SNPeffect 4.0: on-line prediction of molecular and structural effects of protein-coding variants.

SNPeffect 4.0: on-line prediction of molecular and structural effects of protein-coding variants.
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DOI:
10.1093/nar/gkr996
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发表时间:
2012-01
影响因子:
14.9
通讯作者:
Rousseau F
Rousseau F
中科院分区:
生物学2区
文献类型:
--
作者:
De Baets G;Van Durme J;Reumers J;Maurer-Stroh S;Vanhee P;Dopazo J;Schymkowitz J;Rousseau F

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单核苷酸变异(SNV)与拷贝数变异一起是人类基因组变异的主要来源,并与表型变异(如对药物治疗的反应改变和对疾病的易感性)相关。将非同义SNV的结构效应与功能结果联系起来是结构生物信息学中的一个主要问题。SNPeffect数据库(snpeffect.switchlab.org)使用基于序列和结构的生物信息学工具来预测蛋白质编码SNV对蛋白质结构表型的影响。它集成了聚集预测(TANGO),淀粉样蛋白预测(WALTZ),伴侣结合预测(LIMBO)和蛋白质稳定性分析(FoldX)的结构表型。此外,SNPeffect还包含受影响的催化位点和许多翻译后修饰的信息。该数据库包含UniProt所有已知的人类蛋白质变体,但用户现在也可以提交自定义蛋白质变体进行SNP效应分析,包括自动结构建模。新的荟萃分析应用程序允许绘制用户选择的一组变体的表型特征之间的相关性。
Single nucleotide variants (SNVs) are, together with copy number variation, the primary source of variation in the human genome and are associated with phenotypic variation such as altered response to drug treatment and susceptibility to disease. Linking structural effects of non-synonymous SNVs to functional outcomes is a major issue in structural bioinformatics. The SNPeffect database (http://snpeffect.switchlab.org) uses sequence- and structure-based bioinformatics tools to predict the effect of protein-coding SNVs on the structural phenotype of proteins. It integrates aggregation prediction (TANGO), amyloid prediction (WALTZ), chaperone-binding prediction (LIMBO) and protein stability analysis (FoldX) for structural phenotyping. Additionally, SNPeffect holds information on affected catalytic sites and a number of post-translational modifications. The database contains all known human protein variants from UniProt, but users can now also submit custom protein variants for a SNPeffect analysis, including automated structure modeling. The new meta-analysis application allows plotting correlations between phenotypic features for a user-selected set of variants.
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