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A computational approach for structural and functional analyses of disease-associated mutations in the human CYLD
Arpita Singha Roy1, Tasmiah Feroz1, Md Kobirul Islam1
1Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
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.
Insights
Tumor suppressor cylindromatosis protein (CYLD) mutations can lead to cancer. This study identified high-risk CYLD nsSNPs and analyzed their damaging impact on protein function, revealing key mutations for further cancer research.
Area of Science:
- Genetics and Bioinformatics
- Molecular Biology
- Cancer Research
Background:
- The cylindromatosis protein (CYLD) is a tumor suppressor that regulates NF-κB and JNK signaling pathways by cleaving poly-ubiquitin chains, thereby inhibiting cancer progression.
- Mutations in CYLD can disrupt its structure and function, leading to tumor formation and metastasis.
Purpose of the Study:
- To identify deleterious single nucleotide polymorphisms (nsSNPs) in the CYLD gene using various computational tools.
- To analyze the structural and functional impact of these nsSNPs on CYLD protein.
- To investigate the effect of specific CYLD mutations on CYLD-ubiquitin interactions and protein networks.
Main Methods:
- Utilized computational tools (PANTHER, PROVEAN, PredictSNP, PolyPhen-2, PhD-SNP, PON-P2, SIFT) to identify nsSNPs.
- Assessed nsSNP impact on protein structure and stability using ConSurf, I-Mutant, SDM, Phyre2, HOPE, Swiss-PdbViewer, and Mutation 3D.
- Performed molecular docking, molecular dynamics simulations, principal component analysis, and protein-protein interaction network analysis.
Main Results:
- Identified 13 high-risk nsSNPs out of 446 nsSNPs in the CYLD gene.
- Two nsSNPs, R830K and H827R, significantly impacted CYLD-ubiquitin binding affinity and molecular dynamics.
- Discovered that CYLD interacts with 20 proteins involved in critical biological pathways potentially affected by mutations.
Conclusions:
- In silico analyses identified specific CYLD nsSNPs with significant damaging effects on protein function.
- The identified nsSNPs, particularly R830K and H827R, are potential drivers of cancer development.
- Recommended large-scale association studies and targeted drug design for CYLD-associated cancers.
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