Abstract
The NEK6 (NIMA-related kinase 6) serine/threonine kinase is a pivotal player in a multitude of cellular processes, including the regulation of the cell cycle and the response to DNA damage. Its significance extends to disease pathogenesis, as changes in NEK6 activity have been linked to the development of cancer. Non-synonymous single nucleotide polymorphisms (nsSNPs) in NEK6 have been linked to cancer as they alter the protein’s native structure and function. The association between NEK6 activity and cancer development has prompted researchers to explore the effects of genetic variations within the NEK6 gene. Therefore, we utilized advanced computational tools to analyze 155 high-confidence nsSNPs in the NEK6 gene. From this analysis, 21 nsSNPs were identified as potentially harmful, raising concerns about their impact on NEK6 activity and cancer risk. These 21 mutations were then examined for structural alterations, and eight of nsSNPs (I51M, V76A, I134N, Y152D, R171Q, V186G, L237R, and C285S) were found to destabilize the protein. Among the destabilizing mutations screened, a specific mutation, R171Q, stood out due to its conserved nature. To understand its impact on the protein and conformation, all-atom molecular dynamics simulations (MDS) for 100 ns were performed for both Wildtype NEK6 (WT-NEK6) and R171Q. The simulations revealed that the R171Q variant was unstable and led to significant conformational changes in NEK6. This study provides valuable insights into NEK6 dysfunction caused by single amino acid alterations, offering a novel understanding of the molecular mechanisms underlying NEK6-related cancer progression.
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Abbreviations
- EVs:
-
Eigenvectors
- FATHMM:
-
Functional analysis through hidden Markov models
- FEL:
-
Free energy landscape
- HOPES:
-
High-throughput evaluation of protein stability
- NEK6:
-
NIMA (Never In Mitosis Gene A)-related kinase 6
- nsSNP:
-
Non-synonymous single nucleotide polymorphism
- MDS:
-
Molecular dynamics simulations
- PANTHER:
-
Protein ANalysis THrough Evolutionary Relationships
- PCA:
-
Principal component analysis
- PhD-SNP:
-
Predicting human deleterious single nucleotide polymorphisms
- PMut:
-
Protein mutation analysis
- PolyPhen-2:
-
Polymorphism Phenotyping v2
- Provean:
-
Protein variation effect analyzer
- Rg:
-
Radius of gyration
- RMSD:
-
Root-mean-square deviation
- RMSF:
-
Root-mean-square fluctuation
- SASA:
-
Solvent accessible surface area
- SIFT:
-
Sorting intolerant from tolerant
- SNAP:
-
Screening for non-acceptable polymorphisms
- WT:
-
Wild-type
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All the authors are grateful to the Vellore Institute of Technology, Vellore, India for providing the essential facilities to carry out this work.
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" N.K.P and S.E.P: Conceptualization, Literature survey; N.K.P and S.M : Performed experiment ; N.K.P: Wrote the Original draft ; S.E.P: Supervised the work. All authors reviewed the manuscript "
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Panchal, N.K., Mohanty, S. & Prince, S.E. Computational insights into NIMA-related kinase 6: unraveling mutational effects on structure and function. Mol Cell Biochem (2023). https://doi.org/10.1007/s11010-023-04910-0
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DOI: https://doi.org/10.1007/s11010-023-04910-0