scholarly journals 2D-QSAR Study of Indolylpyrimidines Derivative as Antibacterial against Pseudomonas aeruginosa and Staphylococcus aureus: A Comparative Approach

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Prasanna A. Datar
Keyword(s):  
Staphylococcus Aureus ◽  
Pseudomonas Aeruginosa ◽  
Qsar Model ◽  
Antibacterial Activities ◽  
Quantitative Structure Activity Relationship ◽  
Comparative Approach ◽  
Qsar Study ◽  
Qsar Analysis ◽  
Leave One Out ◽  
And Staphylococcus Aureus

A set of 15 indolylpyrimidine derivatives with their antibacterial activities in terms of minimum inhibitory concentration against the gram-negative bacteria Pseudomonas aeruginosa and gram-positive Staphylococcus aureus were selected for 2D quantitative structure activity relationship (QSAR) analysis. QSAR was performed using a combination of various descriptors such as steric, electronic and topological. Stepwise regression method was used to derive the most significant QSAR equation for predicting the inhibitory activity of this class of molecules. The best QSAR model was further validated by a leave one out technique as well as by the random trials. A high correlation between experimental and predicted inhibitory values was observed. A comparative picture of behavior of indolylpyrimidines against both of the microorganisms is discussed.

scholarly journals QSAR Analysis of 5-Substituted-2-Benzoyl-aminobenzoic acids as PPAR Modulator

2004 ◽  
Vol 1 (5) ◽  
pp. 243-250 ◽  
Author(s):  
R. Hemalatha ◽  
L. K. Soni ◽  
A. K. Gupta ◽  
S. G. Kaskhedikar
Keyword(s):  
Linear Regression Analysis ◽  
Qsar Model ◽  
Multiple Linear Regression Analysis ◽  
Quantitative Structure Activity Relationship ◽  
Statistical Regression ◽  
Qsar Study ◽  
Qsar Analysis ◽  
Aminobenzoic Acids ◽  
Leave One Out ◽  
Α Activity

A quantitative structure activity relationship (QSAR) study on a series of analogs of 5-aryl thiazolidine-2, 4-diones with activity on PPAR-α and PPAR-γwas made using combination of various thermodynamic, electronic and spatial descriptors. Several statistical regression expressions were obtained using multiple linear regression analysis. The best QSAR model was further validated by leave one out cross validation method. The studied revealed that for dual PPAR-α/γactivity dipole-dipole energy and PMI-Z play significant role and contributed positively for PPAR-γand PPAR-α activity respectively. Thus, QSAR brings important structural insight to aid the design of dual PPAR-α /γreceptor agonist.

scholarly journals QSAR modeling of antibacterial activity of some benzimidazole derivatives

2011 ◽  
Vol 17 (1) ◽  
pp. 33-38 ◽  
Author(s):  
Sanja Podunavac-Kuzmanovic ◽  
Dragoljub Cvetkovic
Keyword(s):  
Antibacterial Activity ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Structural Features ◽  
Benzimidazole Derivatives ◽  
Qsar Modeling ◽  
Qsar Study ◽  
Validation Procedure ◽  
Leave One Out

A quantitative structure-activity relationship (QSAR) study has been carried out for training set of 12 benzimidazole derivatives to correlate and predict the antibacterial activity of studied compounds against Gram-negative bacteria Pseudomonas aeruginosa. Multiple linear regression was used to select the descriptors and to generate the best prediction model that relates the structural features to inhibitory activity. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based on the following descriptors: parameter of lipophilicity (logP) and hydration energy (HE). Good agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the generated QSAR model.

scholarly journals 3D-QSAR and Docking Studies of a Series ofβ-Carboline Derivatives as Antitumor Agents of PLK1

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jahan B. Ghasemi ◽  
Valentin Davoudian
Keyword(s):  
Antitumor Agents ◽  
Three Dimensional ◽  
Human Tumor ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Human Tumor Cell Lines ◽  
Qsar Analysis ◽  
Leave One Out

An alignment-free, three dimensional quantitative structure-activity relationship (3D-QSAR) analysis has been performed on a series ofβ-carboline derivatives as potent antitumor agents toward HepG2 human tumor cell lines. A highly descriptive and predictive 3D-QSAR model was obtained through the calculation of alignment-independent descriptors (GRIND descriptors) using ALMOND software. For a training set of 30 compounds, PLS analyses result in a three-component model which displays a squared correlation coefficient (r2) of 0.957 and a standard deviation of the error of calculation (SDEC) of 0.116. Validation of this model was performed using leave-one-out,q2looof 0.85, and leave-multiple-out. This model gives a remarkably highr2pred(0.66) for a test set of 10 compounds. Docking studies were performed to investigate the mode of interaction betweenβ-carboline derivatives and the active site of the most probable anticancer receptor, polo-like kinase protein.

scholarly journals QSAR Study of (5-Nitroheteroaryl-1,3,4-Thiadiazole-2-yl) Piperazinyl Derivatives to Predict New Similar Compounds as Antileishmanial Agents

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Abdellah Ousaa ◽  
Bouhya Elidrissi ◽  
Mounir Ghamali ◽  
Samir Chtita ◽  
Adnane Aouidate ◽  
...  
Keyword(s):  
External Validation ◽  
Correlation Coefficients ◽  
Predictive Ability ◽  
Quantitative Structure Activity Relationship ◽  
Qsar Study ◽  
Qsar Analysis ◽  
Ann Models ◽  
Artificial Neural Network Ann ◽  
Leave One Out ◽  
New Compounds

To search for newer and potent antileishmanial drugs, a series of 36 compounds of 5-(5-nitroheteroaryl-2-yl)-1,3,4-thiadiazole derivatives were subjected to a quantitative structure-activity relationship (QSAR) analysis for studying, interpreting, and predicting activities and designing new compounds using several statistical tools. The multiple linear regression (MLR), nonlinear regression (RNLM), and artificial neural network (ANN) models were developed using 30 molecules having pIC50 ranging from 3.155 to 5.046. The best generated MLR, RNLM, and ANN models show conventional correlation coefficients R of 0.750, 0.782, and 0.967 as well as their leave-one-out cross-validation correlation coefficients RCV of 0.722, 0.744, and 0.720, respectively. The predictive ability of those models was evaluated by the external validation using a test set of 6 molecules with predicted correlation coefficients Rtest of 0.840, 0.850, and 0.802, respectively. The applicability domains of MLR and MNLR transparent models were investigated using William’s plot to detect outliers and outsides compounds. We expect that this study would be of great help in lead optimization for early drug discovery of new similar compounds.

scholarly journals ELECTRONIC SPECTRAL CHARACTERIZATION AND ANTIBACTERIAL ACTIVITY OF LANTHANIDE (III) - CEFTAZIDIME COMPLEXES

2020 ◽  
Vol 5 (2) ◽  
pp. 57-65
Author(s):  
Preeti Singhal ◽  
Renuka Jain ◽  
Deepti Goyal
Keyword(s):  
Escherichia Coli ◽  
Staphylococcus Aureus ◽  
Pseudomonas Aeruginosa ◽  
Antibacterial Activity ◽  
Special Reference ◽  
Antibacterial Activities ◽  
Intensity Parameters ◽  
The Impact ◽  
And Staphylococcus Aureus ◽  
Ligand Bond

The present work describes the spectrochemical study of some Lanthanide (III) - ceftazidime (Ln(III)-CEFZ) complexes. The impact of the ligand environment on electronic spectrum of the lantanide ion with special reference to complexation and nature of Ln-ligand bond has been examined. The energy and intensity parameters for the complexes have also been evaluated. The ligand and all prepared complexes were screened for their antibacterial activities against Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus and the results showed that antibacterial activity of ligand on complexation have been enhanced.

Study of Peptides QSAR Based on Multidimensional Attributes (E) Using Multiple Linear Regression

2011 ◽  
Vol 345 ◽  
pp. 263-269 ◽  
Author(s):  
Jia Jian Yin
Keyword(s):  
Amino Acids ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Correlation Coefficients ◽  
Meaningful Work ◽  
Quantitative Structure Activity Relationship ◽  
Structure Characterization ◽  
Qsar Study ◽  
Qsar Analysis ◽  
Leave One Out

A new amino acids descriptor E, which (E1~E5) has been introduced in bioactive peptides Quantitative Structure-Activity Relationship (QSAR) Study. It has been proved that correlate good with hydrophobicity, size, preference for amino acids to occur in -helices, composition and the net charge, respectively. They were then applied to construct characterization and QSAR analysis on 48 bitter tasting dipeptides and 30 bradykinin potentiating (BP) pentapeptides using multiple linear regression (MLR). The leave-one-out cross validation values (Q2(CV)) were 0.888 and 0.797, the multiple correlation coefficients (R2) were 0.940 and 0.891, respectively for bitter tasting dipeptides and BP pentapeptides. The results showed that, in comparison with the conventional descriptors, the descriptor (E) is a useful structure characterization method for peptide QSAR analysis. The importance of each property at each position in peptides is estimated by the regression coefficient value of the MLR model. The establishment of such methods will be a very meaningful work to peptide bioactive investigation in peptide drug design.

scholarly journals Antimicrobial Efficacy and Spectrum of Phosphorous-Fluorine Co-Doped TiO2 Nanoparticles on the Foodborne Pathogenic Bacteria Campylobacter jejuni, Salmonella Typhimurium, Enterohaemorrhagic E. coli, Yersinia enterocolitica, Shewanella putrefaciens, Listeria monocytogenes and Staphylococcus aureus

Foods ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1786
Author(s):  
György Schneider ◽  
Bettina Schweitzer ◽  
Anita Steinbach ◽  
Botond Zsombor Pertics ◽  
Alysia Cox ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Campylobacter Jejuni ◽  
Food Industry ◽  
Pathogenic Bacteria ◽  
Antibacterial Activities ◽  
Tio2 Nps ◽  
E Coli ◽  
Foodborne Pathogenic Bacteria ◽  
And Staphylococcus Aureus ◽  
Co Doped

Contamination of meats and meat products with foodborne pathogenic bacteria raises serious safety issues in the food industry. The antibacterial activities of phosphorous-fluorine co-doped TiO2 nanoparticles (PF-TiO2) were investigated against seven foodborne pathogenic bacteria: Campylobacter jejuni, Salmonella Typhimurium, Enterohaemorrhagic E. coli, Yersinia enterocolitica, Shewanella putrefaciens, Listeria monocytogenes and Staphylococcus aureus. PF-TiO2 NPs were synthesized hydrothermally at 250 °C for 1, 3, 6 or 12 h, and then tested at three different concentrations (500 μg/mL, 100 μg/mL, 20 μg/mL) for the inactivation of foodborne bacteria under UVA irradiation, daylight exposure or dark conditions. The antibacterial efficacies were compared after 30 min of exposure to light. Distinct differences in the antibacterial activities of the PF-TiO2 NPs, and the susceptibilities of tested foodborne pathogenic bacterium species were found. PF-TiO2/3 h and PF-TiO2/6 h showed the highest antibacterial activity by decreasing the living bacterial cell number from ~106 by ~5 log (L. monocytogenes), ~4 log (EHEC), ~3 log (Y. enterolcolitca, S. putrefaciens) and ~2.5 log (S. aureus), along with complete eradication of C. jejuni and S. Typhimurium. Efficacy of PF-TiO2/1 h and PF-TiO2/12 h NPs was lower, typically causing a ~2–4 log decrease in colony forming units depending on the tested bacterium while the effect of PF-TiO2/0 h was comparable to P25 TiO2, a commercial TiO2 with high photocatalytic activity. Our results show that PF-co-doping of TiO2 NPs enhanced the antibacterial action against foodborne pathogenic bacteria and are potential candidates for use in the food industry as active surface components, potentially contributing to the production of meats that are safe for consumption.

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