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Abstract
There is a need for continued development of acetylcholinesterase (AChE) inhibitors that could prolong the life of acetylcholine in the synaptic cleft and also prevent the aggregation of amyloid peptides associated with Alzheimer’s disease. The lack of a 3D-QSAR model which specifically deconvulates the type of interactions and quantifies them in terms of energies has motivated us to report a CoRIA model vis-à-vis the standard 3D-QSAR methods, CoMFA and CoMSIA. The CoRIA model was found to be statistically superior to the CoMFA and CoMSIA models and it could efficiently extract key residues involved in ligand recognition and binding to AChE. These interactions were quantified to gauge the magnitude of their contribution to the biological activity. In order to validate the CoRIA model, a pharmacophore map was first constructed and then used to virtually screen public databases, from which novel scaffolds were cherry picked that were not present in the training set. The biological activities of these novel molecules were then predicted by the CoRIA, CoMFA, and CoMSIA models. The hits identified were purchased and their biological activities were measured by the Ellman’s method for AChE inhibition. The predicted activities are in unison with the experimentally measured biological activities.
Acknowledgments
The computational studies were possible because of the grants to the Department of Pharmaceutical Chemistry from Department of Biotechnology (DBT) [BT/PR11810/BRB/10/690/2009]; Department of Science and Technology (DST-SERB) [SR/SO/HS-0117/2012], and the Council for Scientific and Industrial Research (CSIR) [01/2399/10/EMRII and 02(0047)/12/EMR-II]. Elvis acknowledges the financial assistance from All India Council of Technical Education for postgraduate studies.