Hurwitz Naama, Pellegrini-Calace Marialuisa, Jones David T
Bioinformatics Unit, Department of Computer Science, Darwin Building, University College London, Gower Street, London WC1E 6BT, UK.
Philos Trans R Soc Lond B Biol Sci. 2006 Mar 29;361(1467):465-75. doi: 10.1098/rstb.2005.1804.
In this paper we briefly review some of the recent progress made by ourselves and others in developing methods for predicting the structures of transmembrane proteins from amino acid sequence. Transmembrane proteins are an important class of proteins involved in many diverse biological functions, many of which have great impact in terms of disease mechanism and drug discovery. Despite their biological importance, it has proven very difficult to solve the structures of these proteins by experimental techniques, and so there is a great deal of pressure to develop effective methods for predicting their structure. The methods we discuss range from methods for transmembrane topology prediction to new methods for low resolution folding simulations in a knowledge-based force field. This potential is designed to reproduce the properties of the lipid bilayer. Our eventual aim is to apply these methods in tandem so that useful three-dimensional models can be built for a large fraction of the transmembrane protein domains in whole proteomes.
在本文中，我们简要回顾了我们自己以及其他研究人员近期在开发从氨基酸序列预测跨膜蛋白结构方法方面取得的一些进展。跨膜蛋白是一类重要的蛋白质，参与多种不同的生物学功能，其中许多功能在疾病机制和药物发现方面具有重大影响。尽管它们具有生物学重要性，但通过实验技术解析这些蛋白质的结构已被证明非常困难，因此开发预测其结构的有效方法面临着巨大压力。我们讨论的方法涵盖从跨膜拓扑结构预测方法到基于知识的力场中低分辨率折叠模拟的新方法。这种势旨在重现脂质双层的特性。我们最终的目标是串联应用这些方法，以便能够为整个蛋白质组中的大部分跨膜蛋白结构域构建有用的三维模型。
