Designing and implementing chemoinformatic approaches in TDR Targets Database: linking genes to chemical compounds in tropical disease causing pathogens

Information about chemical compounds and their activity against whole organisms or specific molecular targets is available from the literature or from specialized databases. However, there are few resources that effectively integrate such large chemical datasets with genome data and provide a mechanism to link active compounds to potential target genes. Here, we showcase the integration of chemoinformatic tools for querying chemical datasets and linking chemicals to genes in TDR Targets database (tdrtargets.org), a web accessible resource that integrates a wide range of functional genomic datasets from tropical disease pathogens and provides a ranking mechanism for identifying and prioritising novel therapeutic targets [1].

Chemical datasets were obtained from three different resources: DrugBank, PubChem and StARlite (ChEMBL). A pipeline was developed to calculate a number of properties (molecular weight; number of flexible bonds; polar surface area; H bond donors/acceptors; and predicted octanol/water partition coefficient) and descriptors (InChi, IUPAC's standard and open chemical identifiers; SMILES; and molecular formula) for each molecule, to facilitate querying and linking to other databases. We have also calculated a number of binary fingerprints and molecular statistics to accelerate searches.

A comprehensive collection of chemical data can be queried in various ways, including by chemical properties, structure and descriptors in TDRTargets.org. More importantly, one can also link compounds of interest to novel target genes in tropical disease causing parasitic organisms based on sequence similarity to known targets of these compounds.