Quantitative structure–activity relationship models for compounds with anticonvulsant activity

Abstract Quantitative structure–activity relationship (QSAR) study has been conducted on 36 terpene derivatives with anticonvulsant activity in timed pentylenetetrazole (PTZ) infusion test. QSAR models for anticonvulsant activity prediction of hydrazones and esters of some monocyclic/bicyclic terpenoids were developed using simplex representation of molecular structure (SiRMS; informational field [IF]) approach based on the SiRMS and the IF of molecule. Four 2D partial least squares QSAR consensus models were developed with the coefficient of determination for test sets R test 2 > 0.62 {R}_{\text{test}}^{2}\gt 0.62 . Based on the established QSAR models, we found that carvone and verbenone cores possess the most significant contribution to antiseizure action examined on the model of PTZ-induced convulsions at 3 and 24 h after oral administration of terpene derivatives. Moreover, carbonyl and hydroxy group substitution in terpenoid molecules followed by hydrazones and esters formation leads to enhancement and prolongation of antiseizure action due to the contribution of additional molecular fragments. The presented QSAR models might be utilized to predict anticonvulsant effect among terpene derivatives for their oral administration against onset seizures.

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Molecular docking and quantitative structure-activity relationship study of anticonvulsant activity of aminobenzothiazole derivatives

Beni-Suef University Journal of Basic and Applied Sciences ◽

10.1016/j.bjbas.2017.11.002 ◽

2018 ◽

Vol 7 (2) ◽

pp. 204-214 ◽

Cited By ~ 2

Author(s):

Usman Abdulfatai ◽

Adamu Uzairu ◽

Sani Uba

Keyword(s):

Molecular Docking ◽

Anticonvulsant Activity ◽

Quantitative Structure Activity Relationship ◽

Structure Activity Relationship ◽

Activity Relationship ◽

Quantitative Structure ◽

Structure Activity ◽

Relationship Study

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A quantitative structure-activity relationship (QSAR) study of chlorinated cyclodiene insecticide analogs

10.31274/rtd-180813-12259 ◽

1995 ◽

Author(s):

Jianbo Liu

Keyword(s):

Quantitative Structure Activity Relationship ◽

Structure Activity Relationship ◽

Activity Relationship ◽

Quantitative Structure ◽

Qsar Study ◽

Structure Activity ◽

Cyclodiene Insecticide

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

Current Drug Discovery Technologies ◽

10.2174/1570163816666191108145026 ◽

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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