Quantitative structural-activity relationship (QSAR) study for fungicidal activities of thiazoline derivatives against rice blast

Jin Soo Song, Taesung Moon, Kee Dal Nam, Jae Kyun Lee, Hoh Gyu Hahn, Eui Ju Choi, Chang No Yoon

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

For the development of new fungicides against rice blast, the quantitative structural-activity relationship (QSAR) analyses for fungicidal activities of thiazoline derivatives were carried out using multiple linear regression (MLR) and neural network (NN). We have studied the substituent effects at para site of R1 and at three sites (ortho, meta, or para) of R2 aromatic rings in compounds. The results of MLR and NN analyses in the training set of Set-3 showed good correlations (r2 values of 0.829 and 0.966, respectively) between the descriptors and the fungicidal activities. Five descriptors including the non-overlap steric volume (SVR2 C2), Connolly surface area (SAR1), hydrophobicity (∑ πR2), and Hammett substituent constants (σp R1 and σm R2) were selected as important factors of fungicidal activities. Although the descriptors of optimum MLR model were used in NN, the results were improved by NN. This means that the descriptors used in MLR model include non-linear relationships.

Original languageEnglish
Pages (from-to)2133-2142
Number of pages10
JournalBioorganic and Medicinal Chemistry Letters
Volume18
Issue number6
DOIs
Publication statusPublished - 2008 Mar 15

    Fingerprint

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Organic Chemistry
  • Drug Discovery
  • Pharmaceutical Science

Cite this