Use of connectivity index and simple topological parameters for estimating the inhibition potency of acetylcholinesterase.

ABSTRACT: Acetylcholinesterase (AChE) has proven to be an effective drug target in the treatment of neurodegenerative diseases such as Alzheimer's, Parkinson's and dementia. We developed a novel QSAR regression model for estimating potency to inhibit AChE, pK _i, on a set of 75 structurally different compounds including oximes, N-hydroxyiminoacetamides, 4-aminoquinolines and flavonoids. Although the model included only three simple descriptors, the valence molecular connectivity index of the zero-order, ⁰ χ^v , the number of 10-membered rings (nR10) and the number of hydroxyl groups (nOH), it yielded excellent statistics (r = 0.937, S.E. = 0.51). The stability of the model was evaluated when an initial set of 75 compounds was broadened to 165 compounds in total, with the increase of the range of pK _i (exp) from 6.0 to 10.2, yielding r = 0.882 and S.E. = 0.89. The predictive power of the model was evaluated by calculating pK _i values for 55 randomly chosen compounds (S.E._test = 0.90) from the calibration model created on other 110 compounds (S.E. = 0.89), all taken from the pool of 165 compounds.

SUBMITTER: Milicevic A 

PROVIDER: S-EPMC9068751 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature