OlfactionDB: A Database of Olfactory Receptors and Their Ligands

Odorants are volatile molecules that efficiently carry chemical information, providing one of the main ways for communicating with the environment in all kingdoms of life. In the other hand, mammalian genomes codify for hundreds of olfactory receptors (ORs), e.g. about 400 in human and more than 1000 in mouse, underlying the crucial role of the sense of smell during evolution. Therefore, the olfactory system is capable to discriminate between ~10,000 different odors. The possibility of collecting and compiling information about odorants and their receptors is thus fundamental for a functional characterization of the signaling firing event. OlfactionDB, a manually curated database providing comprehensive information for nearly 400 odorant-receptor interactions at the current state, has been developed for managing information about odorants and their receptors. OlfactionDB is a free publicly database available online from: http://molsim.sci.univr.it/OlfactionDB.


Introduction
The G protein-coupled receptors (GPCRs) family is the largest membrane-bound receptor family expressed by mammalians (encompassing more than 1% of the genome). They are involved in an enormous variety of intra-and extracellular signaling pathways, including detection of light, odors and taste; neurotransmission; inflammation; cardiac and smooth muscle contractility [1]. Ligand (or photon) binding to GPCRs fires a cascade of events, producing an electrical signal as output. More than half of the GPCRs codified in mammalian genomes are olfactory receptors (ORs) [2,3], underlying the crucial role of the sense of smell during evolution. With such an impressive number of different ORs, the olfactory system is capable to discriminate between ~10,000 different odors: one odorant can activate numerous types of ORs, while a single OR can be activated by several different odorants. Thus, it is important to rationally collecting and compiling information about interaction affinities of odorants and their receptors. In the last few years, several human/mouse OR-odorants interaction affinities have been published [4][5][6][7][8][9][10][11][12][13]. Here we present a free, publicly available, database, OlfactionDB, that contains affinity data of human/mouse olfactory receptors (OR) and ligands, manually compiled and extracted from the lite-

Methods
The whole families of mouse and human ORs were retrieved from the Uniprot database [14]. The ORs for which experimental data exist [4][5][6][7][8][9][10][11][12][13] were then aligned using the program PROMALS [15] and manually checked in order to eliminate redundancies. We used in-home-written Python scripts to manipulate the data, whereas annotations regarding the interaction between G-proteins and ligands, the affinity of a particular interaction and the corresponding references were appended manually in a spreadsheet. The data has been organized on the basis of a relational model (Figure. 1) and stored in a PostgreSQL database system. The user has supervisory access through our Apache web server interferential software, which was developed in Java for database manipulation. This software tends to settle any web server's query.
The OR's sequence similarity searches can be carried out in the database using a server-side version of the program Ssearch [16] and the ligand similarity searches can be performed by using a server-side version of OpenBabel (http://openbabel.sf.net).
The three dimensional structures of the odorant molecules can be visualized with Jmol [17] and the multiple sequence alignment of the ORs included in the database can be analyzed by a Jalview [18] applet. A tree as the one showed in Figure.

Results
The current sive informati totalizing info All the data w lished in the data was inde and co-worker One of the preparation of nomenclatures on the referen tabase naviga through its ma navigation, b) tures from at c) Uniprot ac searches can b OpenBabel, fo ample of a sim ure. 3.  help in the modelling of the binding cavities, which is the place into which inhibitors and or other kind of molecules may interact. Our group and collaborators have been involved, during the last decade, in the application of a combination of computational and experimental techniques aimed at the unravelling of the molecular mechanisms underlying the different steps of several signalling cascades, i.e. vision, olfaction and bitter taste, all of them including GPCRs as the initial part of the signalling firing event [22][23][24][25][26][27][28]. In fact, we have to consider that the main challenges for the near future will include the development and application of methods that permit the full description at the molecular/structural level of GPCR-ligand complexes, as they constitute one of the principal drug targets in the human organism. In this sense the availability of a freely-publicly database, accessible to the whole scientific community, able to offer details regarding ligand-receptor affinities may be of fundamental importance for the development of the field.