Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 611731, China.
School of Medicine, Guizhou University, Guiyang 550025, China.
Curr Med Chem. 2019;26(42):7672-7693. doi: 10.2174/0929867325666180629123117.
Phage display is a powerful and versatile technology for the identification of peptide ligands binding to multiple targets, which has been successfully employed in various fields, such as diagnostics and therapeutics, drug-delivery and material science. The integration of next generation sequencing technology with phage display makes this methodology more productive. With the widespread use of this technique and the fast accumulation of phage display data, databases for these data and computational methods have become an indispensable part in this community. This review aims to summarize and discuss recent progress in the development and application of computational methods in the field of phage display.
We undertook a comprehensive search of bioinformatics resources and computational methods for phage display data via Google Scholar and PubMed. The methods and tools were further divided into different categories according to their uses.
We described seven special or relevant databases for phage display data, which provided an evidence-based source for phage display researchers to clean their biopanning results. These databases can identify and report possible target-unrelated peptides (TUPs), thereby excluding false-positive data from peptides obtained from phage display screening experiments. More than 20 computational methods for analyzing biopanning data were also reviewed. These methods were classified into computational methods for reporting TUPs, for predicting epitopes and for analyzing next generation phage display data.
The current bioinformatics archives, methods and tools reviewed here have benefitted the biopanning community. To develop better or new computational tools, some promising directions are also discussed.
噬菌体展示技术是一种强大而通用的技术，可用于鉴定与多种靶标结合的肽配体，已成功应用于诊断和治疗、药物输送和材料科学等多个领域。下一代测序技术与噬菌体展示技术的结合使这种方法更具生产力。随着该技术的广泛应用和噬菌体展示数据的快速积累，这些数据的数据库和计算方法已成为该领域不可或缺的一部分。本文旨在总结和讨论噬菌体展示领域中计算方法的最新进展和应用。
我们通过 Google Scholar 和 PubMed 对噬菌体展示数据的生物信息学资源和计算方法进行了全面搜索。根据用途，将方法和工具进一步分为不同类别。
我们描述了七个特殊或相关的噬菌体展示数据库，为噬菌体展示研究人员提供了一个基于证据的来源，用于清理生物淘选结果。这些数据库可以识别和报告可能与靶标无关的肽（TUPs），从而从噬菌体展示筛选实验中获得的肽中排除假阳性数据。还对 20 多种用于分析生物淘选数据的计算方法进行了综述。这些方法分为用于报告 TUPs 的计算方法、用于预测表位的计算方法和用于分析下一代噬菌体展示数据的计算方法。
本文回顾的当前生物信息学档案、方法和工具使生物淘选社区受益。为了开发更好或新的计算工具，还讨论了一些有前途的方向。
