Structure Activity Relationship and Quantitative Structure-Activity Relationships Modeling of Cyto-Toxicity of Phenothiazine Derivatives

2016 ◽  
Vol 5 (1) ◽  
pp. 124-129
Author(s):  
Zineb Almi ◽  
Salah Belaidi ◽  
Nadjib Melkemi ◽  
Salima Boughdiri ◽  
Lotfi Belkhiri
Keyword(s):  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Phenothiazine Derivatives ◽  
Structure Activity Relationships ◽  
Structure Activity ◽  
Quantitative Structure Activity Relationships

Combined 3D-quantitative structure–activity relationships and topomer technology-based molecular design of human 4-hydroxyphenylpyruvate dioxygenase inhibitors

2020 ◽  
Vol 12 (9) ◽  
pp. 795-811 ◽  
Author(s):  
Yong-Xuan Liu ◽  
Shuang Gao ◽  
Tong Ye ◽  
Jia-Zhong Li ◽  
Fei Ye ◽  
...  
Keyword(s):  
Inhibitory Activity ◽  
Binding Free Energy ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Type I ◽  
Quantitative Structure ◽  
Structure Activity Relationships ◽  
Structure Activity ◽  
Quantitative Structure Activity Relationships ◽  
Relationship Of

Aim: 4-Hydroxyphenylpyruvate dioxygenase (HPPD) has attracted increasing attention as an important target against tyrosinemia type I. This paper aimed to explore the structure–activity relationship of HPPD inhibitors with pyrazole scaffolds and to design novel HPPD inhibitors. Methodology & results: The best 3D-quantitative structure–activity relationships model was established by two different strategies based on 40 pyrazole scaffold-based analogs. Screening of molecular fragments by topomer technology, combined with molecular docking, 14 structures were identified for potential human HPPD inhibitory activity. Molecular dynamics results demonstrated that all the compounds obtained bound to the enzyme and possessed a satisfactory binding free energy. Conclusion: The quantitative structure–activity relationship of HPPD inhibitors of pyrazole scaffolds was clarified and 14 original structures with potential human HPPD inhibitory activity were obtained.

Prediction of Lipophilicity of some Quinolone Derivatives by using Quantitative Structure- Activity Relationship

2019 ◽  
Vol 16 ◽  
Author(s):  
Meysam Shirmohammadi ◽  
Zakiyeh Bayat ◽  
Esmat Mohammadinasab
Keyword(s):  
Partition Coefficient ◽  
Principal Component ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Selection Methods ◽  
Qsar Study ◽  
Structure Activity ◽  
Descriptor Selection

: Quantitative structure activity relationship (QSAR) was used to study the partition coefficient of some quinolones and their derivatives. These molecules are broad-spectrum antibiotic pharmaceutics. First, data were divided into two categories of train and test (validation) sets using random selection method. Second, three approaches including stepwise selection (STS) (forward), genetic algorithm (GA), and simulated annealing (SA) were used to select the descriptors, with the aim of examining the effect feature selection methods. To find the relation between descriptors and partition coefficient, multiple linear regression (MLR), principal component regression (PCR) and partial least squares (PLS) were used. QSAR study showed that the both regression and descriptor selection methods have vital role in the results. Different statistical metrics showed that the MLR-SA approach with (r2=0.96, q2=0.91, pred_r2=0.95) gives the best outcome. The proposed expression by MLR-SA approach can be used in the better design of novel quinolones and their derivatives.

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