Assessing the Performance of In silico Tools and Molecular Dynamics Simulations for Predicting Pharmacogenetic Variant Impact.

The ability of freely available in silico tools to predict the effect of non-synonymous single nucleotide polymorphisms (nsSNPs) in pharmacogenes on protein function is not well defined. We assessed the performance of seven sequence-based (SIFT, PolyPhen2, mutation accessor, FATHMM, PhD-SNP, MutPred2, and SNPs & Go) and five structure-based (mCSM, SDM, DDGun, CupSat, and MAESTROweb) tools in predicting the impact of 118 nsSNPs in the CYP2C19, CYP2C9, CYP2B6, CYP2D6, and DPYD genes with known function (24 normal, one increased, 42 decreased, and 51 no-function). Sequence-based tools had a higher median (IQR) positive predictive value (89% [89-94%] vs. 12% [10-15%], P < 0.001) and lower negative predictive value (30% [24-34%] vs. 90% [80-93%], P < 0.001) than structure-based tools. Accuracy did not significantly differ between sequence-based (59% [37-67%]) and structure-based (34% [23-44%]) tools (P = 0.070). Notably, the no-function CYP2C9*3 allele and decreased function CYP2C9*8 allele were predicted incorrectly as tolerated by 100% of sequenced-based tools and as stabilizing by 60% and 20% of structure-based tools, respectively. As a case study, we performed mutational analysis for the CYP2C9*1, *3 (I359L), and *8 (R150H) proteins through molecular dynamic (MD) simulations using S-warfarin as the substrate. The I359L variant increased the distance of the major metabolic site of S-warfarin to the oxy-ferryl center of CYP2C9, and I359L and R150H caused shifts in the conformation of S-warfarin to a position less favorable for metabolism. These data suggest that MD simulations may better capture the impact of nsSNPs in pharmacogenes than other tools.

Assessing the Knowledge of Analgesic Drugs Utilization during Pregnancy among Women in Saudi Arabia: A Cross-Sectional Study.

BACKGROUND: Pain is a common compensation mechanism in pregnant women that they may face during gestation due to physiological changes. Paracetamol and non-steroidal anti-inflammatory drugs are the most administered analgesic drugs worldwide. Therefore, safety and efficacy are important measures for the use of analgesics during pregnancy. OBJECTIVE: Assess the knowledge of analgesic drug utilization among Saudi pregnant women. METHOD: We conducted a self-administered survey with an electronic questionnaire via Google Drive among a sample of 406 Saudi women. RESULTS: About half of the respondents took analgesics during the first trimester, and 52.5% of women have used analgesics at least once without any medical advice during their gestation. Most participants agreed that paracetamol is the safest and effective analgesic drug during pregnancy, yet 61.8% of women are not aware that analgesics could be detrimental to the fetus if inappropriately administered in the third trimester. CONCLUSION: Participants have a good perception of the safest and most effective analgesic drug during pregnancy, but they have poor knowledge about analgesics' side effects.