Comprehensive characterization of coding and non-coding single nucleotide polymorphisms of the Myoneurin (MYNN) gene using molecular dynamics simulation and docking approaches

Abstract

Genome-wide association studies (GWAS) identified a coding single nucleotide polymorphism, MYNN rs10936599, at chromosome 3q. MYNN gene encodes myoneurin protein, which has been associated with several cancer pathogenesis and disease development processes. However, there needed to be a more detailed characterization of this polymorphism's (and other coding and non-coding polymorphisms) structural, functional, and molecular impact. The current study addressed this gap and analyzed different properties of rs10936599 and non-coding SNPs of MYNN via a thorough computational method. The variant, rs10936599, was predicted functionally deleterious by nine functionality prediction approaches, like SIFT, PolyPhen-2, and REVEL, etc. Following that, structural modifications were estimated through the HOPE server and Mutation3D. Moreover, the mutation was found in a conserved and active residue, according to ConSurf and CPORT. Further, the secondary structures were predicted, followed by tertiary structures, and there was a significant deviation between the native and variant models. Similarly, molecular simulation also showed considerable differences in the dynamic pattern of the wildtype and mutant structures. Molecular docking revealed that the variant binds with better docking scores with ligand NOTCH2. In addition to that, non-coding SNPs located at the MYNN locus were retrieved from the ENSEMBL database. These were found to disrupt the transcription factor binding regulatory regions; nonetheless, only two affect miRNA target sites. Again, eight non-coding variants were detected in the testes with normalized expression, whereas HaploReg v4.1 unveiled annotations for non-coding variants. In summary, in silico comprehensive characterization of coding and non-coding single nucleotide polymorphisms of MYNN gene will assist researchers to work on MYNN gene and establish their association with certain types of cancers.

Fig 1. Flowchart of the pipeline of the analysis.

Fig 2. Deleterious effect of rs10936599 in several web tools.

Fig 3

A) Interaction of MYNN with other cellular proteins. B) Significant GO terms associated with MYNN.

Fig 4

A) Demonstration of the protein used in ribbon display. The side chain of the mutant residue is represented as little balls and is highlighted magenta, along with the protein, which is highlighted grey. B) Close-up of the substitution, where the protein is shaded grey along with the side of wildtype and mutant amino acid in green and red, respectively.

Fig 5. Visualization of conservational analysis in ConSurf.

Fig 6

A) Model structure of wildtype protein. B) Model structure of nsSNP protein. C) Superimposed display of wildtype and variant structure, where wildtype is colored in green and variant in purple. D) Superimposition of the mutated amino acid position in both models. The wildtype structure is shaded in green and nsSNP in purple.

Fig 7

Visualization of the molecular docking complexes of A) wildtype with NOTCH2 B) nsSNP with NOTCH. Here, variant and wildtype structures are shaded in grey, whereas NOTCH is highlighted in green. Ligand interactions in C) wildtype and NOTCH2 complex D) variant and NOTCH2 with hydrogen bond donor/acceptor surface.

Fig 8. RMSD, RMSF, Radius of gyration, and SASA analysis of wildtype MYNN (blue) and variant MYNN (yellow) protein following molecular dynamic simulations.

Fig 9. Demonstration of the number of non-coding SNPs located in various regulome ranks.

Here, 3a, 5, and 6 denote TF binding + any motif + DNase peak, TF binding or DNase peak, and motif hit, respectively.