Computational design and evaluation of tacrine-based carbamate derivatives as acetylcholinesterase inhibitors

Abstract

Alzheimer's disease is marked by a gradual decline in cognitive function accompanied by alterations in cholinergic signaling. Cholinergic function can be improved by targeting acetylcholinesterase (AChE). In this work, an in silico approach was applied to study a series of tacrine-based carbamate derivatives. 3D-QSAR models determined by CoMFA and CoMSIA and validated by cross-validation, external testing and Y-randomization were developed using a dataset of 27 compounds. A complementary 2D-QSAR model provided consistent results to support the proposed structure–activity relationships. The statistical parameters (Q2 > 0.67 and R2 > 0.93) show the influence of steric and hydrogen bond donor effects on activity. Then, four new derivatives were proposed and tested. The ADMET analysis revealed good pharmacokinetic properties and low predicted toxicity. The DFT calculations characterized the electronic properties of the designed derivatives, and the docking results showed stronger contacts within the active sites of TcAChE (2CKM) and hAChE (4EY7). The selected complexes with both AChE structures were stable in the molecular dynamics simulations for 200 ns. The binding energies and stable conformational behavior of the selected complexes were further confirmed by MM-GBSA, PCA, FEL and DCCM analyses. Overall, the results indicate that the designed derivatives could be promising candidates for AChE inhibition in Alzheimer's disease.