are required to validate these results.

© 2025 The Author(s). Published by Bentham Science Publisher.
This is an open access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode.
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2025-04-07
2025-11-04

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/content/journals/cmc/10.2174/0109298673352470250312082922
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Development of Potential Pharmacological Targets to Normalize Gene Expression in Islets of Type 2 Diabetic Patients
Bentham Science Publishers ; https://doi.org/10.2174/0109298673352470250312082922
/content/journals/cmc/10.2174/0109298673352470250312082922
/content/journals/cmc/10.2174/0109298673352470250312082922
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  • Article Type:     Research Article
Keywords: multi-omics ; pancreas ; experimental drugs ; bioinformatics ; Type 2 diabetes ; pharmacology

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