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首页> 外文期刊>Biochimica et biophysica acta: BBA: International journal of biochemistry, biophysics and molecular biololgy. Proteins and Proteomics >D2N: Distance to the native
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D2N: Distance to the native

机译：D2N：到本机的距离

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摘要

Root-mean-square-deviation (RMSD), of computationally-derived protein structures from experimentally determined structures, is a critical index to assessing protein-structure-prediction-algorithms (PSPAs). The development of PSPAs to obtain 0 ? RMSD from native structures is considered central to computational biology. However, till date it has been quite challenging to measure how far a predicted protein structure is from its native - in the absence of a known experimentalative structure. In this work, we report the development of a metric "D2N" (distance to the native) - that predicts the "RMSD" of any structure without actually knowing the native structure. By combining physico-chemical properties and known universalities in spatial organization of soluble proteins to develop D2N, we demonstrate the ability to predict the distance of a proposed structure to within ± 1.5 ? error with a remarkable average accuracy of 93.6% for structures below 5 ? from the native. We believe that this work opens up a completely new avenue towards assigning reliable structures to whole proteomes even in the absence of experimentally determined native structures. The D2N tool is freely available at http://www.scfbio-iitd.res.in/software/d2n.jsp.
机译：从实验确定的结构计算得出的蛋白质结构的均方根偏差（RMSD）是评估蛋白质结构预测算法（PSPA）的关键指标。开发PSPA获得0？来自天然结构的RMSD被认为是计算生物学的中心。然而，迄今为止，在没有已知实验/天然结构的情况下，测量预测的蛋白质结构与天然蛋白质之间的距离一直是一个很大的挑战。在这项工作中，我们报告了度量“ D2N”（到本机的距离）的发展-预测了任何结构的“ RMSD”而实际上并不知道本机的结构。通过结合理化性质和可溶性蛋白质的空间组织中已知的普遍性来发展D2N，我们证明了能够预测拟议结构的距离在±1.5？以内的能力。低于5？的结构具有93.6％的显着平均准确度的误差。来自本地。我们相信，即使没有实验确定的天然结构，这项工作也为向整个蛋白质组分配可靠的结构开辟了一条全新的途径。 D2N工具可从http://www.scfbio-iitd.res.in/software/d2n.jsp免费获得。

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