<![CDATA[Alzheimer's disease is a neurodegenerative condition that causes cognitive deficits and accounts for 60-80% of dementia cases. Several therapeutic strategies target this disease; one of them, cholinesterase inhibition, works through inhibition of the enzymes acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), for example rivastigmine. As a dual AChE/BChE inhibitor, rivastigmine causes gastrointestinal side effects, making natural compounds - particularly alkaloids - attractive alternative drug candidates. This study aimed to determine the potential of alkaloid compounds from Lycopodium clavatum as anti-Alzheimer agents in silico through a Quantitative Structure-Activity Relationship (QSAR) approach and molecular docking. Of the 20 alkaloid compounds obtained from the literature, all satisfied Lipinski's five rules, while 11 compounds passed selection based on LD50 category III values. The best QSAR model (Model 5) used the SA (surface area) descriptor with pKi against AChE as the dependent variable, yielding a coefficient of determination (R²) of 0.620 and a leave-one-out cross-validated Q² of 0.212, indicating that further validation with additional descriptors or a larger compound set is warranted. Molecular docking results identified acetylfawcettiine as the best candidate, with a binding energy of -11.70 kcal/mol and an inhibition constant of 2.66 µM against AChE, superior to rivastigmine (-6.98 kcal/mol; 7.59 µM).]]>
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