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Abstract：
Tumor suppressor cylindromatosis protein (CYLD) regulates NF-κB and JNK signaling pathways by cleaving K63-linked poly-ubiquitin chain from its substrate molecules and thus preventing the progression of tumorigenesis and metastasis of the cancer cells. Mutations in CYLD can cause aberrant structure and abnormal functionality leading to tumor formation. In this study, we utilized several computational tools such as PANTHER, PROVEAN, PredictSNP, PolyPhen-2, PhD-SNP, PON-P2, and SIFT to find out deleterious nsSNPs. We also highlighted the damaging impact of those deleterious nsSNPs on the structure and function of the CYLD utilizing ConSurf, I-Mutant, SDM, Phyre2, HOPE, Swiss-PdbViewer, and Mutation 3D. We shortlisted 18 high-risk nsSNPs from a total of 446 nsSNPs recorded in the NCBI database. Based on the conservation profile, stability status, and structural impact analysis, we finalized 13 nsSNPs. Molecular docking analysis and molecular dynamic simulation concluded the study with the findings of two significant nsSNPs (R830K, H827R) which have a remarkable impact on binding affinity, RMSD, RMSF, radius of gyration, and hydrogen bond formation during CYLD-ubiquitin interaction. The principal component analysis compared native and two mutants R830K and H827R of CYLD that signify structural and energy profile fluctuations during molecular dynamic (MD) simulation. Finally, the protein-protein interaction network showed CYLD interacts with 20 proteins involved in several biological pathways that mutations can impair. Considering all these in silico analyses, our study recommended conducting large-scale association studies of nsSNPs of CYLD with cancer as well as designing precise medications against diseases associated with these polymorphisms.
摘要：
肿瘤抑制蛋白（CYLD）通过从其底物分子上裂解K63连接的聚泛素链调节NF-κB和JNK信号通路，从而阻止癌细胞的肿瘤发生和转移。CYLD中的突变可引起结构异常和功能异常,导致肿瘤形成。在这项研究中,我们利用了几种计算工具，如PANTHER，PROVEAN,PredictSNP,PolyPhen-2，博士-SNP，PON-P2和SIFT以找出有害的nsSNP。我们还强调了这些有害的nsSNP对CYLD的结构和功能的破坏性影响，I-Mutant,SDM,Phyre2希望,Swiss-PdbViewer,和突变3D。我们从NCBI数据库中记录的446个nsSNP中筛选出18个高风险nsSNP。根据保护概况，稳定状态，和结构影响分析，我们最终确定了13个nsSNP。分子对接分析和分子动力学模拟得出的研究结论是两个重要的nsSNPs(R830K，H827R)对结合亲和力有显著影响，RMSD,RMSF,回转半径,CYLD-泛素相互作用过程中氢键的形成。主成分分析比较了CYLD的天然和两个突变体R830K和H827R，这表明分子动力学（MD）模拟期间的结构和能量分布波动。最后,蛋白质-蛋白质相互作用网络显示CYLD与20种蛋白质相互作用,这些蛋白质参与突变可能损害的几种生物学途径.考虑到所有这些模拟分析，我们的研究建议对CYLD的nsSNP与癌症进行大规模关联研究,并设计针对这些多态性相关疾病的精确药物.
