All the information for CYP1B1 missense variants was retrieved from the dbSNP database. Seven different tools, namely: SIFT, PolyPhen-2, PROVEAN, SNAP2, PANTHER, PhD-SNP, and Predict-SNP, were used for functional annotation, and two packages, which were I-Mutant 2.0 and MUpro, were used to predict the effect of the variants on protein stability. A phylogenetic conservation analysis using deleterious variants was performed by the ConSurf server. The 3D structures of the wild-type and mutants were generated using the I-TASSER tool, and a 50 ns molecular dynamic simulation (MDS) was executed using the GROMACS webserver to determine the stability of mutants compared to the native protein. Co-expression, protein-protein interaction (PPI), gene ontology (GO), and pathway analyses were additionally performed for the CYP1B1 in-depth study.
All the retrieved data from the dbSNP database was subjected to functional, structural, and phylogenetic analysis. From the conducted analyses, a total of 19 high-risk variants (P52L, G61E, G90R, P118L, E173K, D291G, Y349D, G365W, G365R, R368H, R368C, D374N, N423Y, D430E, P442A, R444Q, F445L, R469W, and C470Y) were screened out that were considered to be deleterious to the CYP1B1 gene. The phylogenetic analysis revealed that the majority of the variants occurred in highly conserved regions. The MD simulation analysis exhibited that all mutants\' average root mean square deviation (RMSD) values were higher compared to the wild-type protein, which could potentially cause CYP1B1 protein dysfunction, leading to the severity of the disease. Moreover, it has been discovered that CYP1A1, VCAN, HSD17B1, HSD17B2, and AKR1C3 are highly co-expressed and interact with CYP1B1. Besides, the CYP1B1 protein is primarily involved in the metabolism of xenobiotics, chemical carcinogenesis, the retinal metabolic process, and steroid hormone biosynthesis pathways, demonstrating its multifaceted and important roles.
This is the first comprehensive study that adds essential information to the ongoing efforts to understand the crucial role of genetic signatures in the development of PCG and will be useful for more targeted gene-disease association studies.
UNASSIGNED:CYP1B1错义变异的所有信息均从dbSNP数据库中检索。七种不同的工具,即:SIFT,PolyPhen-2,PROVEAN,SNAP2PANTHER,博士-SNP,和预测SNP,用于功能注释,和两个包裹,是I-Mutant2.0和MUpro,用于预测变体对蛋白质稳定性的影响。使用有害变体的系统发育保守分析由ConSurf服务器进行。使用I-TASSER工具生成野生型和突变体的3D结构,并使用GROMACS网络服务器执行50ns分子动态模拟(MDS),以确定突变体与天然蛋白质相比的稳定性。共同表达,蛋白质-蛋白质相互作用(PPI),基因本体论(GO),并对CYP1B1的深入研究进行了通路分析.
UNASSIGNED:从dbSNP数据库中检索到的所有数据都经过函数处理,结构,和系统发育分析。从进行的分析来看,共有19种高风险变体(P52L,G61E,G90R,P118L,E173K,D291G,Y349D,G365W,G365R,R368H,R368C,D374N,N423Y,D430E,P442A,R444Q,F445L,R469W,和C470Y)被筛选出被认为对CYP1B1基因有害的基因。系统发育分析表明,大多数变体发生在高度保守的区域。MD模拟分析显示,与野生型蛋白相比,所有突变体的平均均方根偏差(RMSD)值均较高,这可能会导致CYP1B1蛋白功能障碍,导致疾病的严重程度。此外,已经发现CYP1A1,VCAN,HSD17B1、HSD17B2和AKR1C3高度共表达并与CYP1B1相互作用。此外,CYP1B1蛋白主要参与外源性物质的代谢,化学致癌作用,视网膜代谢过程,和类固醇激素生物合成途径,展示其多方面的重要作用。
UNASSIGNED:这是第一项综合研究,为正在进行的了解遗传特征在PCG发展中的关键作用的努力增加了必要的信息,并将有助于更有针对性的基因-疾病关联研究。