Molecular Immunology Group, Department of Pathology and Infectious Diseases, Royal Veterinary College, Hawkshead Campus, Hawkshead Lane, North Mymms, Hertfordshire AL97TA, United Kingdom.
Dev Comp Immunol. 2010 Oct;34(10):1035-41. doi: 10.1016/j.dci.2010.05.004. Epub 2010 May 21.
Homology modelling is considered the most accurate technique for computational prediction of protein structure. However, this technique comes with fundamental caveats of dependency on template quality, identification of structural features and accuracy of alignment. Leucine-rich repeats (LRRs) characterise a diverse family of proteins. Recently resolved structures reveal a highly conserved region in LRRs that assemble into the curved parallel beta-sheet lining the inner circumference of their solenoid structure. Thus, prediction of these structurally important regions is essential in the comparative modelling of LRR proteins and their interactions. Here, we describe the generation of tLRRdb, a database of selected Toll-like receptor (TLR) sequences with annotated co-ordinates. Derived from this is LRRfinder, a web application for the identification of LRRs within user-defined sequences to facilitate identification of structurally important regions, particularly relevant for protein-protein interaction studies and classification of novel sequences. LRRfinder is available at: www.lrrfinder.com.
同源建模被认为是计算蛋白质结构预测最准确的技术。然而，该技术存在一些基本的局限性，例如依赖于模板质量、结构特征的识别和对齐的准确性。富含亮氨酸重复（LRR）是一类多样化的蛋白质家族。最近解析的结构揭示了 LRR 中一个高度保守的区域，该区域组装成其螺旋结构内圆周的弯曲平行β-折叠。因此，对这些结构重要区域的预测对于 LRR 蛋白及其相互作用的比较建模至关重要。在这里，我们描述了 tLRRdb 的生成，这是一个带有注释坐标的选定 Toll 样受体（TLR）序列的数据库。由此产生的是 LRRfinder，这是一个用于在用户定义的序列中识别 LRR 的网络应用程序，以方便识别结构重要区域，这对于蛋白质-蛋白质相互作用研究和新型序列的分类特别相关。LRRfinder 可在：www.lrrfinder.com 获得。
