PDTD: a web-accessible protein database for drug target identification

Abstract

BackgroundTarget identification is important for modern drug discovery. With the advances in the development of molecular docking, potential binding proteins may be discovered by docking a small molecule to a repository of proteins with three-dimensional (3D) structures. To complete this task, a reverse docking program and a drug target database with 3D structures are necessary. To this end, we have developed a web server tool, TarFisDock (Target Fishing Docking) , which has been used widely by others. Recently, we have constructed a protein target database, Potential Drug Target Database (PDTD), and have integrated PDTD with TarFisDock. This combination aims to assist target identification and validation.DescriptionPDTD is a web-accessible protein database for in silico target identification. It currently contains >1100 protein entries with 3D structures presented in the Protein Data Bank. The data are extracted from the literatures and several online databases such as TTD, DrugBank and Thomson Pharma. The database covers diverse information of >830 known or potential drug targets, including protein and active sites structures in both PDB and mol2 formats, related diseases, biological functions as well as associated regulating (signaling) pathways. Each target is categorized by both nosology and biochemical function. PDTD supports keyword search function, such as PDB ID, target name, and disease name. Data set generated by PDTD can be viewed with the plug-in of molecular visualization tools and also can be downloaded freely. Remarkably, PDTD is specially designed for target identification. In conjunction with TarFisDock, PDTD can be used to identify binding proteins for small molecules. The results can be downloaded in the form of mol2 file with the binding pose of the probe compound and a list of potential binding targets according to their ranking scores.ConclusionPDTD serves as a comprehensive and unique repository of drug targets. Integrated with TarFisDock, PDTD is a useful resource to identify binding proteins for active compounds or existing drugs. Its potential applications include in silico drug target identification, virtual screening, and the discovery of the secondary effects of an old drug (i.e. new pharmacological usage) or an existing target (i.e. new pharmacological or toxic relevance), thus it may be a valuable platform for the pharmaceutical researchers. PDTD is available online at .

Identification of Putative Therapeutic Targets in Candida tropicalis: An in silico Approach

“…This enabled us to predict the function of the proteins and genome annotation that resulted in the identification of potential targets. Screening of the potential drug targets was carried out by similarity search using protein sequence of all the potential targets against the Drug Bank ( Knox et al, 2011), TTD (Chen et al, 2002), PDTD (Gao et al, 2008) and HIT (Ye et al, 2011) to reach the novel drug targets. Further the outer membrane proteins were predicted using Trans-Membrane prediction using Hidden Markov Models (TMHMM), that identify surface membrane proteins which could be used as potential drug targets and vaccine candidates (Krogh et al, 2001).…”

Synthesis and in silico evaluation of 1N-methyl-1S-methyl-2-nitroethylene (NMSM) derivatives against Alzheimer disease: to understand their interacting mechanism with acetylcholinesterase

“…Initially, the library of NMSM derivatives was screened based on their absorption, distribution, metabolism, excretion, and toxicity (ADMET) and Lipinski's rule of five, which resulted in 12 compounds as the best hits. All the 12 compounds were subjected into TarFisDock [41,42] server to find out their protein target. A result of such analysis for the given compounds suggested that they might have an ability to interact with hAChE.…”

The successes and challenges of open-source biopharmaceutical innovation

“…Open-source databases such as DrugBank, the Potential Drug Target Database, Therapeutic Target Database and SuperTarget provide target and drug profiles [2][3][4][5]. These databases feature drug targets, including protein and active site structures, association with related diseases, biological functions and associated signaling pathways [3].…”