Objective: The aim of this study was to screen for compounds with relatively high
inhibitory activity on acetylcholinesterase.
Methods: Classification models for acetylcholinesterase inhibitors based on KNN (1-nearest
neighbors), and a quantitative prediction model based on support vector machine regression were
used. The interaction of the compounds and receptors was analyzed using the molecular simulation
Results: The radial basis kernel function was selected as the kernel function for support vector
machine regression, and a total of 19 descriptors were selected to construct the quantitative