A Computational Approach for Structural and Functional Analyses of Disease-associated Mutations in the Human CYLD Gene

Abstract

Tumor suppressor Cylindromatosis protein (CYLD) regulates NF- {kappa}B and JNK signaling pathway 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, PREDICT- SNP, 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 PDB Viewer, 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 13nsSNPs. 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, H827R of CYLD that signifies 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.