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β-防御素 1 型基因中非同义单核苷酸多态性的计算机分析揭示了它们对蛋白质-配体结合位点的影响。

In-silico analysis of non-synonymous single nucleotide polymorphisms in human β-defensin type 1 gene reveals their impact on protein-ligand binding sites.

机构信息

School of Science and Engineering, Department of Computer Science, Università degli studi di Verona, Verona, Italy.

Faculty of Life Sciences, Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan.

出版信息

Comput Biol Chem. 2022 Jun;98:107669. doi: 10.1016/j.compbiolchem.2022.107669. Epub 2022 Mar 26.

Abstract

Single nucleotide polymorphism (SNPs) is an important genetic biomarker to assess protein function and its possible contribution to genetic diseases, such as the β- defensin 1 gene (DEFB1)-associated non-synonymous SNPs (nsSNPs). Defensins are antimicrobial and immunomodulatory peptides, acting as part of innate immunity, and killing bacteria by interacting phosphatidylinositol 4,5-bisphosphate (PIP2). Therefore, we apply cutting-edge computational algorithms to identify detrimental SNPs in the DEFB1 gene that potentially impact PIP2 binding sites. Furthermore, 4 most important nsSNPs in the DEFB1 gene were discovered (C67S, T58S, G62W, and Y35C) and only two of them were found to be linked to the PIP2 binding site-forming residues (Thr58 and Tyr35). Additional molecular docking and molecular dynamics simulations confirmed the decreased binding affinity of DEFB1 to bacterial PIP2 due to these mutations. Overall, this computational study analyzing nsSNPs in DEFB1 provides more understanding of how these missense mutations could impair or change protein functions by altering the PIP2 binding site.

摘要

单核苷酸多态性(SNPs)是评估蛋白质功能及其可能导致遗传疾病的重要遗传生物标志物,如β-防御素 1 基因(DEFB1)相关的非 synonymous SNPs(nsSNPs)。防御素是抗菌和免疫调节肽,作为先天免疫的一部分,通过与磷脂酰肌醇 4,5-二磷酸(PIP2)相互作用来杀死细菌。因此,我们应用最先进的计算算法来识别 DEFB1 基因中可能影响 PIP2 结合位点的有害 SNPs。此外,在 DEFB1 基因中发现了 4 个最重要的 nsSNPs(C67S、T58S、G62W 和 Y35C),其中只有两个与 PIP2 结合位点形成残基(Thr58 和 Tyr35)有关。额外的分子对接和分子动力学模拟证实,由于这些突变,DEFB1 与细菌 PIP2 的结合亲和力降低。总的来说,这项分析 DEFB1 中 nsSNPs 的计算研究提供了更多的了解,这些错义突变如何通过改变 PIP2 结合位点来损害或改变蛋白质功能。

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