Prediction of site-specific interactions in antibody-antigen complexes: the proABC method and server
Prediction of site-specific interactions in antibody-antigen complexes: the proABC method and server
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DOI：
10.1093/bioinformatics/btt369
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发表时间：
2013-09-15
期刊：
影响因子：
5.8
通讯作者：
Marcatili, Paolo
中科院分区：
文献类型：
--
作者：
Olimpieri, Pier Paolo;Chailyan, Anna;Marcatili, Paolo
动机：抗体或免疫球蛋白是免疫系统中最重要的蛋白质。它们作为诊断、生物技术和治疗工具具有极其重要的意义。它们的模块化结构使得为特定目的重新设计它们变得很容易。这些实验和其他实验一样，不需要经历试错过程，而需要依赖于对抗体结合模式的特定决定因素的了解。结果：在本文中，我们提出了一种仅基于抗体序列来识别抗体残基与其同源抗原直接相互作用的方法。该方法基于随机森林自动学习技术，召回率和特异度高达80%，并作为一个免费且易于使用的服务器实现，称为抗体接触预测。我们相信，它可以对重新设计实验有很大的帮助，对分子对接实验也有指导作用。我们获得的结果也使我们能够剖析抗体序列的哪些特征对特定残基与抗原结合的影响最大。
Motivation: Antibodies or immunoglobulins are proteins of paramount importance in the immune system. They are extremely relevant as diagnostic, biotechnological and therapeutic tools. Their modular structure makes it easy to re-engineer them for specific purposes. Short of undergoing a trial and error process, these experiments, as well as others, need to rely on an understanding of the specific determinants of the antibody binding mode.Results: In this article, we present a method to identify, on the basis of the antibody sequence alone, which residues of an antibody directly interact with its cognate antigen. The method, based on the random forest automatic learning techniques, reaches a recall and specificity as high as 80% and is implemented as a free and easy-to-use server, named prediction of Antibody Contacts. We believe that it can be of great help in re-design experiments as well as a guide for molecular docking experiments. The results that we obtained also allowed us to dissect which features of the antibody sequence contribute most to the involvement of specific residues in binding to the antigen.