QSRR models for potential local anaesthetic drugs using high performance liquid chromatography

Ďurčeková, Tatiana; Boronová, Katarína; Mocák, Ján; Lehotay, J.; Čiẑmárik, J

doi:10.1016/j.jpba.2011.09.035

Cited by 21 publications

(4 citation statements)

References 28 publications

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“…The lipophilic character of an active molecule, defined as the ability of a compound to penetrate through hydrophobic barriers in order to get from the delivery point to the site of action [1,2], is usually quantitatively characterized as the logarithmic forms of the n -octanol-water partition coefficient P ow (LogP ow ) and n -octanol-water distribution coefficient D ow (LogD ow )—experimentally determined [3] or calculated by using a series of mathematical models [4]. Due to experimental limitations of the classical “shake-flask” method [5], the most widely used techniques for the measurement of the lipophilic properties of different chemical molecules are nowadays the chromatographic techniques in reversed-phase systems (RP-TLC and RP-HPLC) [6,7].…”

Section: Introductionmentioning

confidence: 99%

Study of the Relationships between the Structure, Lipophilicity and Biological Activity of Some Thiazolyl-carbonyl-thiosemicarbazides and Thiazolyl-azoles

et al. 2015

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Lipophilicity, as one of the most important physicochemical parameters of bioactive molecules, was investigated for twenty-two thiazolyl-carbonyl-thiosemicarbazides and thiazolyl-azoles. The determination was carried out by reversed-phase thin-layer chromatography, using a binary isopropanol-water mobile phase. Chromatographically obtained lipophilicity parameters were correlated with calculated log P and log D and with some biological parameters, determined in order to evaluate the anti-inflammatory and antioxidant potential of the investigated compounds, by using principal component analysis (PCA). The PCA grouped the compounds based on the nature of their substituents (X, R and Y), indicating that their nature, electronic effects and molar volumes influence the lipophilicity parameters and their anti-inflammatory and antioxidant effects. Also, the results of the PCA analysis applied on all the experimental and computed parameters show that the best anti-inflammatory and antioxidant compounds were correlated with medium values of the lipophilicity parameters. On the other hand, the knowledge of the grouping patterns of the tested variables allows the reduction of the number of parameters, determined in order to establish the biological activity.

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Section: Introductionmentioning

confidence: 99%

Study of the Relationships between the Structure, Lipophilicity and Biological Activity of Some Thiazolyl-carbonyl-thiosemicarbazides and Thiazolyl-azoles

et al. 2015

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“…15 Quantitativestructure-activity/propertyrelationship(QSAR/ QSPR)isakindofeffectivemeans,bywhichchemicalstructure isquantitativelycorrelatedwithawelldefinedactivity/property. Since 1990ʹs, ithasbeenappliedwidelytopredictthechromatographicretentionfactors, [16][17][18][19] separationfactors, [20][21][22][23] andchiral resolutionability 24 ,whilethechiralityandtheabsoluteconfigurationsoftheenantiomerswerenotconsideredinthesestudies.As aresult,themainreasonfortheseparationoftheenantiomers couldnotbeelucidatedclearly.Chiraldescriptorsorcodeswere presentedtobuildtheQSAR [25][26][27] orQSPR [27][28][29][30] models.However, thesedescriptorsandcodeswerenotbroadlyusedbecauseofthe complicatedcomputationalmethods.Insomestudies, 31,32 however, ithasbeendisclosedthatthereexistssignificantdifferencesfor somestructuraldescriptorsbetweenapairofenantiomers. Whethercanthesestructuraldifferencesbeusedtobuildthe modeltopredicttheseparationofenantiomersaswellasjudgethe absoluteconfigurationsandelutionorderoftheenantiomers?For thispurpose,wereporttheQSPRmodelsofchiraldiarylmethane derivates.Three-dimensional(3D)structuraldescriptorsderived fromVolSurfprogramwereadoptedtopredicttheretention factorsandseparationfactorsfor63samples.…”

Section: Introductionmentioning

confidence: 99%

Predicting Retention and Separation Factors of Chiral Diarylmethane Derivates by QSPR Models

Hu¹,

Luo²,

Pan³

et al. 2015

Acta Physico-Chimica Sinica

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“…By QSRR models, the retention time of a new or untested chemical can be inferred from the molecular structure of similar compounds whose retention has already been assessed (Bodzioch et al 2010;Durcekova et al 2012). Currently, molecular modeling and computational chemistry are the inseparable parts in toxic design and discovery, and no one can talk about compounds design without having a bit of knowledge about computational methods (Bodzioch et al 2010;Durcekova et al 2012;Matteis et al 2010). Computational methods result in the saving of time and money for discovering new compounds in all steps of compound production.…”

Section: Introductionmentioning

confidence: 99%

Chemometrics analysis for investigation of retention behavior of hazardous compounds in effluents

Karimi

Farmany

Noorizadeh

2012

Environ Monit Assess

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The toxic substances, pesticides, and organic contaminants in effluents can potentially be causing damage that includes increased cancer risk; liver, kidney, stomach, nervous system, and immune system problems; reproductive difficulties; cataracts; and anemia. A quantitative structure-retention relationship (QSRR) was developed using the partial least square (PLS), kernel PLS (KPLS), and Levenberg-Marquardt artificial neural network (L-M ANN) approach for chemometrics study. The data which contained retention time (RT) of the 47 hazardous compounds in effluents were obtained by reverse-phase high-performance liquid chromatography. Genetic algorithm was employed as a factor selection procedure for PLS and KPLS modeling methods. By comparing the results, GA-PLS descriptors are selected for L-M ANN. Finally, a model with a low prediction error and a good correlation coefficient was obtained by L-M ANN. The described model does not require experimental parameters and potentially provides useful prediction for RT of new compounds. This is the first research on the QSRR of hazardous compounds in effluents using the chemometrics models.

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QSRR models for potential local anaesthetic drugs using high performance liquid chromatography

Cited by 21 publications

References 28 publications

Study of the Relationships between the Structure, Lipophilicity and Biological Activity of Some Thiazolyl-carbonyl-thiosemicarbazides and Thiazolyl-azoles

Study of the Relationships between the Structure, Lipophilicity and Biological Activity of Some Thiazolyl-carbonyl-thiosemicarbazides and Thiazolyl-azoles

Predicting Retention and Separation Factors of Chiral Diarylmethane Derivates by QSPR Models

Chemometrics analysis for investigation of retention behavior of hazardous compounds in effluents

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