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Comput Biol Med ; 155: 106630, 2023 03.
Artículo en Inglés | MEDLINE | ID: mdl-36774894

RESUMEN

Colorectal cancer (CRC) is a severe health concern that results from a cocktail of genetic, epigenetic, and environmental abnormalities. Because it is the second most lethal malignancy in the world and the third-most common malignant tumor, but the treatment is unavailable. The goal of the current study was to use bioinformatics and systems biology techniques to determine the pharmacological mechanism underlying putative important genes and linked pathways in early-onset CRC. Computer-aided methods were used to uncover similar biological targets and signaling pathways associated with CRC, along with bioinformatics and network pharmacology techniques to assess the effects of enzastaurin on CRC. The KEGG and gene ontology (GO) pathway analysis revealed several significant pathways including in positive regulation of protein phosphorylation, negative regulation of the apoptotic process, nucleus, nucleoplasm, protein tyrosine kinase activity, PI3K-Akt signaling pathway, pathways in cancer, focal adhesion, HIF-1 signaling pathway, and Rap1 signaling pathway. Later, the hub protein module identified from the protein-protein interactions (PPIs) network, molecular docking and molecular dynamics simulation represented that enzastaurin showed strong binding interaction with two hub proteins including CASP3 (-8.6 kcal/mol), and MCL1 (-8.6 kcal/mol), which were strongly implicated in CRC management than other the five hub proteins. Moreover, the pharmacokinetic features of enzastaurin revealed that it is an effective therapeutic agent with minimal adverse effects. Enzastaurin may inhibit the potential biological targets that are thought to be responsible for the advancement of CRC and this study suggests a potential novel therapeutic target for CRC.


Asunto(s)
Neoplasias Colorrectales , Humanos , Neoplasias Colorrectales/patología , Biología de Sistemas , Simulación del Acoplamiento Molecular , Vías Clínicas , Reposicionamiento de Medicamentos , Fosfatidilinositol 3-Quinasas , Biología Computacional/métodos , Biomarcadores de Tumor/genética
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