Fig 1.
Entire workflow for nsSNPs screening in the SCN9A gene using computational tools.
Fig 2.
Pie chart distribution of Single nucleotide polymorphisms (SNPs) in SCN9A gene.
Fig 3.
Prediction of functional consequences of nsSNPs by A) SIFT and B) PolyPhen.
Table 1.
High risk non-synonymous SNPs identified by SIFT, Polyphen, Mutpred2 and SNAP2.
Table 2.
Cumulative prediction of possible deleterious nature of nsSNPs.
Table 3.
Prediction of disease causing SNPs by P-Mutant, Meta SNP, PhD SNP and SNP & GO.
Table 4.
List of nsSNP’s predicted by Mu-Pro, I mutant and ConSURF.
Fig 4.
Pie chart displaying the prevalence of deleterious missense mutations.
Evaluation of 15 In silico tools reveals the percentage and numerical quantity of deleterious nsSNPs.
Fig 5.
Procheck-RAMACHANDRAN plot of the native SCN9A predicted model.
Table 5.
Structural validation and comparison of SCN9A gene.
Table 6.
Top ranked binding affinities of 20 compounds with native and mutant proteins.
Fig 6.
Interaction of protein ligands with typical SCN9A and mutant D1778N, F1782V, L1802P, M939V, and V1311M.
Table 7.
Interacting residues obtained from docking.
Wild protein, L1802P, F1782V, D1778N, V1311M and M936V variants with ligands including their binding residues and hydrophobic interactions.