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回忆录:基于模板的膜蛋白结构预测。

Memoir: template-based structure prediction for membrane proteins.

机构信息

Department of Statistics, Oxford University, Oxford, OX1 3TG, UK.

出版信息

Nucleic Acids Res. 2013 Jul;41(Web Server issue):W379-83. doi: 10.1093/nar/gkt331. Epub 2013 May 2.

Abstract

Membrane proteins are estimated to be the targets of 50% of drugs that are currently in development, yet we have few membrane protein crystal structures. As a result, for a membrane protein of interest, the much-needed structural information usually comes from a homology model. Current homology modelling software is optimized for globular proteins, and ignores the constraints that the membrane is known to place on protein structure. Our Memoir server produces homology models using alignment and coordinate generation software that has been designed specifically for transmembrane proteins. Memoir is easy to use, with the only inputs being a structural template and the sequence that is to be modelled. We provide a video tutorial and a guide to assessing model quality. Supporting data aid manual refinement of the models. These data include a set of alternative conformations for each modelled loop, and a multiple sequence alignment that incorporates the query and template. Memoir works with both α-helical and β-barrel types of membrane proteins and is freely available at http://opig.stats.ox.ac.uk/webapps/memoir.

摘要

膜蛋白估计是目前正在开发的 50%药物的靶点,但我们对膜蛋白的晶体结构知之甚少。因此,对于感兴趣的膜蛋白,通常需要从同源建模中获取急需的结构信息。目前的同源建模软件针对球状蛋白进行了优化,忽略了众所周知的膜对蛋白质结构的限制。我们的 Memoir 服务器使用专门为跨膜蛋白设计的对齐和坐标生成软件来生成同源模型。Memoir 使用方便,唯一的输入是结构模板和要建模的序列。我们提供了一个视频教程和一个评估模型质量的指南。支持数据有助于手动改进模型。这些数据包括每个建模环的一组替代构象,以及包含查询和模板的多重序列比对。Memoir 适用于α-螺旋和β-桶类型的膜蛋白,可在 http://opig.stats.ox.ac.uk/webapps/memoir 免费获得。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/370a/3692111/b1c197259615/gkt331f1p.jpg

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