Identification of Disease Risk DNA Variations is Shaping the Future of Precision Health

Fakhouri, Walid D.; Letra, Ariadne

doi:10.3390/genes10060450

Cited by 1 publication

(1 citation statement)

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“…SLIT2 and ROBO1 gene expression in the cells of placenta and trophoblast may be linked with spontaneous PTB [ 58 ]. In this manner, variant annotations with elaborative approach regarding their role in PTB are needed to interpret the impact of point mutations which can lead to protein structural and functional changes, and may set the basis for the occurrence of APOs [ 59 ]. Our findings about point mutations that may influence protein stability can be useful in drug designing and prevention of PTB.…”

Section: Discussionmentioning

confidence: 99%

Identification of potential therapeutic intervening targets by in-silico analysis of nsSNPs in preterm birth-related genes

et al. 2023

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Prematurity is the foremost cause of death in children under 5 years of age. Genetics contributes to 25–40% of all preterm births (PTB) yet we still need to identify specific targets for intervention based on genetic pathways. This study involved the effect of region-specific non-synonymous variations and their transcript level mutational impact on protein functioning and stability by various in-silico tools. This investigation identifies potential therapeutic targets to manage the challenge of PTB, corresponding protein cavities and explores their binding interactions with intervening compounds. We searched 20 genes coding 55 PTB proteins from NCBI. Single Nucleotide Polymorphisms (SNPs) of concerned genes were extracted from ENSEMBL, and filtration of exonic variants (non-synonymous) was performed. Several in-silico downstream protein functional effect prediction tools were used to identify damaging variants. Rare coding variants were selected with an allele frequency of ≤1% in 1KGD, further supported by South Asian ALFA frequencies and GTEx gene/tissue expression database. CNN1, COL24A1, IQGAP2 and SLIT2 were identified with 7 rare pathogenic variants found in 17 transcript sequences. The functional impact analyses of rs532147352 (R>H) of CNN1 computed through PhD-SNP, PROVEAN, SNP&GO, PMut and MutPred2 algorithms showed impending deleterious effects, and the presence of this pathogenic mutation in CNN1 resulted in large decrease in protein structural stability (ΔΔG (kcal/mol). After structural protein identification, homology modelling of CNN1, which has been previously reported as a biomarker for the prediction of PTB, was performed, followed by the stereochemical quality checks of the 3D model. Blind docking approach were used to search the binding cavities and molecular interactions with progesterone, ranked with energetic estimations. Molecular interactions of CNN1 with progesterone were investigated through LigPlot 2D. Further, molecular docking experimentation of CNN1 showed the significant interactions at S102, L105, A106, K123, Y124 with five selected PTB-drugs, Allylestrenol (-7.56 kcal/mol), Hydroxyprogesterone caproate (-8.19 kcal/mol), Retosiban (-9.43 kcal/mol), Ritodrine (-7.39 kcal/mol) and Terbutaline (-6.87 kcal/mol). Calponin-1 gene and its molecular interaction analysis could serve as an intervention target for the prevention of PTB.

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Section: Discussionmentioning

confidence: 99%