A network-based computational and experimental framework for repurposing compounds toward the treatment of non-alcoholic fatty liver disease
Danae Stella Zareifi,
Odysseas Chaliotis,
Nafsika Chala,
Nikos Meimetis,
Maria Sofotasiou,
Konstantinos Zeakis,
Eirini Pantiora,
Antonis Vezakis,
George K. Matsopoulos,
Georgios Fragulidis,
Leonidas G. Alexopoulos
Affiliations
Danae Stella Zareifi
School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechneiou 9, Zografou, 15780 Athens, Greece
Odysseas Chaliotis
School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechneiou 9, Zografou, 15780 Athens, Greece
Nafsika Chala
School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechneiou 9, Zografou, 15780 Athens, Greece
Nikos Meimetis
School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechneiou 9, Zografou, 15780 Athens, Greece
Maria Sofotasiou
School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechneiou 9, Zografou, 15780 Athens, Greece
Konstantinos Zeakis
School of Electrical Engineering, National Technical University of Athens, 15780 Athens, Greece
Eirini Pantiora
2nd Department of Surgery, Aretaieio Hospital, University of Athens, School of Medicine, 11528, Athens, Greece
Antonis Vezakis
2nd Department of Surgery, Aretaieio Hospital, University of Athens, School of Medicine, 11528, Athens, Greece
George K. Matsopoulos
School of Electrical Engineering, National Technical University of Athens, 15780 Athens, Greece
Georgios Fragulidis
2nd Department of Surgery, Aretaieio Hospital, University of Athens, School of Medicine, 11528, Athens, Greece
Leonidas G. Alexopoulos
School of Mechanical Engineering, National Technical University of Athens, Iroon Polytechneiou 9, Zografou, 15780 Athens, Greece; ProtATonce Ltd, Patriarchou Grigoriou & Neapoleos Demokritos Science Park, Building#27, Agia Paraskevi GR15343, Greece; Corresponding author
Summary: Non-alcoholic fatty liver disease (NAFLD) is among the most common liver pathologies, however, none approved condition-specific therapy yet exists. The present study introduces a drug repositioning (DR) approach that combines in vitro steatosis models with a network-based computational platform, constructed upon genomic data from diseased liver biopsies and compound-treated cell lines, to propose effectively repositioned therapeutic compounds. The introduced in silico approach screened 20′000 compounds, while complementary in vitro and proteomic assays were developed to test the efficacy of the 46 in silico predictions. This approach successfully identified six compounds, including the known anti-steatogenic drugs resveratrol and sirolimus. In short, gallamine triethiotide, diflorasone, fenoterol, and pralidoxime ameliorate steatosis similarly to resveratrol/sirolimus. The implementation holds great potential in reducing screening time in the early drug discovery stages and in delivering promising compounds for in vivo testing.
