Title:New Research for Quinazoline-2,4-diones as HPPD Inhibitors Based on 2D-MLR and 3D-QSAR Models
VOLUME: 20 ISSUE: 9
Author(s):Ying Fu, Yi-Na Sun, Hai-Feng Cao, Ke-Han Yi, Li-Xia Zhao, Jia-Zhong Li and Fei Ye*
Affiliation:Department of Applied Chemistry, College of Science, Northeast Agricultural University, Harbin, 150030, Department of Applied Chemistry, College of Science, Northeast Agricultural University, Harbin, 150030, Department of Applied Chemistry, College of Science, Northeast Agricultural University, Harbin, 150030, Department of Applied Chemistry, College of Science, Northeast Agricultural University, Harbin, 150030, Department of Applied Chemistry, College of Science, Northeast Agricultural University, Harbin, 150030, School of Pharmacy, Lanzhou University, 199 West Donggang Rd., Lanzhou 730000, Department of Applied Chemistry, College of Science, Northeast Agricultural University, Harbin, 150030
Keywords:HPPD inhibitor, 2D-MLR, pharmacophore, CoMFA, CoMSIA, 3D-QSAR models.
Abstract:Aim and Objective: 4-Hydroxyphenylpyruvate dioxygenase (HPPD), converting phydroxyphenylpyruvate
(HPPA) to homogentisate (HGA), is an important target for treating type I
tyrosinemia and synthesizing novel herbicides due to its significant role in tyrosine catabolism.
Hence, it is imperative to design novel HPPD inhibitors that can block HPPA–HGA conversion,
which leads to the deficiency in isoprenoid redox cofactors such as plastoquinone and tocopherol,
and finally caused growth inhibition. This study was undertaken to investigate structural
requirements for their HPPD inhibition with better biological activity.
Materials and Methods: Based on the structure-activity relationships, a series of quinolinone-2,4-
diones derivatives were studied using combined of 2D multiple linear regression (2D-MLR) and 3D
quantitative structure-activity relationship (3D-QSAR). Firstly, genetic algorithm (GA) was applied
and descriptors generated in DRAGON 5.5 software were used for building 2D-MLR models in the
QSARINGS. Then CoMFA and CoMSIA models were performed by using alignment of the
common framework and the pharmacophore model. The obtained models were validated through
internal and external validation to verify predictive abilities. Especially, the CoMFA and CoMSIA
contour maps were used to show vital structural characteristics related to HPPD inhibitors activities.
Results: The 2D-MLR liner equation and corresponding parameters were listed as follows:
pKi = -38.2034Me+22.4078GATS2m-1.4265EEig15r-2.1849Hy+32.9158
ntr=28, npred=6, R2=0.863, Q2
LOO=0.787, Q2
LMO=0.607, Q2
F1=0.780, Q2
F2=0.780, Q2
F3=0.860,
CCCpred=0.920. RMSEtr=0.253, RMSEpred=0.555, F=36.289
The steric contours graph indicated that small and negative electrostatic substitutions at R1 and R2
regions were favorable for the better activity, and hydrogen-bond donors at this region would also
increase the activity. Positive electrostatic and bulky substitutions in the R3 position would enhance
the activity. The analysis of these models suggested that the steric factor of R4 position was crucial
for activity of quinazoline-2,4-diones HPPD inhibitors, bulky substitutions might improve the
bioactivity of these inhibitors greatly, meanwhile, hydrogen-bond acceptor groups in this position
were required for higher activity.
Conclusion: In this study, a combined 2D-MLR, CoMFA and CoMSIA models demonstrated
satisfying results through internal and external validation, especially good predictive abilities and the
CoMFA and CoMSIA contour maps showed vital structural characteristics related to HPPD
inhibitors activities.
