Gap junctions (GJs) made of connexin-43 (Cx43) are necessary for the conduction of electrical impulses in the heart. Modulation of Cx43 GJ activity may be beneficial in the treatment of cardiac arrhythmias and other dysfunctions. The search for novel GJ-modulating agents using molecular docking allows for the accurate prediction of binding affinities of ligands, which, unfortunately, often poorly correlate with their potencies. The objective of this study was to demonstrate that a Quantitative Structure-Activity Relationship (QSAR) model could be used for more precise identification of potent Cx43 GJ inhibitors. Using molecular docking, QSAR, and 3D-QSAR, we evaluated 16 known Cx43 GJ inhibitors, suggested the monocyclic monoterpene d-limonene as a putative Cx43 inhibitor, and tested it experimentally in HeLa cells expressing exogenous Cx43. The predicted concentrations required to produce 50% of the maximal effect (IC₅₀) for each of these compounds were compared with those determined experimentally (pIC₅₀ and eIC_50, respectively). The pIC₅₀ies of d-limonene and other Cx43 GJ inhibitors examined by our QSAR and 3D-QSAR models showed a good correlation with their eIC₅₀ies (R = 0.88 and 0.90, respectively) in contrast to pIC₅₀ies obtained from molecular docking (R = 0.78). However, molecular docking suggests that inhibitor potency may depend on their docking conformation on Cx43. Searching for new potent, selective, and specific inhibitors of GJ channels, we propose to perform the primary screening of new putative compounds using the QSAR model, followed by the validation of the most suitable candidates by patch-clamp techniques.

Gap junctions (GJs) made of connexin-43 (Cx43) are important for the conduction of electrical impulses in the heart. Modulation of Cx43 activity may be useful in the treatment of cardiac arrhythmias and other dysfunctions. Search of novel GJ modulating agents using molecular docking approach allows to predict the binding affinities that often significantly differ from experimentally estimated their potencies. The objective of this study was to demonstrate that Quantitative Structure-Activity Relationship (QSAR) model could be used for more precise identification of potent Cx43 GJ inhibitors. Using the QSAR model and molecular docking, we evaluated the known Cx43 GJ inhibitors, suggested a new one, and tested it experimentally. Our QSAR model predicted the concentrations required to produce 50% of the maximal effect (IC50) for each of these compounds and estimated the correlation between predicted and experimental IC50ies (pIC50 and eIC50). This led to suggestion of monocyclic monoterpene d-limonene as putative Cx43 inhibitor with pIC50 = 1.07. In turn, dual whole-cell patch-clamp measurements provided eIC50=1.41. The pIC50ies of d-limonene and other Cx43 GJ inhibitors examined by our QSAR model well correlated with their eIC50ies (R = 0.88) in contrast to pIC50s obtained from molecular docking (R = 0.42). However, the molecular docking suggested that inhibitor potency may depend on their docking sites on Cx43.