Computational Prediction Of High-Confidence Nonsynonymous SNPs In Genes In The Glucocorticoid Pathway Associated With The Glucocorticoid Response In Patients With Nephrotic Syndrome

Objective: To identify high-confidence nonsynonymous single nucleotide polymorphisms(nsSNPs)associated with GCs resistance in human genes in the GCs pathway.Methods: In total,12 computational biology methods were used to predict high-confidence nsSNPs in the GCs pathway.First,we predicted “damaging” nsSNPs using sequence homology-based approaches(SIFT and PROVEAN).Subsequently,we performed structural homology-based predictions of “deleterious” nsSNPs using PolyPhen-2 and MutationAssessor.We then used a machine learning-based approach to predict disease-related SNPs using SNAP2,PhD-SNP,PANTHER and SNPs&GO.We evaluated the effects of amino acid substitutions on protein stability using the SDM server.Furthermore,we identified disease phenotypes associated with nsSNPs using MutPred2,and Clustal Omega and ConSurf were used for multiple sequence alignment and phylogenetic analysis.Results: 41 nsSNPs were predicted from 4198 nsSNPs as candidate SNPs.The predicted high-confidence nsSNPs were ABCB1(R262G,G534 V,R538S,R543 H,R543P,D555 G,R789Q,E913 K,G1063C,G1179 C,R1183S,R1183 C,R1183H and R1188H),CRHR1(R85W),CYP3A4(R130P and G436R),CYP3A5(R105G,E362 G,R375G,G435 R,G435E and R439T),FKBP4(R152C and R358C),FKBP5(E101K and I122N),HSD11B1(S43I and G173R),HSP90AA1(E42G,R182 G,R182C,E308 V,P379R,P379 L,R456W and S468F),NR3C1(R477H)and STIP1(H38D,D60 G and E271G),all of which are candidates for case–control studies to determine clinical significance.Conclusion: A total of 41 high-confidence nsSNPs were found in 10 genes,among which G534 V,R538S and R477 H showed biological effects.The 41 high-confidence nsSNPs predicted by us are likely to lead to changes in protein function and structure,further affecting the activity of enzymes and biomacromolecules,and affecting the GC pathway,resulting in differences in GC reactivity.Therefore,they can be used as candidate SNPs for clinical studies to further clarify their clinical significance.