Pharmadoop: a tool for pharmacophore searching using Hadoop framework

The term pharmacophore is used to define the important features of one or more molecules having the same biological activity. Pharmacophores are selected based on several common features, such as the type of functional groups present, the distance between each atom or group of atoms and the angle between such groups or an individual atom. In this paper, we present the design and implementation of a pharmacophore searching tool, Pharmadoop, using the Hadoop framework. Due to its Hadoop implementation, Pharmadoop is a faster approach as compared to the existing standalone pharmacophore search tools. It utilizes the MapReduce algorithm to support the comparison of millions of conformers in a short time span. We further demonstrated and compared the utility of Pharmadoop on ten distinct chemical datasets of ligand molecules by running common substructure searching job on standalone and multi-system Hadoop platforms. These results were further used to perform pharmacophore searching applications on standalone and multi-node Hadoop distributions. The performance, speed and accuracy of the tool were evaluated through time-scale analysis and receiver operating curve. The Pharmadoop tool can be accessed at http://bioserver.iiita.ac.in/Pharmadoop/ .