Target-based drug discovery for ?-globin disorders: drug target prediction using quantitative modeling with hybrid functional Petri nets

Abstract

Recent molecular studies provide important clues into treatment of beta-thalassemia, sickle-cell anaemia and other beta-globin disorders revealing that increased production of fetal hemoglobin, that is normally suppressed in adulthood, can ameliorate the severity of these diseases. In this paper, we present a novel approach for drug prediction for beta-globin disorders. Our approach is centered upon quantitative modeling of interactions in human fetal-to-adult hemoglobin switch network using hybrid functional Petri nets. In accordance with the reverse pharmacology approach, we pose a hypothesis regarding modulation of specific protein targets that induce gamma-globin and consequently fetal hemoglobin. Comparison of simulation results for the proposed strategy with the ones obtained for already existing drugs shows that our strategy is the optimal as it leads to highest level of gamma-globin induction and thereby has potential beneficial therapeutic effects on beta-globin disorders. Simulation results enable verification of model coherence demonstrating that it is consistent with qPCR data available for known strategies and/or drugs.