Author(s): Kleemann Robert | Bureeva Svetlana | Perlina Ally | Kaput Jim | Verschuren Lars | Wielinga Peter | Hurt-Camejo Eva | Nikolsky Yuri | van Ommen Ben | Kooistra Teake
Journal: BMC Systems Biology
ISSN 1752-0509
Volume: 5;
Issue: 1;
Start page: 125;
Date: 2011;
Original page
ABSTRACT
Abstract Background Successful drug development has been hampered by a limited understanding of how to translate laboratory-based biological discoveries into safe and effective medicines. We have developed a generic method for predicting the effects of drugs on biological processes. Information derived from the chemical structure and experimental omics data from short-term efficacy studies are combined to predict the possible protein targets and cellular pathways affected by drugs. Results Validation of the method with anti-atherosclerotic compounds (fenofibrate, rosuvastatin, LXR activator T0901317) demonstrated a great conformity between the computationally predicted effects and the wet-lab biochemical effects. Comparative genome-wide pathway mapping revealed that the biological drug effects were realized largely via different pathways and mechanisms. In line with the predictions, the drugs showed differential effects on inflammatory pathways (downstream of PDGF, VEGF, IFNγ, TGFβ, IL1β, TNFα, LPS), transcriptional regulators (NFκB, C/EBP, STAT3, AP-1) and enzymes (PKCδ, AKT, PLA2), and they quenched different aspects of the inflammatory signaling cascade. Fenofibrate, the compound predicted to be most efficacious in inhibiting early processes of atherosclerosis, had the strongest effect on early lesion development. Conclusion Our approach provides mechanistic rationales for the differential and common effects of drugs and may help to better understand the origins of drug actions and the design of combination therapies.
Journal: BMC Systems Biology
ISSN 1752-0509
Volume: 5;
Issue: 1;
Start page: 125;
Date: 2011;
Original page
ABSTRACT
Abstract Background Successful drug development has been hampered by a limited understanding of how to translate laboratory-based biological discoveries into safe and effective medicines. We have developed a generic method for predicting the effects of drugs on biological processes. Information derived from the chemical structure and experimental omics data from short-term efficacy studies are combined to predict the possible protein targets and cellular pathways affected by drugs. Results Validation of the method with anti-atherosclerotic compounds (fenofibrate, rosuvastatin, LXR activator T0901317) demonstrated a great conformity between the computationally predicted effects and the wet-lab biochemical effects. Comparative genome-wide pathway mapping revealed that the biological drug effects were realized largely via different pathways and mechanisms. In line with the predictions, the drugs showed differential effects on inflammatory pathways (downstream of PDGF, VEGF, IFNγ, TGFβ, IL1β, TNFα, LPS), transcriptional regulators (NFκB, C/EBP, STAT3, AP-1) and enzymes (PKCδ, AKT, PLA2), and they quenched different aspects of the inflammatory signaling cascade. Fenofibrate, the compound predicted to be most efficacious in inhibiting early processes of atherosclerosis, had the strongest effect on early lesion development. Conclusion Our approach provides mechanistic rationales for the differential and common effects of drugs and may help to better understand the origins of drug actions and the design of combination therapies.