通过对早产相关基因中 nsSNP 的计算机分析鉴定潜在的治疗干预靶点。
Identification of potential therapeutic intervening targets by in-silico analysis of nsSNPs in preterm birth-related genes.
机构信息
Department of Biochemistry, Dow Medical College, Dow University of Health Sciences, Karachi, Pakistan.
Department of Biosciences, Faculty of Life Sciences, Mohammad Ali Jinnah University, Karachi, Pakistan.
出版信息
PLoS One. 2023 Mar 7;18(3):e0280305. doi: 10.1371/journal.pone.0280305. eCollection 2023.
Prematurity is the foremost cause of death in children under 5 years of age. Genetics contributes to 25-40% of all preterm births (PTB) yet we still need to identify specific targets for intervention based on genetic pathways. This study involved the effect of region-specific non-synonymous variations and their transcript level mutational impact on protein functioning and stability by various in-silico tools. This investigation identifies potential therapeutic targets to manage the challenge of PTB, corresponding protein cavities and explores their binding interactions with intervening compounds. We searched 20 genes coding 55 PTB proteins from NCBI. Single Nucleotide Polymorphisms (SNPs) of concerned genes were extracted from ENSEMBL, and filtration of exonic variants (non-synonymous) was performed. Several in-silico downstream protein functional effect prediction tools were used to identify damaging variants. Rare coding variants were selected with an allele frequency of ≤1% in 1KGD, further supported by South Asian ALFA frequencies and GTEx gene/tissue expression database. CNN1, COL24A1, IQGAP2 and SLIT2 were identified with 7 rare pathogenic variants found in 17 transcript sequences. The functional impact analyses of rs532147352 (R>H) of CNN1 computed through PhD-SNP, PROVEAN, SNP&GO, PMut and MutPred2 algorithms showed impending deleterious effects, and the presence of this pathogenic mutation in CNN1 resulted in large decrease in protein structural stability (ΔΔG (kcal/mol). After structural protein identification, homology modelling of CNN1, which has been previously reported as a biomarker for the prediction of PTB, was performed, followed by the stereochemical quality checks of the 3D model. Blind docking approach were used to search the binding cavities and molecular interactions with progesterone, ranked with energetic estimations. Molecular interactions of CNN1 with progesterone were investigated through LigPlot 2D. Further, molecular docking experimentation of CNN1 showed the significant interactions at S102, L105, A106, K123, Y124 with five selected PTB-drugs, Allylestrenol (-7.56 kcal/mol), Hydroxyprogesterone caproate (-8.19 kcal/mol), Retosiban (-9.43 kcal/mol), Ritodrine (-7.39 kcal/mol) and Terbutaline (-6.87 kcal/mol). Calponin-1 gene and its molecular interaction analysis could serve as an intervention target for the prevention of PTB.
早产是 5 岁以下儿童死亡的首要原因。遗传学导致 25-40%的早产(PTB),但我们仍需要根据遗传途径确定具体的干预靶点。本研究通过各种计算机工具研究了区域特异性非同义变异及其对蛋白质功能和稳定性的转录水平突变影响。这项研究确定了潜在的治疗靶点,以应对 PTB 的挑战,对应蛋白腔,并探索它们与介入化合物的结合相互作用。我们从 NCBI 搜索了 20 个编码 55 种 PTB 蛋白的基因。从 ENSEMBL 中提取了相关基因的单核苷酸多态性(SNP),并对外显子变异(非同义)进行了过滤。使用了几种计算机下游蛋白功能效应预测工具来识别有害变异。使用在 1KGD 中频率≤1%的罕见编码变异进行选择,并进一步得到南亚 ALFA 频率和 GTEx 基因/组织表达数据库的支持。在 17 个转录序列中发现了 7 个罕见的致病性变异,确定了 CNN1、COL24A1、IQGAP2 和 SLIT2 中存在 7 个罕见的致病性变异。通过 PhD-SNP、PROVEAN、SNP&GO、PMut 和 MutPred2 算法计算的 rs532147352(R>H)对 CNN1 的功能影响分析表明存在潜在的有害影响,并且 CNN1 中存在这种致病性突变导致蛋白质结构稳定性大幅下降(ΔΔG(kcal/mol)。在鉴定结构蛋白后,对先前报道为 PTB 预测生物标志物的 CNN1 进行同源建模,然后对 3D 模型进行立体化学质量检查。使用盲目对接方法搜索与孕酮的结合腔和分子相互作用,并根据能量估计进行排序。通过 LigPlot 2D 研究了 CNN1 与孕酮的分子相互作用。此外,通过 CNN1 的分子对接实验,研究了与 5 种选定的 PTB 药物 Allylestrenol(-7.56 kcal/mol)、Hydroxyprogesterone caproate(-8.19 kcal/mol)、Retosiban(-9.43 kcal/mol)、Ritodrine(-7.39 kcal/mol)和 Terbutaline(-6.87 kcal/mol)的 S102、L105、A106、K123、Y124 上的显著相互作用。钙调蛋白-1 基因及其分子相互作用分析可作为预防 PTB 的干预靶点。
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