The importance of PPIs as targets for drugs, especially small molecule drugs, has increased greatly in recent years [1–4]. Over 30 PPIs have been widely studied as targets for PPI-inhibiting small ligands. Currently, a huge amount of PPI data has been rapidly accumulated in public databases and in the literature. In addition, advances in high-throughput experimental technologies have lead to a large amount of various types of omics data, which have been deposited in many databases. These PPI data and omics data require methodologies for their application to pharmacological and medicinal studies. There is an urgent need to identify novel PPIs as drug targets from the PPI data accumulated, since only about 30 druggable PPIs have been well studied to date, whereas approximately 60,000 PPIs have been identified in human. We have recently proposed integrative approaches for discovering drug target PPIs by assessing the druggability of PPIs by the use of various types of omics data [5, 6]. The application of our methods to human PPIs predicted many potentially druggable PPIs.
Several databases and web-based tools specializing in drug targets have been published. For example, TTD [7, 8], a database of known therapeutic target proteins, stores information relevant to the targets, such as tertiary structures, disease associations, pathways, and pertinent literature. PDTD , a database for in silico drug target identification, stores diverse information on drug target proteins identified by the web-based tool Target Fishing Docking. SuperPred , a web-server for drug classification, uses a similarity score between drugs/chemicals to predict drug target proteins. These drug target databases and web-servers are very useful for researchers in in silico pharmacology and medicine. All of them, however, deal only with single proteins, rather than PPIs.
Recently, two databases (2P2IDB  and TIMBAL ) specializing in drug target PPIs and PPI-inhibiting chemicals have been published. 2P2IDB mainly focuses on protein/protein and protein/inhibitor interfaces in terms of various physicochemical parameters such as atom and residue properties, pocket volume, and accessible surface area . TIMBAL is a database of small molecules that inhibit protein/protein complexes, and it stores many properties of the molecules such as molecular weight, LogP value, number of rings, number of rotatable bonds, and binding affinity . 2P2IDB and TIMBAL can provide useful information to researchers developing PPI inhibitors. Both databases, however, contain only known drug target PPIs, so only a very small number of PPIs and PPI-inhibiting chemicals are stored. As a next step, in order to efficiently utilize the databases such as 2P2IDB and TIMBAL, it is needed to apply the information obtained from known drug target PPIs and their inhibitors to other PPIs not presently targeted by inhibitors.
Here we describe a novel database system, Dr. PIAS, which focuses on the druggability of PPIs. Dr. PIAS assesses the druggability of PPIs, currently not targeted by inhibitors, by utilizing the information obtained from known drug target PPIs. Dr. PIAS holds not only known drug target PPIs but also all PPIs identified to date for human, mouse, rat, and HIV proteins. In addition to information on the properties of the tertiary structures of PPI interfaces and that on the properties of drugs/chemicals related to interacting proteins, which are dealt with in 2P2IDB and TIMBAL, other properties associated with the biological function of PPIs are also included in the assessment. This is important because, to select a drug target PPI, a researcher considers not only information on the tertiary structure of the PPI and its known inhibitors but also that on the biological function of the PPI. All information on the PPIs used in the assessment is stored in Dr. PIAS. Users can search for druggable PPIs in Dr. PIAS by using various words and terms such as protein/gene name, tertiary structure, disease, pathway, and drug/chemical name as keywords.