In silico Characterization of Esophageal Cancer Predominant Genes

Year 2023, Volume: 27 Issue: 6, 1255 - 1264, 18.12.2023

Gizem Köprülülü Küçük

https://doi.org/10.16984/saufenbilder.1274006

Abstract

Cancer is an important health problem nowadays. One of these problems is esophageal cancer (EC). The 7th most common cancer is EC worldwide. Rhomboid-related biomarkers play an important role in EC. Analysis of such biomarkers can yield important insights into the role of rhomboid 5 Homolog 2 (RHBDF2) in cancer pathology. The characterization of genes was made in silico tools such as STRING, SWISS-MODEL, UCSF Chimera ver 1.15, ProtParam, and GeneCards. The protein interactions string of the rhomboid 5 homologs 2 (RHBDF2) gene was obtained from STRING. Epidermal growth factor (EGF), and ADAM Metallopeptidase Domain 17 (ADAM17) genes were detected as related genes. Amino acid sequences of these genes were obtained from NCBI. Homology models, and Ramachandran graphic of RHBDF2, ADAM17, and EGF genes were created by the SWISS-MODEL database and UCSF Chimera ver 1.15 program. Physicochemical properties of RHBDF2, ADAM17, and EGF genes were calculated by the ProtParam database. Subcellular localizations were detected by the GeneCards server. As a result of this study, genomic and subcellular localization of RHBDF2, ADAM17, and EGF genes were obtained. Amino acid sequences, 3D-protein structures, and physicochemical properties were detected.

Keywords

Eusopagheal cancer, homology model, rhomboid 5 homologs 2 (RHBDF2), epidermal growth factor (EGF), ADAM Metallopeptidase Domain 17 (ADAM17)

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