SecretEPDB is a Bacterial Secreted Effector Protein DataBase for T3/4/6 proteins.

Bacteria transport or translocate their effector molecules from bacterial cells to host cells through their highly evolved secretion systems. A number of secreted proteins are programmed to enter the host cell (including effectors, enzymes, and toxins), by virtue of secretion systems which include a nanomachine, chaperones and regulatory factors. A growing number of bacterial secretion systems have been classified, from type I to type IX so far. Each secretion system is programmed to secrete one or more (sometimes around a hundred) specifically selected effector proteins to manipulate the cell biology of their hosts. Accordingly, sequence, structural and functional annotations of these proteins are essential to understanding how bacterial secretion systems work. We are developing a new bioinformatics knowledgebase, termed SecretEPDB (Bacterial Secreted Effector Protein DataBase), for comprehensive annotations of effector proteins of bacterial type III secretion system (T3SS), type IV secretion system (T4SS) and type VI secretion system (T6SS).

SecretEPDB provides enriched and comprehensive annotations of the three classes of effector proteins by manually extracting and integrating structural and functional annotations from a variety of currently available databases and literature. All the retrieved effector protein entries included have been experimentally verified to be secreted by T3SS, T4SS, or T6SS. The annotations of SecretEPDB are provided in terms of protein characteristics, protein function annotation, protein 3D structure, presence of Pfam domains, metabolic pathway, and protein evolution information.

The data entries stored in SecretEPDB reside in a MySQL database. Website development techniques (including Structs2, Hibernate, Jquery and Bootstrap) were applied to construct SecretEPDB with user-friendly interfaces, enhanced data visualization and database functionalities.

A variety of search options with different keywords are provided in SecretEPDB including ID number and other different keywords such as protein name, post-translational modification type, disease caused by mutation and species. In addition, SecretEPDB allows researcher to submit their novel study results and discoveries and accordingly will release new entries after a careful review and curation. We anticipate that the proposed SecretEPDB will be useful for novel biological hypothesis of secretion effector research and will benefit a better understanding to secreted proteins and secretion systems.