Molecular docking and 3D-QSAR of 16α,17α- cycloalkanoprogesterone derivatives as ligands of the progesterone receptor

A series of 42 (pregna-D′-pentarane) steroid ligands was used to generate models predicting ligand affinity to the progesterone receptor. The best result (Q2 = 0.91) was obtained using a combination of molecular docking, molecular dynamics simulation and artificial neural networks. Good predictive power of the model was validated using a group of 8 pentaranes synthesized separately and tested in vitro (Rtest2 = 0.77). This model can be used for determination of ligand-receptor binding affinity and accurate ranking of binding capacity of compounds tested. © Pleiades Publishing, Ltd., 2014.