A quality metric for homology modeling: the H-factor.
A quality metric for homology modeling: the H-factor.
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DOI：
10.1186/1471-2105-12-48
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发表时间：
2011-02-04
影响因子：
3
通讯作者：
Koehl P
中科院分区：
文献类型：
--
作者：
di Luccio E;Koehl P
对蛋白质结构的分析提供了对大多数生化功能的基本洞察，从而对疾病的原因和可能的治疗方法提供了深入的了解。由于大多数已知蛋白质的结构不能因为技术或有时简单的时间限制而通过实验来解决，因此蛋白质结构预测有望介入并生成更完整的蛋白质结构宇宙图景。蛋白质结构的分子建模是一个快速发展的领域，自从第一个模型问世以来，人们已经做了大量的工作。建模技术的发展，更具体地说，是那些依赖于现有蛋白质结构实验知识的技术的发展，与高分辨率实验技术的发展密切相关，如核磁共振、X射线结晶学和电子显微镜。然而，实验方法和电子计算机方法之间的这种强烈联系在模型师和实验者中并不是没有批评和担忧。在这篇文章中，我们专注于同源建模，更具体地说，我们回顾了结构生物界是如何看待它的，以及可以做些什么来让实验者记住它对他们来说是一个有价值的资源。我们回顾了常见的实践，并提供了一套构建更好模型的指导方针。为此，我们引入了H因子，这是一种新的评估同源模型质量的指标，模拟了X射线结晶学中的R因子。详细描述了H因子的计算方法，并在一系列测试用例上进行了验证。我们已经开发了一个用于计算蛋白质结构模型的H因子的Web服务。这项服务可在http://koehllab.genomecenter.ucdavis.edu/toolkit/h-factor.上免费使用
The analysis of protein structures provides fundamental insight into most biochemical functions and consequently into the cause and possible treatment of diseases. As the structures of most known proteins cannot be solved experimentally for technical or sometimes simply for time constraints, in silico protein structure prediction is expected to step in and generate a more complete picture of the protein structure universe. Molecular modeling of protein structures is a fast growing field and tremendous works have been done since the publication of the very first model. The growth of modeling techniques and more specifically of those that rely on the existing experimental knowledge of protein structures is intimately linked to the developments of high resolution, experimental techniques such as NMR, X-ray crystallography and electron microscopy. This strong connection between experimental and in silico methods is however not devoid of criticisms and concerns among modelers as well as among experimentalists. In this paper, we focus on homology-modeling and more specifically, we review how it is perceived by the structural biology community and what can be done to impress on the experimentalists that it can be a valuable resource to them. We review the common practices and provide a set of guidelines for building better models. For that purpose, we introduce the H-factor, a new indicator for assessing the quality of homology models, mimicking the R-factor in X-ray crystallography. The methods for computing the H-factor is fully described and validated on a series of test cases. We have developed a web service for computing the H-factor for models of a protein structure. This service is freely accessible at http://koehllab.genomecenter.ucdavis.edu/toolkit/h-factor.
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影响因子：
2.9
作者：
Di Luccio, Eric;Wilson, David K.
通讯作者：
Wilson, David K.
影响因子：
14.9
作者：
Eswar, N;John, B;Sali, A
通讯作者：
Sali, A
影响因子：
6.8
作者：
Buchete, NV;Straub, JE;Thirumalai, D
通讯作者：
Thirumalai, D
DOI：
10.1002/prot.340230412
发表时间：
1995-12-01
期刊：
PROTEINS-STRUCTURE FUNCTION AND GENETICS
影响因子：
--
作者：
Frishman, D;Argos, P
通讯作者：
Argos, P
影响因子：
5.6
作者：
ACHARYA, KR;STUART, DI;PHILLIPS, DC
通讯作者：
PHILLIPS, DC