Protein structure prediction on the Web: a case study using the Phyre server
Protein structure prediction on the Web: a case study using the Phyre server
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DOI：
10.1038/nprot.2009.2
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发表时间：
2009-01-01
期刊：
影响因子：
14.8
通讯作者：
Sternberg, Michael J. E.
中科院分区：
文献类型：
--
作者：
Kelley, Lawrence A.;Sternberg, Michael J. E.
确定新蛋白质的结构和功能是现代生物学许多方面的基石。在过去的几十年里，已经开发了许多用于结构预测的计算工具。至关重要的是，生物界了解这些工具，并能够以知情的方式解释其结果。该协议提供了一个指南，以解释一般的结构预测服务器的输出，特别是一个这样的工具，蛋白质同源性/类比识别引擎（Phyre）。近年来，新的轮廓轮廓匹配算法大大改善了结构预测。虽然Phyre的性能是许多使用此类算法的结构预测系统的典型，但所有这些系统都可以可靠地检测到多达标准序列轮廓搜索两倍的远程同源性。Phyre被生物界广泛使用，每天有4150个提交，并提供了一个简单的结果界面。Phyre需要30分钟来预测250个残基的蛋白质的结构。
Determining the structure and function of a novel protein is a cornerstone of many aspects of modern biology. Over the past decades, a number of computational tools for structure prediction have been developed. It is critical that the biological community is aware of such tools and is able to interpret their results in an informed way. This protocol provides a guide to interpreting the output of structure prediction servers in general and one such tool in particular, the protein homology/analogy recognition engine (Phyre). New profile-profile matching algorithms have improved structure prediction considerably in recent years. Although the performance of Phyre is typical of many structure prediction systems using such algorithms, all these systems can reliably detect up to twice as many remote homologies as standard sequence-profile searching. Phyre is widely used by the biological community, with 4150 submissions per day, and provides a simple interface to results. Phyre takes 30 min to predict the structure of a 250-residue protein.