Rational prediction of the herbicidal activities of novel protoporphyrinogen oxidase inhibitors by quantitative structure-activity relationship model based on docking-guided active conformation

Beilei Lei, Jiazhong Li, Jing Lu, Juan Du, Huanxiang Liu, Xlaojun Yao

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

Molecular docking-guided active conformation selection was used in a quantitative structure-activity relationship (QSAR) study of a series of novel protoporphyrinogen oxidase (PPO) inhibitors with herbicidal activities. The developed model can be used for the rational and accurate prediction of herbicidal activities of these inhibitors from their molecular structures. Molecular docking study was carried out to dock the inhibitors into the PPO active site and to obtain the rational active conformations. Based on the conformations generated from molecular docking, satisfactory predictive results were obtained by a genetic algorithm-multiple linear regression (GA-MLR) model according to the internal and external validations. The model gave a correlation coefficient R2 of 0.972 and 0.953 and an absolute average relative deviation AARD of 2.24% and 2.75% for the training set and test set, respectively. The results from this work demonstrate that the molecular docking-guided active conformation selection strategy is rational and useful in the QSAR study of these PPO inhibitors and for the quantitative prediction of their herbicidal activities. The results obtained could be helpful to the design of new derivatives with potential herbicidal activities

Original languageEnglish
Pages (from-to)9593-9598
Number of pages6
JournalJournal of Agricultural and Food Chemistry
Volume57
Issue number20
DOIs
Publication statusPublished - 28 Oct 2009
Externally publishedYes

Keywords

  • Genetic algorithm-multiple linear regression (GA-MLR)
  • Molecular clocking
  • Protoporphyrinogen oxidase (PPO)
  • Quantitative structure-activity relationship (QSAR)

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