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Status of GPCR modeling and docking as reflected by community-wide GPCR Dock 2010 assessment.通过 2010 年 GPCR 对接评估反映的 GPCR 建模和对接的现状。
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Structure of an agonist-bound human A2A adenosine receptor.激动剂结合的人 A2A 腺苷受体结构。
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Artefacts and biases affecting the evaluation of scoring functions on decoy sets for protein structure prediction.影响用于蛋白质结构预测的诱饵集评分函数评估的假象和偏差。
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Comparing four different approaches for the determination of inter-residue interactions provides insight for the structure prediction of helical membrane proteins.比较四种不同的确定残基间相互作用的方法,可为螺旋膜蛋白的结构预测提供见解。
Biopolymers. 2009 Jul;91(7):547-56. doi: 10.1002/bip.21175.
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Conserved network properties of helical membrane protein structures and its implication for improving membrane protein homology modeling at the twilight zone.螺旋膜蛋白结构的保守网络性质及其对改善 twilight 区膜蛋白同源建模的启示。
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Network pattern of residue packing in helical membrane proteins and its application in membrane protein structure prediction.螺旋膜蛋白中残基堆积的网络模式及其在膜蛋白结构预测中的应用。
Protein Eng Des Sel. 2008 Jan;21(1):55-64. doi: 10.1093/protein/gzm059. Epub 2008 Jan 3.
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基于特定的残基间相互作用,开发用于膜蛋白结构的高质量打分函数。

Developing a high-quality scoring function for membrane protein structures based on specific inter-residue interactions.

机构信息

Department of Chemistry and Biochemistry, University of the Sciences in Philadelphia, Box 48, Philadelphia, PA 19104, USA.

出版信息

J Comput Aided Mol Des. 2012 Mar;26(3):301-9. doi: 10.1007/s10822-012-9556-z. Epub 2012 Mar 1.

DOI:10.1007/s10822-012-9556-z
PMID:22395902
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3322274/
Abstract

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 Interaction-based Quality assessment (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.

摘要

膜蛋白具有特殊的生物学和药物学重要性,计算建模和结构预测方法在膜蛋白研究中起着重要作用。开发一个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。目前提出的此类程序很少能够广泛应用于各种膜蛋白类别,并具有高精度。我们开发了一种新的模型评分函数——基于相互作用的质量评估 (IQ),该函数基于对螺旋膜蛋白跨膜域中四种类型的残基间相互作用的分析。该功能使用三个高质量的模型集进行了测试:2008 年 GPCR Dock 的所有 206 个模型、2010 年 GPCR Dock 的所有 284 个模型以及 HOMEP 集的所有 92 个螺旋膜蛋白模型。对于所有三个模型集,评分函数都可以在所有模型中选择天然结构,成功率分别为 93%、85%和 100%。相比之下,这三个模型集也被用于最近发表的膜蛋白结构模型评估程序 ProQM,该程序的成功率分别为 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是有用的。