Alzheimer's disease (AD) is the most common cause of dementia in old aged people and clinically used drugs for treatment are associated with side e®ects. Thus, there is a current demand for the discovery and development of new potential molecules. However, the recent advances in drug therapy have challenged the predominance of the disease. In this manuscript, an attempt has been made to develop the 2D and 3D quantitative structure-activity relationship (QSAR) models for a series of rutaecarpine, quinazolines and 7,8-dehydrorutaecarpine derivatives to obtain insights to Acetylcholinesterase (AChE) inhibition. Five di®erent QSAR models have been generated and validated using a set of 52 compounds comprising of varying sca®olds with IC 50 values ranging from 11,000 nM to 0.6 nM. These AChE-speci¯c prediction models (M1-M5) adequately re°ect the structure-activity relationship of the existing AChE inhibitors. Out of all developed models, QSAR model generated using ADME properties has been found to be the best with satisfactory statistical signi¯cance (regression (r 2 ) of 0.9309 and regression adjusted coe±cient of variation (r 2 adj ) of 0.9194). The QSAR models highlight the importance of aromatic moiety as their presence in the structure in°uence the biological activity. Additional insights on the compounds show that acyclic amines attached to side chain have lower activity than cyclic amines. The QSAR models pinpointing structural basis for the AChEIs suggest new guidelines for the design of novel molecules.