Fuchs Julian E, Wellenzohn Bernd, Weskamp Nils, Liedl Klaus R
Theoretical Chemistry, Faculty of Chemistry and Pharmacy, University of Innsbruck , Innrain 82, 6020 Innsbruck, Austria.
Research Germany/Lead Identification and Optimization Support, Boehringer Ingelheim Pharma GmbH & Co. KG , Birkendorfer Straße 65, 88397 Biberach an der Riss, Germany.
J Chem Inf Model. 2015 Nov 23;55(11):2315-23. doi: 10.1021/acs.jcim.5b00476. Epub 2015 Nov 6.
Biopharmaceuticals hold great promise for the future of drug discovery. Nevertheless, rational drug design strategies are mainly focused on the discovery of small synthetic molecules. Herein we present matched peptides, an innovative analysis technique for biological data related to peptide and protein sequences. It represents an extension of matched molecular pair analysis toward macromolecular sequence data and allows quantitative predictions of the effect of single amino acid substitutions on the basis of statistical data on known transformations. We demonstrate the application of matched peptides to a data set of major histocompatibility complex class II peptide ligands and discuss the trends captured with respect to classical quantitative structure-activity relationship approaches as well as structural aspects of the investigated protein-peptide interface. We expect our novel readily interpretable tool at the interface of cheminformatics and bioinformatics to support the rational design of biopharmaceuticals and give directions for further development of the presented methodology.
生物制药对药物研发的未来有着巨大的前景。然而，合理的药物设计策略主要集中在发现小型合成分子上。在此，我们介绍匹配肽，这是一种用于与肽和蛋白质序列相关的生物数据的创新分析技术。它代表了匹配分子对分析向大分子序列数据的扩展，并允许基于已知转化的统计数据对单个氨基酸取代的影响进行定量预测。我们展示了匹配肽在主要组织相容性复合体II类肽配体数据集上的应用，并讨论了相对于经典定量构效关系方法所捕捉到的趋势以及所研究的蛋白质 - 肽界面的结构方面。我们期望我们在化学信息学和生物信息学界面的新型易于解释的工具能够支持生物制药的合理设计，并为所提出方法的进一步发展指明方向。
