A multiple linear regression approach to the estimation of carboxylic acid ester and lactone alkaline hydrolysis rate constants.

ABSTRACT: Pesticides, pharmaceuticals, and other organic contaminants often undergo hydrolysis when released into the environment; therefore, measured or estimated hydrolysis rates are needed to assess their environmental persistence. An intuitive multiple linear regression (MLR) approach was used to develop robust QSARs for predicting base-catalyzed rate constants of carboxylic acid esters (CAEs) and lactones. We explored various combinations of independent descriptors, resulting in four primary models (two for lactones and two for CAEs), with a total of 15 and 11 parameters included in the CAE and lactone QSAR models, respectively. The most significant descriptors include pK_a, electronegativity, charge density, and steric parameters. Model performance is assessed using Drug Theor

SUBMITTER: Lazare J 

PROVIDER: S-EPMC10547131 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature