DGPD: a knowledge database of dense granule proteins of the Apicomplexa. (27th September 2022)

• Record Type: Journal Article
• Authors: Hu, Hang; Lu, Zhenxiao; Feng, Haisong; Chen, Guojun; Wang, Yongmei; Yang, Congshan; Yue, Zhenyu
• Is Part Of: Database. Volume 2022(2022)
• Publication Date: 2022-09-27
• Subjects: Biology -- Databases -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1093/database/baac085
• Languages: English
• ISSNs: 1758-0463

Abstract

Abstract: Apicomplexan parasites cause severe diseases in human and livestock. Dense granule proteins (GRAs), specific to the Apicomplexa, participate in the maintenance of intracellular parasitism of host cells. GRAs have better immunogenicity and they can be emerged as important players in vaccine development. Although studies on GRAs have increased gradually in recent years, due to incompleteness and complexity of data collection, biologists have difficulty in the comprehensive utilization of information. Thus, there is a desperate need of user-friendly resource to integrate with existing GRAs. In this paper, we developed the Dense Granule Protein Database (DGPD), the first knowledge database dedicated to the integration and analysis of typical GRAs properties. The current version of DGPD includes annotated GRAs metadata of 245 samples derived from multiple web repositories and literature mining, involving five species that cause common diseases ( Plasmodium falciparum, Toxoplasma gondii, Hammondia hammondi, Neospora caninum and Cystoisospora suis ). We explored the baseline characteristics of GRAs and found that the number of introns and transmembrane domains in GRAs are markedly different from those of non-GRAs. Furthermore, we utilized the data in DGPD to explore the prediction algorithms for GRAs. We hope DGPD will be a good database for researchers to study GRAs. Database URL : http://dgpd.tlds.cc/DGPD/index/