According to the Medical Subject Heading (MeSH), hormones are defined as chemical substances having a specific regulatory effect on the activity of a certain organ or organs, although the classical definition of hormones limits them to the domain of chemical signaling molecules produced by endocrine glands and secreted directly into the bloodstream. Hormones travel through the blood to distant tissues and organs, where they can bind to specific cell sites called receptors. By binding to receptors, hormones trigger various responses in the tissues/cells containing cognate receptors 12. On the basis of their chemical natures, hormones are broadly classified into protein/peptide hormones (genome-encoded) and non-peptide hormones (non-genome-encoded). Hormone-receptor interactions are amongst the most important ligand-receptor type of interactions in biological systems. The living multicellular entity depends on complex communication networks for its survival. Hormones, acting as chemical messengers, are the postmen of endocrine machinery. The endocrine system focuses on ligand-receptor interactions to play a critical role in growth and development of multicellular eukaryotes 34. The data flow in this area of biological science is rapid and vast. Therefore, collection and compilation of information about these interactions, and underlying molecules (hormones and receptors), will be useful.

In recent years, efforts have been made to collect and organize receptors (like GPCRDB, ORDB, NuReBase and GRIS) 5678. These databases deal with different classes of receptors in biological system; for example, GPCRDB/GRIS/ORDB for G-protein coupled receptors (GPCRs) and NuReBase for nuclear hormone receptors. Various type of databases; for example SwePep 9 for endogenous peptides and PepBank 10 for peptides collected from literature using text mining tools, came into existence recently. There are a few databases which maintain information about ligands and their receptors like PRRDB 11, GLIDA 12, and EndoNet 13. PRRDB, an immunological database, provides information regarding Pattern Recognition Receptors and their ligands. GLIDA is developed with possible implications in chemical genomic research and GPCR-related drug discovery, whereas EndoNet is an information resource about intercellular regulatory communication. Though existing databases provide important information, there is lack of a comprehensive resource on hormones and their receptors.

In order to complement existing databases in the field, and to understand hormones and their interaction with receptors, we have developed a database called Hmrbase. This database provides comprehensive information about hormones and receptors. Various data fields like hormone precursor, subcellular localization, post-translational modification, taxonomy, source organism, function, description, tissue specificity, molecular weight, similarity to other proteins, and mapping of hormone peptide on its corresponding precursor etc. have been included for peptide hormones and their receptor. For non-peptide hormones, the data fields consist of their names, molecular weights and molecular formulae, IUPAC names, canonical and isomeric smile formulae, melting points, LogP values, water solubility, and their corresponding receptors etc. Various co-ordinate files such as PDB, SDF, and MOL files are available for download. Structure visualization tools such as Advance Chemistry Development (ACD) structure drawing applet 14 (for 2-D visualization) and Jmol applet 15 (for 3-D visualization) have been embedded in Hmrbase. Links to neighbors (external links) like Swiss-Prot 16, PDB 17, NCBI Gene Database 18, Pfam 19, PubChem 20, KEGG 21, HMDB 22, DrugBank 23, and DrugPedia 24 have been incorporated in Hmrbase to make it a complete system. Moreover, hormones and receptors entries are linked to their corresponding receptors and hormones, respectively. Sequence similarity search, peptide mapping and domain search tool, in case of protein hormone and receptor, facilitates the extraction of useful information. In addition to text search, a structural similarity-based search option for non-peptide hormones supports the search algorithm. Thus, Hmrbase provides both comprehensive and easy-to-use information related to hormones and their receptors.

For collection of peptide hormones, we have extensively searched Swiss-Prot, other databases and the related literature. Initially, we started searching through Sequence Retrieval System (SRS) of Swiss-Prot with a keyword "hormone" against the "Description" field with wild card. Then we exploited GPCRDB for hormone receptor. GPCR class A comprises hormone receptors such as serotonin, cholecystokinin, melanocortin, prolactin, somatostatin, vasopressin, adrenomedullin, melanin etc. GPCR class B comprises calcitonin, glucagons, diurectic, parathyroid, secretin hormone receptors. Regarding collection of non-peptide hormones we searched various databases like PubChem, Human Metabolome Database (HMDB), and EndoNet. The corresponding receptors were taken from PubChem, literature databases like PubMed, EndoNet, DrugBank, NucleaRDB 25, and Swiss-Prot. Detailed information about data collection and manual curation has been included in the additional file 1.

This database consists of extensively manually curated information about peptide hormones, non-peptide hormones, and their receptors. The statistics of the data has been given in Table 1 and Table 2. Following is the brief description of data available at Hmrbase.

Hmrbase is a comprehensive information resource about hormones and their receptors. Ligand-receptor interactions have been elucidated in a bi-directional manner. Users can start from searching hormone entry (ies) and end up in their corresponding receptor (s); and vice-versa. The database will fulfill the requirements of theoretical as well as clinical endocrinologists. Data structure of Hmrbase is quite simple and convenient for general users. The mature hormone sequence is mapped on its precursor protein sequence in order to define the functional modes of hormones. Furthermore, this information can be exploited by experimental scientists to design better ligands for a particular receptor or for studying binding affinity of hormones to their corresponding receptors. Protein domains have been inferred as the basic building blocks of protein interactions 29. Therefore, to derive the Pfam domains distribution among the entries of Hmrbase, a domain search facility has been embedded.

Furthermore, a collection of non-peptide hormone molecules along with various operational tools such as ACD/Structure drawing applet, Jmol, and JC Search with JME editor facilitates the completeness of the database.

Hopefully this customized database will expand quantitatively as well as qualitatively in coming days to cover the annotation gaps such as orphan receptors and probably any novel hormone molecule.

Hmrbase presents data in a sophisticated way. Apart from text search, several browsing options facilitate the retrieval of important datasets, such as entries for a particular organism or hormone name or specific domain or domain combinations etc. Moreover, hormone-receptor and receptor-hormone pairs have been presented to infer the range of action of a particular hormone or receptor. Different types of structure search algorithm such as substructure, exact, superstructure search would help in compiling the set of entries containing a particular functional group or moiety. Moreover, each entry of Hmrbase has been linked to DrugPedia, which would serve as a complement to Hmrbase entries. Any new or updated information posted on DrugPedia would be included in Hmrbase database after validation. Thus Hmrbase would be a comprehensive and stable system for biomedical researchers and bioinformatician.

Several new data types such as pharmacological data are being collected to incorporate into Hmrbase. The major limitation of this resource is the lack of a fully automated database populating system. Nevertheless, we have devised different models for updation of Hmrbase at a period of every three month (see Additional file 1).

Hmrbase is available at: http://crdd.osdd.net/raghava/hmrbase/. To access all features of Hmrbase database to its optimum level, javascript and Java Runtime Environment (JRE) plugin must be enabled.

MR collected and compiled the data from literature and public databases. MR made the structure of the database. DS collected non-peptide hormone molecules and their nuclear receptor counterparts. MK and MR incorporated various amino acid sequence manipulative tools in Hmrbase. Web interface was designed by AS and MR. AS contributed in converting Perl scripts into PHP and PgSQL tables into MySQL tables originally made by MR and MK. AS and DS incorporated tools for non-peptide hormone manipulation. GPSR conceived the project, coordinated it and refined the manuscript drafted by MR.