Liu Ya-He, Li Chun Guang, Zhou Shu-Feng
Discipline of Chinese Medicine, School of Health Sciences, RMIT University, Bundoora, Victoria 3083, Australia.
Drug Metab Lett. 2009 Dec;3(4):242-86. doi: 10.2174/187231209790218145.
The nuclear receptor (NR) superfamily represents an important group of regulating factors that control the expression of a number of target genes including those encoding important drug metabolizing enzymes and drug transporters. Single nucleotide polymorphism (SNP) is the most common mutation in the human genome and a large number of SNPs have been identified to date. It is unlikely to examine the functional impact of all these mutations using an experimental approach. As such, we employed two algorithms, Sorting Intolerant from Tolerant (SIFT) and Polymorphism Phenotyping (PolyPhen) to predict the impact of non-synonymous SNPs (nsSNPs) on NR activities and disease susceptibility. We identified 442 nsSNPs in a systematic screening of 48 human NR genes. Using SIFT, of 442 amino acid substitutions, 289 (65.38%) were classified as "intolerant". The PolyPhen program classified 269 (60.86%) of them as "probably damaging" or "possibly damaging". The results from the two algorithms were in concordance. Among the 442 mutations, 229 of them have been functionally characterized. SIFT predicted 192 of these nsSNPs as "intolerant", resulting in a correct prediction rate of 83.84%, while PolyPhen gave a prediction rate of 76.86%. For 216 nsSNPs of the androgen receptor gene, 149 nsSNPs have been functionally studied and most (121) of them resulted in a reduction of receptor activity. SIFT sorted 187 out of 216 as "intolerant" (86.57%) and PolyPhen identified 159 out of 216 as "potentially intolerant" (73.61%). These results indicate that both SIFT and PolyPhen are useful and efficient tools to predict the functional effects of nsSNPs of human NR genes.
核受体（NR）超家族是一组重要的调节因子，可控制许多靶基因的表达，包括那些编码重要药物代谢酶和药物转运蛋白的基因。单核苷酸多态性（SNP）是人类基因组中最常见的突变，迄今为止已鉴定出大量的SNP。使用实验方法来检测所有这些突变的功能影响不太可能。因此，我们采用了两种算法，即从耐受中筛选不耐受（SIFT）和多态性表型分析（PolyPhen），来预测非同义SNP（nsSNP）对NR活性和疾病易感性的影响。我们在对48个人类NR基因的系统筛选中鉴定出442个nsSNP。使用SIFT，在442个氨基酸替换中，有289个（65.38%）被分类为“不耐受”。PolyPhen程序将其中269个（60.86%）分类为“可能有害”或“可能有害”。两种算法的结果一致。在这442个突变中，有229个已进行了功能表征。SIFT将这些nsSNP中的192个预测为“不耐受”，正确预测率为83.84%，而PolyPhen的预测率为76.86%。对于雄激素受体基因的216个nsSNP，其中149个已进行了功能研究，其中大多数（121个）导致受体活性降低。SIFT将216个中的187个分类为“不耐受”（86.57%），PolyPhen将216个中的159个鉴定为“潜在不耐受”（73.61%）。这些结果表明，SIFT和PolyPhen都是预测人类NR基因nsSNP功能效应的有用且有效的工具。
