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BeEP 服务器:利用进化信息评估蛋白质结构模型的质量。

BeEP Server: Using evolutionary information for quality assessment of protein structure models.

机构信息

Departamento de Ciencia y Tecnologia, Universidad Nacional de Quilmes, B1876BXD, Bernal, Buenos Aires, Argentina.

出版信息

Nucleic Acids Res. 2013 Jul;41(Web Server issue):W398-405. doi: 10.1093/nar/gkt453. Epub 2013 May 31.

Abstract

The BeEP Server (http://www.embnet.qb.fcen.uba.ar/embnet/beep.php) is an online resource aimed to help in the endgame of protein structure prediction. It is able to rank submitted structural models of a protein through an explicit use of evolutionary information, a criterion differing from structural or energetic considerations commonly used in other assessment programs. The idea behind BeEP (Best Evolutionary Pattern) is to benefit from the substitution pattern derived from structural constraints present in a set of homologous proteins adopting a given protein conformation. The BeEP method uses a model of protein evolution that takes into account the structure of a protein to build site-specific substitution matrices. The suitability of these substitution matrices is assessed through maximum likelihood calculations from which position-specific and global scores can be derived. These scores estimate how well the structural constraints derived from each structural model are represented in a sequence alignment of homologous proteins. Our assessment on a subset of proteins from the Critical Assessment of techniques for protein Structure Prediction (CASP) experiment has shown that BeEP is capable of discriminating the models and selecting one or more native-like structures. Moreover, BeEP is not explicitly parameterized to find structural similarities between models and given targets, potentially helping to explore the conformational ensemble of the native state.

摘要

BeEP 服务器(http://www.embnet.qb.fcen.uba.ar/embnet/beep.php)是一个在线资源,旨在帮助蛋白质结构预测的最后阶段。它能够通过明确使用进化信息对提交的蛋白质结构模型进行排名,这与其他评估程序中常用的结构或能量标准不同。BeEP(最佳进化模式)的理念是利用从一组具有给定蛋白质构象的同源蛋白质中存在的结构约束得出的取代模式。BeEP 方法使用一种考虑蛋白质结构的蛋白质进化模型来构建特定位置的取代矩阵。通过最大似然计算评估这些取代矩阵的适用性,从中可以得出位置特异性和全局得分。这些分数估计从每个结构模型中得出的结构约束在同源蛋白质的序列比对中得到了多好的表示。我们对蛋白质结构预测技术关键评估(CASP)实验中的一组蛋白质的评估表明,BeEP 能够区分模型并选择一个或多个类似天然的结构。此外,BeEP 没有明确参数化来寻找模型和给定目标之间的结构相似性,这可能有助于探索天然状态的构象 ensemble。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2928/3692104/0f2d199014bc/gkt453f1p.jpg

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