QSAR study of mosquito repellents using Codessa Pro

Katritzky, Alan R.; Dobchev, Dimitar A.; Tulp, Indrek; Karelson, Mati; Carlson, David A.

doi:10.1016/j.bmcl.2005.11.113

Cited by 57 publications

(47 citation statements)

References 14 publications

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“…This method, already successfully used in previous works [22,50,43], consists in analyzing the correlation improvement with the number of variables in the model. By plotting the R² values as functions of the number of descriptors, an asymptotic behavior was observed and the improvement of correlation became less significant after a certain rank (∆R² < 0.02-0.03).…”

Section: Discussionmentioning

confidence: 99%

Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanisms

et al. 2010

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Section: Discussionmentioning

confidence: 99%

Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanisms

et al. 2010

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“…The generation of the structural descriptors of the benzoic acids was performed with the CODESSA program [27]. The structures of the compounds were drawn with HyperChem Lite and the geometries were fully optimized, without symmetry restrictions, using the semi-empirical method AM1 [28] implemented in the MOPAC 6.0 program [29].…”

Section: Solute Descriptorsmentioning

confidence: 99%

QSPR Prediction of pK_a for Benzoic Acids in Different Solvents

2008

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A Computational Neural Network (CNN) derived model is proposed for the pK a prediction of benzoic acids in different solvents. The system studied contains 519 pK a values corresponding to 136 benzoic acids determined in water and in 8 organic solvents. The benzoic acids were described by the usual molecular descriptors and the solvents by a number of physical properties and by several parameters of the most widely used polarity solvent scales. The model is composed of seven descriptors -five of them corresponding to the solute and the other two to the solvents -and was validated by an external prediction set. The three sets of values needed in the analysis, training, prediction, and cross-validation, have the same squared correlation coefficient (0.998) and Root-Mean Square Error (RMSE) (0.21) values. The robustness of the model is also given for the statistical results for small subsets, such as ortho-and non-ortho-substituted acids, those obtained in protic or aprotic solvents, those obtained in each solvent, and even those for the set of pK a values of one specific acid in several solvents. The descriptors encode information about the chemical nature of the solutes and the solvents that is clearly related to the interactions present in the dissociation process in solution. The derived model also has the ability to predict pK a values of a larger set of aromatic neutral acids, containing both phenols and benzoic acids.

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“…Various packages (e.g. CODESSA 50 , DRAGON 51 , ALMOND 52 ) are available now a days for the calculation of large number of such descriptors.…”

Section: Qsar Methodologiesmentioning

confidence: 99%

“…The Catalyst program was used to identify the structural features in the group of 8 inhibitors whose IC 50 values ranged from 0.34 nM to 1.2 mM. The 3-D pharmacophore models are characterized by at least one hydrogen bond acceptor site and 2-3 hydrophobic sites and demonstrate very good correlation between the predicted and experimental IC 50 values.…”

Section: Qsar For Biological Activity Predictionmentioning

confidence: 99%

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Computer Aided Pesticide Design: A Rational Tool for Supplementing DDT Lacunae

2014

Chem Sci Trans

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Abstract:The reliance of mankind on synthetic pesticide, particularly dichloro diphenyl-trichloro ethane (DDT) reached its zenith during 1950s-60s, since the first application during second world War. But very soon it faced a serious scientific opposition due to its bio-magnifying nature and was banned in 1970s in most part of world with certain exceptional usage in health control programmes. Although, the pesticidal activity range and economic viability of DDT has never been questioned and still there are several voices to bring back DDT. To answer this controversy is the search for new DDT like pesticide with similar pesticidal efficacy and lower ecological accumulative effects. Recent advances in computer aided molecular design has provided us very robust, economic and time and labour saving tool to design and develop new chemical entities with pesticidal activity similar to DDT and has good commercial prospects as well. The present paper reviews the brief history of DDT and the developments in computational and molecular design methods to rejuvenate the era of new pesticide research.

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QSAR study of mosquito repellents using Codessa Pro

Cited by 57 publications

References 14 publications

Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanisms

Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanisms

QSPR Prediction of pK_a for Benzoic Acids in Different Solvents

Computer Aided Pesticide Design: A Rational Tool for Supplementing DDT Lacunae

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QSAR study of mosquito repellents using Codessa Pro

Cited by 57 publications

References 14 publications

Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanisms

Development of a QSPR model for predicting thermal stabilities of nitroaromatic compounds taking into account their decomposition mechanisms

QSPR Prediction of pKa for Benzoic Acids in Different Solvents

Computer Aided Pesticide Design: A Rational Tool for Supplementing DDT Lacunae

Contact Info

Product

Resources

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QSPR Prediction of pK_a for Benzoic Acids in Different Solvents