Alzheimer's disease is one of the leading causes of disability and death in the global scenario. Acetylcholinesterase inhibitors are symptomatically involved in the therapeutic management of Alzheimer's disease. Due to the prophetic capability of SMILES-based QSAR studies, the current method explored its efficiency for designing novel inhibitors of acetylcholinesterase enzyme. Two newly introduced validation parameters (the ideality of correlation (IIC) and the correlation contradiction index

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... CI)) were studied for further validating the predictive capability of developed models. The index of ideality of correlation was found to have a positive effect on models developed in comparison to models developed without IIC. The structural features accountable for intensifying the inhibitory activity were identified by performing QSAR modelling studies on 60 acetylcholinesterase inhibitors from the literature. Based on the molecular features identified designing of new molecules was accomplished and was found to have satisfactory inhibitory potential. Docking interactions of designed molecules pointed the importance of position of nitro group, aromatic ring and alkyl substitution in influencing the inhibitory activity and binding interactions. The designed compound DD2 was found to have highest inhibitory potential (4.33) and binding affinity (−11.2 kcal mol−1).