Diego Carrella1, Francesco Napolitano1, Rossella Rispoli1, Mario Miglietta1, Annamaria Carissimo1, Luisa Cutillo2, Francesco Sirci1, Francesco Gregoretti1, Diego Di Bernardo2. 1. Telethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli 'Parthenope', Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples 'Federico II', Via Claudio 21, 80125 Naples, Italy. 2. Telethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli 'Parthenope', Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples 'Federico II', Via Claudio 21, 80125 Naples, ItalyTelethon Institute of Genetics and Medicine, Via P. Castellino 111, 80131 Naples, Interactive SRL, Via Fratelli Bisogno 5, 83100 Avellino, Dip. di Studi Aziendali e Quantitativi Università degli studi di Napoli 'Parthenope', Via Generale Parisi 13, 80132 Naples, Institute for High-Performance Computing - ICAR - CNR, Via P. Castellino 111, 80131 Naples and Department of Electrical Engineering and Information Technology, University of Naples 'Federico II', Via Claudio 21, 80125 Naples, Italy.
Abstract
SUMMARY: Elucidation of molecular targets of a compound [mode of action (MoA)] and its off-targets is a crucial step in drug development. We developed an online collaborative resource (MANTRA 2.0) that supports this process by exploiting similarities between drug-induced transcriptional profiles. Drugs are organized in a network of nodes (drugs) and edges (similarities) highlighting 'communities' of drugs sharing a similar MoA. A user can upload gene expression profiles before and after drug treatment in one or multiple cell types. An automated processing pipeline transforms the gene expression profiles into a unique drug 'node' embedded in the drug-network. Visual inspection of the neighbouring drugs and communities helps in revealing its MoA and to suggest new applications of known drugs (drug repurposing). MANTRA 2.0 allows storing and sharing user-generated network nodes, thus making MANTRA 2.0 a collaborative ever-growing resource. AVAILABILITY AND IMPLEMENTATION: The web tool is freely available for academic use at http://mantra.tigem.it.
SUMMARY: Elucidation of molecular targets of a compound [mode of action (MoA)] and its off-targets is a crucial step in drug development. We developed an online collaborative resource (MANTRA 2.0) that supports this process by exploiting similarities between drug-induced transcriptional profiles. Drugs are organized in a network of nodes (drugs) and edges (similarities) highlighting 'communities' of drugs sharing a similar MoA. A user can upload gene expression profiles before and after drug treatment in one or multiple cell types. An automated processing pipeline transforms the gene expression profiles into a unique drug 'node' embedded in the drug-network. Visual inspection of the neighbouring drugs and communities helps in revealing its MoA and to suggest new applications of known drugs (drug repurposing). MANTRA 2.0 allows storing and sharing user-generated network nodes, thus making MANTRA 2.0 a collaborative ever-growing resource. AVAILABILITY AND IMPLEMENTATION: The web tool is freely available for academic use at http://mantra.tigem.it.
Authors: Jiansong Fang; Andrew A Pieper; Ruth Nussinov; Garam Lee; Lynn Bekris; James B Leverenz; Jeffrey Cummings; Feixiong Cheng Journal: Med Res Rev Date: 2020-07-13 Impact factor: 12.944