scholarly journals Correlation between the lipophilicity and antifungal activity of some benzoxazole derivatives

2010 ◽  
pp. 177-185 ◽  
Author(s):  
Sanja Podunavac-Kuzmanovic ◽  
Sonja Velimirovic
Keyword(s):  
Antifungal Activity ◽  
Inhibitory Concentration ◽  
Quantitative Relationship ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Biologically Active ◽  
High Agreement ◽  
Structure Activity ◽  
Lipophilicity Parameter ◽  
Office Software

In the present work, a quantitative relationship between the lipophilicity and antifungal activity of some benzoxazole derivatives against Candida albicans was investigated by using QSAR (quantitative structure-activity relationship) analyses. The descriptors which describe numerically the lipophilicity, logP, were calculated using Chem-Office Software version 7.0. The linear correlation between the minimal inhibitory concentration (log1/cMIC) and lipophilicity descriptors was investigated. The best QSAR model predicting the antifungal activity of the investigated series of benzoxazole was developed. The results are discussed on the basis of statistical data. High agreement between theoretical and experimental inhibitory values was obtained. The results of this study indicate that the lipophilicity parameter has a significant effect on antifungal activity of this class of compounds, which can be very useful in the design of new biologically active molecules.

scholarly journals Quantitative structure-activity relationships to predict antibacterial effect of some benzimidazole derivatives

2008 ◽  
pp. 181-191 ◽  
Author(s):  
Sanja Podunavac-Kuzmanovic ◽  
Dijana Barna ◽  
Dragoljub Cvetkovic
Keyword(s):  
Antibacterial Activity ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Biologically Active ◽  
Benzimidazole Derivatives ◽  
Quantitative Structure ◽  
Structure Activity ◽  
Lipophilicity Parameter ◽  
Office Software

The antibacterial activity of some substituted benzimidazole derivatives against Gram negative bacteria Escherichia coli was investigated. The tested compounds displayed in vitro inhibitory activity and their minimum inhibitory concentrations were determined. Quantitative structure-activity relationship has been used to study the relationships between the antibacterial activity and lipophilicity parameter, logP. Lipophilicity parameters were calculated for each molecule by using CS Chem-Office Software version 7.0. Multiple linear regression was used to correlate the logP values and antibacterial activity of benzimidazole derivatives. The results are discussed on the basis of statistical data. The most acceptable QSAR model for prediction of antibacterial activity of the investigated series of benzimidazoles was developed. High agreement between experimental and predicted inhibitory values was obtained. The results of this study indicate that the lipophilicity parameter has a significant effect on antibacterial activity of this class of compounds, thus simplifying design of new biologically active molecules.

scholarly journals Quantitative structure-activity relationship of some 1-benzylbenzimidazole derivatives as antifungal agents

2007 ◽  
pp. 139-147 ◽  
Author(s):  
Sanja Podunavac-Kuzmanovic ◽  
Dijana Barna ◽  
Dragoljub Cvetkovic
Keyword(s):  
Antifungal Activity ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Biologically Active ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Yeast Saccharomyces Cerevisiae ◽  
Structure Activity ◽  
Lipophilicity Parameter

In the present study, the antifungal activity of some 1-benzylbenzimidazole derivatives against yeast Saccharomyces cerevisiae was investigated. The tested benzimidazoles displayed in vitro antifungal activity and minimum inhibitory concentration (MIC) was determined for all the compounds. Quantitative structure-activity relationship (QSAR) has been used to study the relationships between the antifungal activity and lipophilicity parameter, logP, calculated by using CS Chem-Office Software version 7.0. The results are discussed on the basis of statistical data. The best QSAR model for prediction of antifungal activity of the investigated series of benzimidazoles was developed. High agreement between experimental and predicted inhibitory values was obtained. The results of this study indicate that the lipophilicity parameter has a significant effect on antifungal activity of this class of compounds, which simplify design of new biologically active molecules.

scholarly journals The effect of lipophilicity on the antibacterial activity of some 1-benzylbenzimidazole derivatives

2008 ◽  
Vol 73 (10) ◽  
pp. 967-978 ◽  
Author(s):  
S.O. Podunavac-Kuzmanovic ◽  
D.D. Cvetkovic ◽  
D.J. Barna
Keyword(s):  
Antibacterial Activity ◽  
Quantitative Structure Activity Relationship ◽  
Biologically Active ◽  
Benzimidazole Derivatives ◽  
Log P ◽  
P Values ◽  
High Agreement ◽  
Software Products ◽  
Lipophilicity Parameter ◽  
Qsar Models

In the present paper, the antibacterial activity of some 1-benzylbenzimidazole derivatives were evaluated against the Gram-negative bacteria Escherichia coli. The minimum inhibitory concentration was determined for all the compounds. Quantitative structure-activity relationship (QSAR) was employed to study the effect of the lipophilicity parameters (log P) on the inhibitory activity. Log P values for the target compounds were experimentally determined by the "shake-flask" method and calculated by using eight different software products. Multiple linear regression was used to correlate the log P values and antibacterial activity of the studied benzimidazole derivatives. The results are discussed based on statistical data. The most acceptable QSAR models for the prediction of the antibacterial activity of the investigated series of benzimidazoles were developed. High agreement between the experimental and predicted inhibitory values was obtained. The results of this study indicate that the lipophilicity parameter has a significant effect on the antibacterial activity of this class of compounds, which simplifies the design of new biologically active molecules.

scholarly journals Identifying Structural Features of Sulforaphane Derivatives Based on QM Force Field for Predicting the Anti-Cancer Activity

2020 ◽  
Vol 8 (6) ◽  
pp. 1631-1636
Keyword(s):  
Biological Activity ◽  
Cancer Cells ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Structural Features ◽  
Biologically Active ◽  
Structure Activity ◽  
Anti Cancer ◽  
Derivatives Of ◽  
Cancer Activity

Sulforaphane (SFN) is a biologically active compound-based drug obtained from cruciferous vegetables, which has been investigated for its anti-tumor and chemopreventive effects. SFN shows a potential mechanism of its anti-cancer activity by binding to Macrophage Migration Inhibitory Factor (MIF) which is a pleiotropic cytokine that overexpresses in cancer cells increasing the aggressiveness of the disease. SFN can significantly inhibit the action of MIF on angiogenesis and the prevention of apoptosis in cancer cells. Preclinical studies on the anti-cancer activity of SFN showed promising results but in clinical studies, it is not yet convincing. Screening of a set of compounds chemically related to SFN can have a chance of showing promising anticancer activity. The quantitative structure activity relationship (QSAR) based on quantum mechanics has been done to derive the best mathematical model of these selected derivatives of sulforaphane for the calculation of its biological activity. These sulforaphane derivatives have been evaluated with respect to their ADMET and physicochemical properties. Validation was done to indicate the predictiveness of the model. The significant R2 value of 0.5676 between experimental and predicted biological activity and R2 cv value of 0.554 depicts a decent statistical fit of the model. A best QSAR model has been selected which has a future scope of helping in designing anti-cancerous drugs.

Phenolic Imidazole Derivatives with Dual Antioxidant/Antifungal Activity: Synthesis and Structure-Activity Relationship

2019 ◽  
Vol 15 (4) ◽  
pp. 341-351 ◽  
Author(s):  
Ana P. Bettencourt ◽  
Marián Castro ◽  
João P. Silva ◽  
Francisco Fernandes ◽  
Olga P. Coutinho ◽  
...  
Keyword(s):  
Antioxidant Activity ◽  
Antifungal Activity ◽  
Organic Molecules ◽  
Inhibitory Concentration ◽  
Yeast Species ◽  
Dpph Radical ◽  
Dpph Assay ◽  
Gram Negative ◽  
Structure Activity ◽  
Deoxyribose Degradation

Background: Previous publications show that the addition of a phenolic antioxidant to an antifungal agent, considerably enhances the antifungal activity. Objective: Synthesis of novel compounds combining phenolic units with linear or cyclic nitrogencontaining organic molecules with antioxidant/antifungal activity using methodologies previously developed in the group. Methods: Several N- [1,2-dicyano-2- (arylidenamino) vinyl]-O-alkylformamidoximes 3 were synthesized and cyclized to 4,5-dicyano-N- (N´-alcoxyformimidoyl)-2-arylimidazoles 4 upon reflux in DMF, in the presence of manganese dioxide or to 6-cyano-8-arylpurines 5 when the reagent was refluxed in acetonitrile with an excess of triethylamine. These compounds were tested for their antioxidant activity by cyclic voltammetry, DPPH radical (DPPH•) assay and deoxyribose degradation assay. The minimum inhibitory concentration (MIC) of all compounds was evaluated against two yeast species, Saccharomyces cerevisiae and Candida albicans, and against bacteria Bacillus subtilis (Gram-positive) and Escherichia coli (Gram negative). Their cytotoxicity was evaluated in fibroblasts. Results: Among the synthetised compounds, five presented higher antioxidant activity than reference antioxidant Trolox and from these compounds, four presented antifungal activity without toxic effects in fibroblasts and bacteria. Conclusion: Four novel compounds presented dual antioxidant/antifungal activity at concentrations that are not toxic to bacteria and fibroblasts. The active molecules can be used as an inspiration for further studies in this area.

Antimicrobial Screening, in Silico Studies and QSAR of Chalcone-based 1,4-disubstituted 1,2,3-triazole Hybrids

Drug Research ◽  
2020 ◽  
Author(s):  
Pinki Yadav ◽  
Kashmiri Lal ◽  
Ashwani Kumar
Keyword(s):  
Topoisomerase Ii ◽  
Antimicrobial Properties ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Binding Modes ◽  
E Coli ◽  
Structure Activity ◽  
In Silico Studies ◽  
Microbial Strains

AbstractThe in vitro antimicrobial properties of some chalcones (1a–1c ) and chalcone tethred 1,4-disubstituted 1,2,3-triazoles (2a–2u) towards different microbial strains viz. Staphylococcus aureus, Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa, Aspergillus niger and Candida albicans are reported. Compounds 2g and 2u exhibited better potency than the standard Fluconazole with MIC values of 0.0063 µmol/mL and 0.0068 µmol/mL, respectively. Furthermore, molecular docking was performed to investigate the binding modes of two potent compounds 2q and 2g with E. coli topoisomerase II DNA gyrase B and C. albicans lanosterol 14α-demethylase, respectively. Based on these results, a statistically significant quantitative structure activity relationship (QSAR) model was successfully summarized for antibacterial activity against B. subtilis.

scholarly journals Development of a new quantitative structure–activity relationship model for predicting Ames mutagenicity of food flavor chemicals using StarDrop™ auto-Modeller™

2021 ◽  
Vol 43 (1) ◽  
Author(s):  
Toshio Kasamatsu ◽  
Airi Kitazawa ◽  
Sumie Tajima ◽  
Masahiro Kaneko ◽  
Kei-ichi Sugiyama ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Ames Test ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Low Molecular Weight ◽  
Quantitative Structure ◽  
Industrial Chemicals ◽  
Structure Activity

Abstract Background Food flavors are relatively low molecular weight chemicals with unique odor-related functional groups that may also be associated with mutagenicity. These chemicals are often difficult to test for mutagenicity by the Ames test because of their low production and peculiar odor. Therefore, application of the quantitative structure–activity relationship (QSAR) approach is being considered. We used the StarDrop™ Auto-Modeller™ to develop a new QSAR model. Results In the first step, we developed a new robust Ames database of 406 food flavor chemicals consisting of existing Ames flavor chemical data and newly acquired Ames test data. Ames results for some existing flavor chemicals have been revised by expert reviews. We also collected 428 Ames test datasets for industrial chemicals from other databases that are structurally similar to flavor chemicals. A total of 834 chemicals’ Ames test datasets were used to develop the new QSAR models. We repeated the development and verification of prototypes by selecting appropriate modeling methods and descriptors and developed a local QSAR model. A new QSAR model “StarDrop NIHS 834_67” showed excellent performance (sensitivity: 79.5%, specificity: 96.4%, accuracy: 94.6%) for predicting Ames mutagenicity of 406 food flavors and was better than other commercial QSAR tools. Conclusions A local QSAR model, StarDrop NIHS 834_67, was customized to predict the Ames mutagenicity of food flavor chemicals and other low molecular weight chemicals. The model can be used to assess the mutagenicity of food flavors without actual testing.

Computational Atom-based Three-Dimensional Quantitative Structure-Activity Relationship (3D QSAR) Model for Predicting Anti-Dengue Agents

2021 ◽  
Vol 16 (10) ◽  
pp. 50-58
Author(s):  
Ali Qusay Khalid ◽  
Vasudeva Rao Avupati ◽  
Husniza Hussain ◽  
Tabarek Najeeb Zaidan
Keyword(s):  
Dengue Fever ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Contour Maps ◽  
Structure Activity ◽  
Bioactive Ligands

Dengue fever is a viral infection spread by the female mosquito Aedes aegypti. It is a virus spread by mosquitoes found all over the tropics with risk levels varying depending on rainfall, relative humidity, temperature and urbanization. There are no specific medications that can be used to treat the condition. The development of possible bioactive ligands to combat Dengue fever before it becomes a pandemic is a global priority. Few studies on building three-dimensional quantitative structure-activity relationship (3D QSAR) models for anti-dengue agents have been reported. Thus, we aimed at building a statistically validated atom-based 3D-QSAR model using bioactive ligands reported to possess significant anti-dengue properties. In this study, the Schrodinger PhaseTM atom-based 3D QSAR model was developed and was validated using known anti-dengue properties as ligand data. This model was also tested to see if there was a link between structural characteristics and anti-dengue activity of a series of 3-acyl-indole derivatives. The established 3D QSAR model has strong predictive capacity and is statistically significant [Model: R2 Training Set = 0.93, Q2 (R2 Test Set) = 0.72]. In addition, the pharmacophore characteristics essential for the reported anti-dengue properties were explored using combined effects contour maps (coloured contour maps: blue: positive potential and red: negative potential) of the model. In the pathway of anti-dengue drug development, the model could be included as a virtual screening method to predict novel hits.

Using nano-QSAR to determine the most responsible factor(s) in gold nanoparticle exocytosis

RSC Advances ◽  
2015 ◽  
Vol 5 (70) ◽  
pp. 57030-57037 ◽  
Author(s):  
Arafeh Bigdeli ◽  
Mohammad Reza Hormozi-Nezhad ◽  
Hadi Parastar
Keyword(s):  
Gold Nanoparticles ◽  
Gold Nanoparticle ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Structure Activity ◽  
Determining Factors

A nano-quantitative structure-activity relationship (nano-QSAR) model is proposed to indicate the determining factors responsible in the exocytosis of gold nanoparticles in macrophages.

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