Molecular docking and 3D-QSAR studies of 2-substituted 1-indanone derivatives as acetylcholinesterase inhibitors
Abstract
Aim: To explore the binding mode of 2-substituted 1-indanone derivatives with acetylcholinesterase (AChE) and provide hints for the future design of new derivatives with higher potency and specificity.
Methods: The GOLD-docking conformations of the compounds in the active site of the enzyme were used in subsequent studies. The highly reliable and predictive three-dimensional quantitative structure-activity relationship (3D-QSAR) models were achieved by comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods. The predictive capabilities of the models were validated by an external test set. Moreover, the stabilities of the 3D-QSAR models were verified by the leave-4-out cross-validation method.
Results: The CoMFA and CoMSIA models were constructed successfully with a good cross-validated coefficient (q2) and a non-cross-validated coefficient (r2). The q2 and r2 obtained from the leave-1-out cross validation method were 0.784 and 0.974 in the CoMFA model and 0.736 and 0.947 in the CoMSIA model, respectively. The coefficient isocontour maps obtained from these models were compatible with the geometrical and physicochemical properties of AChE.
Conclusion: The contour map demonstrated that the binding affinity could be enhanced when the small protonated nitrogen moiety was replaced by a more hydrophobic and bulky group with a highly partial positive charge. The present study provides a better understanding of the interaction between the inhibitors and AChE, which is helpful for the discovery of new compounds with more potency and selective activity.
Keywords:
Methods: The GOLD-docking conformations of the compounds in the active site of the enzyme were used in subsequent studies. The highly reliable and predictive three-dimensional quantitative structure-activity relationship (3D-QSAR) models were achieved by comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods. The predictive capabilities of the models were validated by an external test set. Moreover, the stabilities of the 3D-QSAR models were verified by the leave-4-out cross-validation method.
Results: The CoMFA and CoMSIA models were constructed successfully with a good cross-validated coefficient (q2) and a non-cross-validated coefficient (r2). The q2 and r2 obtained from the leave-1-out cross validation method were 0.784 and 0.974 in the CoMFA model and 0.736 and 0.947 in the CoMSIA model, respectively. The coefficient isocontour maps obtained from these models were compatible with the geometrical and physicochemical properties of AChE.
Conclusion: The contour map demonstrated that the binding affinity could be enhanced when the small protonated nitrogen moiety was replaced by a more hydrophobic and bulky group with a highly partial positive charge. The present study provides a better understanding of the interaction between the inhibitors and AChE, which is helpful for the discovery of new compounds with more potency and selective activity.