Unraveling the potential effects of non-synonymous single nucleotide polymorphisms (nsSNPs) on the Protein structure and function of the human SLC30A8 gene on type 2 diabetes and colorectal cancer: An In silico approach
Md. Moin Uddin,
Md. Tanvir Hossain,
Md. Arju Hossain,
Asif Ahsan,
Kamrul Hasan Shamim,
Md. Arif Hossen,
Md. Shahinur Rahman,
Md Habibur Rahman,
Kawsar Ahmed,
Francis M. Bui,
Fahad Ahmed Al-Zahrani
Affiliations
Md. Moin Uddin
Department of Biotechnology, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh
Md. Tanvir Hossain
Department of Biotechnology, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh
Md. Arju Hossain
Department of Microbiology, Primeasia University, Banani, Dhaka 1213, Bangladesh; Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Santosh, Tangail 1902, Bangladesh
Asif Ahsan
Department of Biotechnology, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh
Kamrul Hasan Shamim
Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Santosh, Tangail 1902, Bangladesh
Md. Arif Hossen
Department of Biochemistry and Molecular Biology, Mawlana Bhashani Science and Technology University, Santosh, Tangail 1902, Bangladesh
Md. Shahinur Rahman
Department of Diabetes and Endocrinology, Pabna Diabetic Association Hospital, Pabna 6600, Bangladesh
Md Habibur Rahman
Department of Computer Science and Engineering, Islamic University, Kushtia 7003, Bangladesh
Kawsar Ahmed
Department of Electrical and Computer Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, S7N 5A9, Canada; Group of Biophotomatiχ, Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University, Santosh, Tangail 1902, Bangladesh; Health Informatics Research Lab, Department of Computer Science and Engineering, Daffodil International University, Daffodil Smart City (DSC), Birulia, Savar, Dhaka-1216, Bangladesh; Corresponding author. Department of Electrical and Computer Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, S7N 5A9, Canada.
Francis M. Bui
Department of Electrical and Computer Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, S7N 5A9, Canada
Fahad Ahmed Al-Zahrani
Department of Computer Engineering, Umm Al-Qura University, Mecca 24381, Saudi Arabia; Corresponding author.
Background and aims: The single nucleotide polymorphisms (SNPs) in SLC30A8 gene have been recognized as contributing to type 2 diabetes (T2D) susceptibility and colorectal cancer. This study aims to predict the structural stability, and functional impacts on variations in non-synonymous SNPs (nsSNPs) in the human SLC30A8 gene using various computational techniques. Materials and methods: Several in silico tools, including SIFT, Predict-SNP, SNPs&GO, MAPP, SNAP2, PhD-SNP, PANTHER, PolyPhen-1,PolyPhen-2, I-Mutant 2.0, and MUpro, have been used in our study. Results: After data analysis, out of 336 missenses, the eight nsSNPs, namely R138Q, I141N, W136G, I349N, L303R, E140A, W306C, and L308Q, were discovered by ConSurf to be in highly conserved regions, which could affect the stability of their proteins. Project HOPE determines any significant molecular effects on the structure and function of eight mutated proteins and the three-dimensional (3D) structures of these proteins. The two pharmacologically significant compounds, Luzonoid B and Roseoside demonstrate strong binding affinity to the mutant proteins, and they are more efficient in inhibiting them than the typical SLC30A8 protein using Autodock Vina and Chimera. Increased binding affinity to mutant SLC30A8 proteins has been determined not to influence drug resistance. Ultimately, the Kaplan-Meier plotter study revealed that alterations in SLC30A8 gene expression notably affect the survival rates of patients with various cancer types. Conclusion: Finally, the study found eight highly deleterious missense nsSNPs in the SLC30A8 gene that can be helpful for further proteomic and genomic studies for T2D and colorectal cancer diagnosis. These findings also pave the way for personalized treatments using biomarkers and more effective healthcare strategies.
