Kaman Tuğba, Karasakal Ömer Faruk, Özkan Oktay Ebru, Ulucan Korkut, Konuk Muhsin
Department of Medicinal and Aromatic Plants, Vocational School of Health Services, Üsküdar University, İstanbul Turkey.
Department of Medical Laboratory Techniques, Vocational School of Health Services, Üsküdar University, İstanbul Turkey.
Turk J Biol. 2019 Dec 13;43(6):371-381. doi: 10.3906/biy-1905-18. eCollection 2019.
The apoptotic protease activating factor 1 () gene encodes a cytoplasmic protein that initiates apoptosis and is a crucial factor in the mitochondria-dependent death pathway. is implicated in many pathways such as apoptosis, neurodegenerative diseases, and cancer. The purpose of this study was to predict deleterious/damaging SNPs in the gene viain silicoanalysis. To this end, missense SNPs were obtained from the NCBI dbSNP database In silico analysis of the missense SNPs was carried out by using publicly available online software tools. The stabilization and three-dimensional modeling of mutant proteins were also determined by using the I-Mutant 2.0 and Project HOPE webservers, respectively. In total, 772 missense SNPs were found in the gene from the NCBI dbSNP database, 18 SNPs of which were demonstrated to be deleterious or damaging. Of those, 13 SNPs had a decreasing effect on protein stability, while the other 5 SNPs had an increasing effect. Based on the modeling results, some dissimilarities of mutant type amino acids from wild-type amino acids such as size, charge, and hydrophobicity were revealed. The SNPs predicted to be deleterious in this study might be used in the selection of target SNPs for genotyping in disease association studies. Therefore, we could suggest that the present study could pave the way for future experimental studies.
凋亡蛋白酶激活因子1（）基因编码一种启动细胞凋亡的胞质蛋白，是线粒体依赖性死亡途径中的关键因子。它涉及许多途径，如细胞凋亡、神经退行性疾病和癌症。本研究的目的是通过计算机分析预测该基因中有害/损伤性单核苷酸多态性（SNP）。为此，从NCBI的dbSNP数据库中获取错义SNP，利用公开可用的在线软件工具对错义SNP进行计算机分析。突变蛋白的稳定性和三维建模也分别通过I-Mutant 2.0和Project HOPE网络服务器进行测定。从NCBI的dbSNP数据库中总共发现该基因有772个错义SNP，其中18个SNP被证明是有害或损伤性的。其中，13个SNP对蛋白质稳定性有降低作用，另外5个SNP有增加作用。基于建模结果，揭示了突变型氨基酸与野生型氨基酸在大小、电荷和疏水性等方面的一些差异。本研究中预测为有害的SNP可用于疾病关联研究中基因分型的目标SNP选择。因此，我们可以认为本研究可为未来的实验研究铺平道路。
