Identification of pro- and anti- apoptotic BCL-2 proteins biomarkers for colorectal cancer cells: a comprehensive in-silico computational analysis
Publication Date
March 9, 2024
Creator
Abstract
Colorectal cancer (CRC) is a multifaceted disease characterized by abnormal cell proliferation within the colon and rectum. The BCL-2 family proteins have been implicated in the pathogenesis of CRC, but the impact of genetic variations within these proteins remains elusive. In this in-silico study, we employed diverse sequence and structure-based bioinformatic tools to distinguish potentially pathogenic nonsynonymous single nucleotide polymorphisms (nsSNPs) in BCL-2 family proteins from neutral variants. Leveraging computational tools including SIFT, PolyPhen-2, SNPs&GO, PhD-SNP, PANTHER, and Condel, we predicted 94 nsSNPs as deleterious, damaging, and disease-associated by at least five tools. Further stability analysis using I-Mutant2.0, MutPred, and PredictSNP revealed 31 nsSNPs that induce decreased protein stability. Conservation analysis identified rs960653284, rs758817904, rs1466732626, rs569276903, rs746711568, rs764437421, rs779690846, and rs2038330314 as highly functional and exposed, while rs376149674, rs1375767408, rs1582066443, rs367558446, rs367558446, rs1319541919, and rs1370070128 were considered structural and buried. Subsequently, we explored the structural consequences of these nsSNPs through the assessment of ligand binding energies using molecular docking. Notably, G233D, R102C, and R102P exhibited increased binding affinity towards d-Alpha-Tocopherol and Tocotrienol, suggesting less favourable protein-ligand interactions compared to the wild-type. To the best of our knowledge, this is the first comprehensive analysis of functional nsSNPs in BCL-2 family proteins. We consign confidence that this study holds great promise for future large-scale population-based investigations, provides insights into drug repurposing, and holds potential for the development of diagnostic and therapeutic modalities targeting CRC.
Item Type
ethesis
Thesis Type
MRes
Subjects (LC)
Associated Schools / Departments
School of Biosciences (MY)
eprints ID
76734
UoN Repository URI
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Kong, Amanda Shen-Yee, 20503486, FINAL.pdf
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Full-text
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6.17 MB
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