Development of Neural Network QSPR Models for Hansch Substituent Constants. 2. Applications in QSAR Studies of HIV-1 Reverse Transcriptase and Dihydrofolate Reductase Inhibitors
Ting‐Lan Chiu, Sung‐Sau So · Journal of Chemical Information and Computer Sciences · 2003
In this paper, the applications of a Hansch substituent constant predictor(1) to Quantitative Structure-Activity Relationships (QSAR) studies of E. coli dihydrofolate reductase (DHFR) inhibitors 2,4-diamino-5-(substituted-benzyl)pyrimidines as well as HIV-1 reverse transcriptase (RT) inhibitors 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine (HEPT) derivatives are demonstrated. Both data sets contain functional groups for which the substituent constants (pi, MR, F and R) could not be found in standard substituent constant tables. The substituent constant predictor allowed us to derive predicted pi, MR, F and R values for all substituents in both data sets, thus enabling the generation of easily interpretable QSAR models of comparable or better predictivity than previous models.