SiteLight: Binding-site prediction using phage display libraries
SiteLight: Binding-site prediction using phage display libraries
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DOI：
10.1110/ps.0237103
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发表时间：
2003-07-01
期刊：
影响因子：
8
通讯作者：
Nussinov, R
中科院分区：
文献类型：
--
作者：
Halperin, I;Wolfson, H;Nussinov, R
噬菌体展示使大量的多肽呈现在噬菌体颗粒的表面。这样的文库可以通过亲和力选择来测试与感兴趣的目标分子的结合。在这里，我们介绍了SiteLight，一个使用噬菌体展示文库进行结合位点预测的新型计算工具。SiteLight是一种将一维肽库映射到三维(3D)蛋白质表面的算法。它适用于由蛋白质模板和任何类型的称为靶的分子组成的络合物。给定模板的三维结构和通过对照靶标进行生物扫描得到的序列集合，预测模板与靶标的相互作用部位。我们已经创建了一个庞大而多样的数据集，用于评估SiteLight正确预测结合位点的能力。SiteLight预测映射能够区分表面的结合部分和非结合部分。这一预测可以在不排除结合部位的情况下有效地减少75%的表面。在我们测试的63%的情况下，至少有一个结合位点预测与界面重叠至少50%。这些结果表明，噬菌体展示文库可用于三维结构上的自动结合位点预测。为了更有效地预测结合位点，我们建议使用两次随机噬菌体展示库来扫描给定复合体的两个结合伙伴。将衍生的多肽映射到另一个结合伙伴(现在用作模板)。在这里，每个伙伴的表面减少了75%，显著地集中了他们彼此之间的相对位置。这些信息可用于改进对接算法和评分函数。
Phage display enables the presentation of a large number of peptides on the surface of phage particles. Such libraries can be tested for binding to target molecules of interest by means of affinity selection. Here we present SiteLight, a novel computational tool for binding site prediction using phage display libraries. SiteLight is an algorithm that maps the 1D peptide library onto a three-dimensional (3D) protein surface. It is applicable to complexes made up of a protein Template and any type of molecule termed Target. Given the three-dimensional structure of a Template and a collection of sequences derived from biopanning against the Target, the Template interaction site with the Target is predicted. We have created a large diverse data set for assessing the ability of SiteLight to correctly predict,binding sites. SiteLight predictive mapping enables discrimination between the binding and nonbinding parts of the surface. This prediction can be used to effectively reduce the surface by 75% without excluding the binding site. In 63% of the cases we have tested, there is at least one binding site prediction that overlaps the interface by at least 50%. These results suggest the applicability of phage display libraries for automated binding site prediction on three-dimensional structures. For most effective binding site prediction we propose using a random phage display library twice, to scan both binding partners of a given complex. The derived peptides are mapped to the other binding partner (now used as a Template). Here, the surface of each partner is reduced by 75%, focusing their relative positions with respect to each other significantly. Such information can be utilized to improve docking algorithms and scoring functions.