Developing a high-quality scoring function for membrane protein structures based on specific inter-residue interactions.
Developing a high-quality scoring function for membrane protein structures based on specific inter-residue interactions.
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DOI：
10.1007/s10822-012-9556-z
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发表时间：
2012-03
影响因子：
3.5
通讯作者：
Li, Zhijun
中科院分区：
文献类型：
--
作者：
Heim, Andrew J.;Li, Zhijun
关键词：
膜蛋白具有特殊的生物学和药物重要性，计算建模和结构预测方法在膜蛋白的研究中发挥着重要作用。开发准确的模型质量评估程序对于膜蛋白的结构预测具有重要意义。很少有人提出这样的程序可以应用于广泛的膜蛋白类别并以高精度执行。基于对螺旋膜蛋白跨膜域内四种残基间相互作用的分析，我们开发了一种新的模型评分函数 IQ。该功能使用三个高质量模型集进行了测试：GPCR Dock 2008 的所有 206 个模型、GPCR Dock 2010 的所有 284 个模型以及 HOMEP 集的所有 92 个螺旋膜蛋白模型。对于所有三组，评分函数都可以在所有模型中选择本地结构，成功率分别为 93%、85% 和 100%。为了进行比较，最近发布的膜蛋白结构模型评估程序 ProQM 也采用了这三个模型集，其成功率分别为 85%、79% 和 92%。这些结果表明，当仅考虑模型的跨膜区域时，IQ 优于 ProQM。该评分函数对于膜蛋白的计算建模应该有用。
Membrane proteins are of particular biological and pharmaceutical importance, and computational modeling and structure prediction approaches play an important role in studies of membrane proteins. Developing an accurate model quality assessment program is of significance to the structure prediction of membrane proteins. Few such programs are proposed that can be applied to a broad range of membrane protein classes and perform with high accuracy. We developed a new model scoring function IQ, based on the analysis of four types of inter-residue interactions within the transmembrane domains of helical membrane proteins. This function was tested using three high-quality model sets: all 206 models of GPCR Dock 2008, all 284 models of GPCR Dock 2010, and all 92 helical membrane protein models of the HOMEP set. For all three sets, the scoring function can select the native structures among all of the models with the success rates of 93%, 85%, and 100% respectively. For comparison, these three model sets were also adopted for a recently published model assessment program for membrane protein structures, ProQM, which gave the success rates of 85%, 79%, and 92% separately. These results suggested that IQ outperforms ProQM when only the transmembrane regions of the models are considered. This scoring function should be useful for the computational modeling of membrane proteins.
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影响因子：
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