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Combinatorial Chemistry & High Throughput Screening


ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

Research Article

New Research for Quinazoline-2,4-diones as HPPD Inhibitors Based on 2D-MLR and 3D-QSAR Models

Author(s): Ying Fu, Yi-Na Sun, Hai-Feng Cao, Ke-Han Yi, Li-Xia Zhao, Jia-Zhong Li and Fei Ye*

Volume 20, Issue 9, 2017

Page: [748 - 759] Pages: 12

DOI: 10.2174/1386207320666170622073738

Price: $65


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.

Keywords: HPPD inhibitor, 2D-MLR, pharmacophore, CoMFA, CoMSIA, 3D-QSAR models.

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