scholarly journals Quantitative structure-activity relationship study on the MMP-13 inhibitory activity of fused pyrimidine derivatives possessing a 1,2,4-Triazol-3-yl group as a ZBG

2021 ◽  
Vol 16 (1) ◽  
pp. 251-265
Author(s):  
Afsar Jahan ◽  
Brij Kishore Sharma ◽  
Vishnu Dutt Sharma
Keyword(s):  
Inhibitory Activity ◽  
Topological Charge ◽  
Structural Information ◽  
Quantitative Structure Activity Relationship ◽  
Quality Parameters ◽  
Applicability Domain ◽  
Pyrimidine Derivatives ◽  
Qsar Study ◽  
Atomic Properties ◽  
Dragon Descriptors

QSAR study has been carried out on the MMP-13 inhibitory activity of fused pyrimidine derivatives possessing a1,2,4-triazol-3-yl group as a ZBG in 0D- to 2D-Dragon descriptors. The derived QSAR models have revealed that the number of Sulfur atoms (descriptor nS), Balaban mean square distance index (descriptor MSD), molecular electrotopological variation (descriptor DELS), structural information content index of neighborhood symmetry of 2nd and 3rd order (descriptors SIC2 and SIC3), average valence connectivity index chi-4 (descriptor X4Av) in addition to 1st order Galvez topological charge index (descriptor JGI1) and global topological charge index (descriptor JGT) played a pivotal role in rationalization of MMP-13 inhibition activity of titled compounds. Atomic properties such as mass and volume in terms of atomic properties weighted descriptors MATS5m and MATS3v, and certain atom centred fragments such as CH2RX (descriptor C-006), X--CX--X (descriptor C-044), H attached to heteroatom (descriptor H-050) and H attached to C0(sp3) with 1X attached to next C (descriptor H-052) are also predominant to explain MMP-13 inhibition actions of fused pyrimidines. PLS analysis has also corroborated the dominance of CP-MLR identified descriptors. Applicability domain analysis revealed that the suggested model matches the high-quality parameters with good fitting power and the capability of assessing external data and all of the compounds was within the applicability domain of the proposed model and were evaluated correctly.

scholarly journals Sulfonamide Based β-Carbonic Anhydrase Inhibitors: 2D QSAR Study

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Meenakshi N. Deodhar ◽  
Priyanka L. Khopade ◽  
Mahesh G. Varat
Keyword(s):  
Carbon Dioxide ◽  
Inhibitory Activity ◽  
Molecular Design ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Carbonic Anhydrases ◽  
Human Pathogens ◽  
Qsar Study ◽  
Physiological Concentration ◽  
2D Qsar

The carbonic anhydrases (CAs) (or carbonate dehydratases) form a family of metalloenzymes that catalyze the rapid interconversion of carbon dioxide and water to bicarbonate and protons (or vice versa), a reversible reaction that occurs rather slowly in the absence of a catalyst. The β-CAs have been characterized in a high number of human pathogens, such as the fungi/yeasts Candida albicans, Candida glabrata, Cryptococcus neoformans, and Saccharomyces cerevisiae and the bacteria Helicobacter pylori, Mycobacterium tuberculosis, Haemophilus influenzae, Brucella suis, and Streptococcus pneumonia. The β-CAs in microorganisms provide physiological concentration of carbon dioxide and bicarbonate (CO2/HCO3-) for their growth. Inhibition of β-CAs from the pathogenic microorganism is recently being explored as a novel pharmacological target to treat infections caused by the these organisms. The present study aimed to establish a relationship between the β-CAs inhibitory activity for structurally related sulphonamide derivatives and the physicochemical descriptors in quantitative terms. The statistically validated two-dimensional quantitative structure activity relationship (2D QSAR) model was obtained through multiple linear regression (MLR) analysis method using Vlife molecular design suits (MDS). Five descriptors showing positive and negative correlation with the β-CAs inhibitory activity have been included in the model. This validated 2D QSAR model may be used to design sulfonamide derivatives with better inhibitory properties.

CoMFA, CoMSIA and HQSAR Analysis of 3-aryl-3-ethoxypropanoic Acid Derivatives as GPR40 Modulators

2020 ◽  
Vol 17 (1) ◽  
pp. 100-118
Author(s):  
Krishna A. Gajjar ◽  
Anuradha K. Gajjar
Keyword(s):  
Biological Activity ◽  
Structural Information ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Statistical Parameters ◽  
Qsar Study ◽  
Negative Contribution

Background: Human GPR40 receptor, also known as free fatty-acid receptor 1, is a Gprotein- coupled receptor that binds long chain free fatty acids to enhance glucose-dependent insulin secretion. In order to improve the resistance and efficacy, computational tools were applied to a series of 3-aryl-3-ethoxypropanoic acid derivatives. A relationship between the structure and biological activity of these compounds, was derived using a three-dimensional quantitative structure-activity relationship (3D-QSAR) study using CoMFA, CoMSIA and two-dimensional QSAR study using HQSAR methods. Methods: Building the 3D-QSAR models, CoMFA, CoMSIA and HQSAR were performed using Sybyl-X software. The ratio of training to test set was kept 70:30. For the generation of 3D-QSAR model three different alignments were used namely, distill, pharmacophore and docking based alignments. Molecular docking studies were carried out on designed molecules using the same software. Results: Among all the three methods used, Distill alignment was found to be reliable and predictive with good statistical results. The results obtained from CoMFA analysis q2, r2cv and r2 pred were 0.693, 0.69 and 0.992 respectively and in CoMSIA analysis q2, r2cv and r2pred were 0.668, 0.648 and 0.990. Contour maps of CoMFA (lipophilic and electrostatic), CoMSIA (lipophilic, electrostatic, hydrophobic, and donor) and HQSAR (positive & negative contribution) provided significant insights i.e. favoured and disfavoured regions or positive & negative contributing fragments with R1 and R2 substitutions, which gave hints for the modifications required to design new molecules with improved biological activity. Conclusion: 3D-QSAR techniques were applied for the first time on the series 3-aryl-3- ethoxypropanoic acids. All the models (CoMFA, CoMSIA and HQSAR) were found to be satisfactory according to the statistical parameters. Therefore such a methodology, whereby maximum structural information (from ligand and biological target) is explored, gives maximum insights into the plausible protein-ligand interactions and is more likely to provide potential lead candidates has been exemplified from this study.

scholarly journals Molecular Docking and QSAR Study of Chalcone and Pyrimidine Derivatives as Potent Anti-Malarial Agents against Plasmodium falciparum

2020 ◽  
Vol 85 ◽  
pp. 23-34
Author(s):  
Dayena J. Christian ◽  
Rajesh H. Vekariya ◽  
Kinjal D. Patel ◽  
Dhanji P. Rajani ◽  
Smita D. Rajani ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Molecular Docking ◽  
Antimalarial Activity ◽  
Docking Study ◽  
Quantitative Structure Activity Relationship ◽  
Negative Influence ◽  
Pyrimidine Derivatives ◽  
Molecular Docking Study ◽  
Qsar Study ◽  
Data Set

A data set of chalcone and pyrimidine derivatives with anti-malarial activity against Plasmodium falciparum was employed in investigating the quantitative structure-activity relationship (QSAR). Molecular docking study was performed for plasmodium falciparum dihydrofolate reductase (PfDHFR-TS). Genetic function approximation (GFA) technique was used to identify the descriptors that have influence on anti-malarial activity. The most influencing molecular descriptors identified include thermodynamics, structural and physical descriptors. Generated model was found to be good based on correlation coefficient, LOF, rm2 and rcv2 values. Nrotb, solubility, polarizibility may have negative influence on antimalarial activity or play an important role in growth inhibition of Plasmodium falciparum. The QSAR models so constructed provide fruitful insights for the future development of anti-malarial agents.

scholarly journals Application of Wavelet and Genetic Algorithms for QSAR Study on 5-Lipoxygenase Inhibitors and Design New Compounds

2017 ◽  
Vol 59 (3) ◽  
Author(s):  
Fatemeh Bagheban Shahri
Keyword(s):  
Inhibitory Activity ◽  
Multivariate Calibration ◽  
Quantitative Structure Activity Relationship ◽  
Qsar Modeling ◽  
Qsar Study ◽  
Prediction Ability ◽  
Lipoxygenase Inhibitors ◽  
Calibration Methods ◽  
High Prediction ◽  
New Compounds

A quantitative structure-activity relationship (QSAR) modeling was carried out for the prediction of inhibitory activity of 1-phenyl[2H]-tetrahydro-triazine-3-one analogues as inhibitors of 5-lipoxygenase. Partial least squares (PLS) algorithm was employed to model the relationships between molecular descriptors and inhibitory activity of molecules using the genetic algorithm (GA) method as variable selection tool. Pre-processing methods such as wavelet transform (WT) were also used to enhance the predictive power of multivariate calibration methods. To evaluate the models applied in this study (PLS, GA-PLS and WT-GA-PLS), the inhibitory activities of several compounds, not included in the modeling procedure, were predicted. The results of models showed high prediction ability with root mean square error of prediction 0.194, 0.161 and 0.140 for PLS, GA-PLS and WT-GA-PLS, respectively. The WT-GA-PLS method was employed to predict the inhibitory activity of the new inhibitor derivatives.

A QSAR study of macrocyclic diterpenes with P-gp inhibitory activity isolated from Euphorbia species

Planta Medica ◽  
2011 ◽  
Vol 77 (12) ◽  
Author(s):  
IJ Sousa ◽  
J Molnar ◽  
MU Ferreira ◽  
MX Fernandes
Keyword(s):  
Inhibitory Activity ◽  
Qsar Study

QSAR Studies of Halogenated Pyrimidine Derivatives as Inhibitors of Human Dihydroorotate Dehydrogenase Using Modified Bee Algorithm

2018 ◽  
Vol 21 (5) ◽  
pp. 381-387 ◽  
Author(s):  
Hossein Atabati ◽  
Kobra Zarei ◽  
Hamid Reza Zare-Mehrjardi
Keyword(s):  
External Validation ◽  
Correlation Coefficients ◽  
Quantitative Structure Activity Relationship ◽  
Molecular Structures ◽  
Dihydroorotate Dehydrogenase ◽  
Pyrimidine Derivatives ◽  
Qsar Studies ◽  
Bee Algorithm ◽  
Test Sets ◽  
Leave One Out

Aim and Objective: Human dihydroorotate dehydrogenase (DHODH) catalyzes the fourth stage of the biosynthesis of pyrimidines in cells. Hence it is important to identify suitable inhibitors of DHODH to prevent virus replication. In this study, a quantitative structure-activity relationship was performed to predict the activity of one group of newly synthesized halogenated pyrimidine derivatives as inhibitors of DHODH. Materials and Methods: Molecular structures of halogenated pyrimidine derivatives were drawn in the HyperChem and then molecular descriptors were calculated by DRAGON software. Finally, the most effective descriptors for 32 halogenated pyrimidine derivatives were selected using bee algorithm. Results: The selected descriptors using bee algorithm were applied for modeling. The mean relative error and correlation coefficient were obtained as 2.86% and 0.9627, respectively, while these amounts for the leave one out−cross validation method were calculated as 4.18% and 0.9297, respectively. The external validation was also conducted using two training and test sets. The correlation coefficients for the training and test sets were obtained as 0.9596 and 0.9185, respectively. Conclusion: The results of modeling of present work showed that bee algorithm has good performance for variable selection in QSAR studies and its results were better than the constructed model with the selected descriptors using the genetic algorithm method.

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.

Action of Thioglycosides of 1,2,4-Triazoles and Imidazoles on the Oxidative Stress and Glycosidases in Mice with Molecular Docking

2019 ◽  
Vol 16 (6) ◽  
pp. 696-710
Author(s):  
Mahmoud Balbaa ◽  
Doaa Awad ◽  
Ahmad Abd Elaal ◽  
Shimaa Mahsoub ◽  
Mayssaa Moharram ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Molecular Docking ◽  
Active Sites ◽  
Biological Activities ◽  
Imidazole Ring ◽  
Quantitative Structure Activity Relationship ◽  
Binding Interaction ◽  
Qsar Study

Background: ,2,3-Triazoles and imidazoles are important five-membered heterocyclic scaffolds due to their extensive biological activities. These products have been an area of growing interest to many researchers around the world because of their enormous pharmaceutical scope. Methods: The in vivo and in vitro enzyme inhibition of some thioglycosides encompassing 1,2,4- triazole N1, N2, and N3 and/or imidazole moieties N4, N5, and N6. The effect on the antioxidant enzymes (superoxide dismutase, glutathione S-transferase, glutathione peroxidase and catalase) was investigated as well as their effect on α-glucosidase and β-glucuronidase. Molecular docking studies were carried out to investigate the mode of the binding interaction of the compounds with α- glucosidase and β -glucuronidase. In addition, quantitative structure-activity relationship (QSAR) investigation was applied to find out the correlation between toxicity and physicochemical properties. Results: The decrease of the antioxidant status was revealed by the in vivo effect of the tested compounds. Furthermore, the in vivo and in vitro inhibitory effects of the tested compounds were clearly pronounced on α-glucosidase, but not β-glucuronidase. The IC50 and Ki values revealed that the thioglycoside - based 1,2,4-triazole N3 possesses a high inhibitory action. In addition, the in vitro studies demonstrated that the whole tested 1,2,4-triazole are potent inhibitors with a Ki magnitude of 10-6 and exhibited a competitive type inhibition. On the other hand, the thioglycosides - based imidazole ring showed an antioxidant activity and exerted a slight in vivo stimulation of α-glucosidase and β- glucuronidase. Molecular docking proved that the compounds exhibited binding affinity with the active sites of α -glucosidase and β-glucuronidase (docking score ranged from -2.320 to -4.370 kcal/mol). Furthermore, QSAR study revealed that the HBD and RB were found to have an overall significant correlation with the toxicity. Conclusion: These data suggest that the inhibition of α-glucosidase is accompanied by an oxidative stress action.

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