Jibon Md Delowar Kobir, Islam Md Asadul, Hosen Md Eram, Faruqe Md Omar, Zaman Rashed, Acharjee Uzzal Kumar, Sikdar Biswanath, Tiruneh Yewulsew Kebede, Khalekuzzaman Md, Jawi Motasim, Zaki Magdi E A
Professor Joardar DNA and Chromosome Research Laboratory, Department of Genetic Engineering and Biotechnology, University of Rajshahi, Rajshahi, 6205, Bangladesh.
Biomedical Science and Molecular Biology, College of Medicine and Dentistry, James Cook University, Townsville, Australia.
BMC Genomics. 2025 May 15;26(1):492. doi: 10.1186/s12864-025-11655-1.
Single nucleotide polymorphisms are the most prevalent type of DNA variation occurring at a single nucleotide within the genomic sequence. The AVPR1a gene exhibits genetic polymorphism and is linked to neurological and developmental problems, including autism spectrum disorder. Due to the difficulties of studying all non-synonymous single nucleotide polymorphisms (nsSNPs) of the AVPR1a gene in the general population, our goal is to use a computational approach to identify the most detrimental nsSNPs of the AVPR1a gene. We employed several bioinformatics tools, such as SNPnexus, PROVEAN, PANTHER, PhD-SNP, SNP & GO, and I-Mutant2.0, to detect the 23 most detrimental mutants (R85H, D202N, E54G, H92P, D148Y, C203G, V297M, D148V, S182N, Q108L, R149C, G212V, M145T, G212S, Y140S, F207V, Q108H, W219G, R284W, L93F, P156R, F136C, P107L). Later, we used other bioinformatics tools to perform domain and conservation analysis. We analyzed the consequences of high‑risk nsSNPs on active sites, post-translational modification (PTM) sites, and their functional effects on protein stability. 3D modeling, structure validation, protein-ligand binding affinity prediction, and Protein-protein docking were conducted to verify the presence of five significant substitutions (R284W, Y140S, P107L, R149C, and F207V) and explore the modifications induced due to these mutants. These non-synonymous single nucleotide polymorphisms can potentially be the focus of future investigations into various illnesses caused by AVPR1a malfunction. Employing in-silico methodologies to evaluate AVPR1a gene variants will facilitate the coordination of extensive investigations and the formulation of specific therapeutic approaches for diseases associated with these variations.
单核苷酸多态性是基因组序列中单个核苷酸处发生的最普遍的DNA变异类型。AVPR1a基因表现出遗传多态性，并与包括自闭症谱系障碍在内的神经和发育问题相关。由于在普通人群中研究AVPR1a基因的所有非同义单核苷酸多态性（nsSNPs）存在困难，我们的目标是使用计算方法来识别AVPR1a基因中最有害的nsSNPs。我们使用了几种生物信息学工具，如SNPnexus、PROVEAN、PANTHER、PhD-SNP、SNP & GO和I-Mutant2.0，来检测23个最有害的突变体（R85H、D202N、E54G、H92P、D148Y、C203G、V297M、D148V、S182N、Q108L、R149C、G212V、M145T、G212S、Y140S、F207V、Q108H、W219G、R284W、L93F、P156R、F136C、P107L）。后来，我们使用其他生物信息学工具进行结构域和保守性分析。我们分析了高风险nsSNPs对活性位点、翻译后修饰（PTM）位点的影响及其对蛋白质稳定性的功能作用。进行了三维建模、结构验证、蛋白质-配体结合亲和力预测和蛋白质-蛋白质对接，以验证五个重要替代（R284W、Y140S、P107L、R149C和F207V）的存在，并探索这些突变体引起的修饰。这些非同义单核苷酸多态性可能成为未来对由AVPR1a功能障碍引起的各种疾病进行研究的重点。采用计算机模拟方法评估AVPR1a基因变异将有助于协调广泛的研究，并为与这些变异相关的疾病制定具体的治疗方法。
