Quantitative structure-activity relationships in 1-aryl-2-(alkylamino)ethanol antimalarials

Kim, Ki Hwan; Hansch, Corwin; Fukunaga, James Y.; Steller, Edward E.; Jow, P. Y. C.; Craig, Paul N.; Page, June

doi:10.1021/jm00190a007

Cited by 37 publications

(8 citation statements)

References 10 publications

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“…It seems to us that receptors in the central or shallow compartment would show relatively little dependence on log P and that the parabolic dependence of activity on log P would be broad. This would appear to be true for drugs acting on blood cells [Kim et al, 1979;Hansch et al, 198Oal. For example, in a set of over 700 antimalarials actkg in mice, it was found that antimalarial activity had almost no dependence on overall log P (a very shallow parabola), despite the fact that there was a wide range in log P for the set.…”

Section: When To Stop Modification In Drug Designmentioning

confidence: 99%

The physicochemical approach to drug design and discovery (QSAR)

Hansch

1981

Drug Development Research

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The study of physicochemical parameters to correlate mathematically chemical structure with biological activity induced by sets of congeneric drugs is now generally referred to as QSAR (quantitative structure‐activity relationships). The ways in which the QSAR paradigm are developing are becoming more varied and complex. Many kinds of parameters are under study in many different groups; various types of mathematical models have been proposed and are being evaluated. Drug researchers are turning more to enzyme modulation to control various biological processes. It is the study of enzyme‐ligand reactions of enzymes whose x‐ray crystallographic structure is known that affords us the means for developing a deeper understanding of QSAR and, at the same time, enhancing our ability to make drugs more selective for various forms of a given enzyme. The union of x‐ray crystallography, moleculargraphics, and QSAR is one of the most exciting new areas of drug development. This report is an introduction to how QSAR is being used to gain insight into the interaction of drugs with macromolecules and macromolecular systems.

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Section: When To Stop Modification In Drug Designmentioning

confidence: 99%

The physicochemical approach to drug design and discovery (QSAR)

Hansch

1981

Drug Development Research

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“…The characteristic 1 H-NMR and 13 C-NMR data of compounds 6a – 6d are shown in Table 1. In the 1 H-NMR spectra, the proton at C-4 of 4β-substituted compounds appears as a doublet at 4.72–4.96 ppm, usually with a coupling constant J 3-4 < 4.0 Hz, indicating a cis -relationship between C 3 -H and C 4 -H 31. The coupling constant of the anomeric proton of the glucose residue ( J 1”-2” ) is typically <4.0 Hz, which confirms that the glycosidic linkage is fan α–linkage.…”

Section: Resultsmentioning

confidence: 99%

<p>Glucoside Derivatives Of Podophyllotoxin: Synthesis, Physicochemical Properties, And Cytotoxicity</p>

Liu

Kong

et al. 2019

DDDT

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BackgroundWidespread concern of the side effects and the broad-spectrum anticancer property of podophyllotoxin as an antitumor agent highlight the need for the development of new podophyllotoxin derivatives. Although some per-butyrylated glucosides of podophyllotoxin and 4β-triazolyl-podophyllotoxin glycosides show good anticancer activity, the per-acetylated/free of podophyllotoxin glucosides and their per-acetylated are not well studied.MethodsA few glucoside derivatives of PPT were synthesized and evaluated for their in vitro cytotoxic activities against five human cancer cell lines, HL-60 (leukemia), SMMC-7721 (hepatoma), A-549 (lung cancer), MCF-7 (breast cancer), and SW480 (colon cancer), as well as the normal human pulmonary epithelial cell line (BEAS-2B). In addition, we investigated the structure–activity relationship and the physicochemical property–anticancer activity relationship of these compounds.ResultsCompound 6b shows the highest cytotoxic potency against all five cancer cell lines tested, with IC50 values ranging from 3.27±0.21 to 11.37±0.52 μM. We have also found that 6b displays higher selectivity than the etoposide except in the case of HL-60 cell line. The active compounds possess similar physicochemical properties: MSA > 900, %PSA < 20, ClogP > 2, MW > 700 Da, and RB > 10.ConclusionWe synthesized several glucoside derivatives of PPT and tested their cytotoxicity. Among them, compound 6b showed the highest cytotoxicity. Further studies including selectivity of active compounds have shown that the selectivity indexes of 6b are much greater than the etoposide except in the case of HL-60 cell line. The active compounds possessed similar physicochemical properties. This study indicates that active glucoside analogs of podophyllotoxin have potential as lead compounds for developing novel anticancer agents.

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“…Exemplo extremo de utilização dessa regra é fornecido por Kim e colaboradores 72 , que analisaram a atividade antimalarial em ratos de nada menos do que 646 compostos derivados de fenantrenos, quinolinas e piridinas (eq 19, em que não será mencionado o significado das variáveis citadas). Neste modelo foram incluídas 14 variáveis, número que certamente é justificado pela imensa quantidade de compostos analisados.…”

Section: Número De Variáveis Em Cada Modelounclassified

Proposição, validação e análise dos modelos que correlacionam estrutura química e atividade biológica

Gaudio¹,

Zandonade²

2001

Quím. Nova

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Recebido em 7/4/00; aceito em 15/12/00 PROPOSITION, VALIDATION AND ANALYSIS OF QSAR MODELS. The present paper aims to bring under discussion some theoretical and practical aspects about the proposition, validation and analysis of QSAR models based on multiple linear regression. A comprehensive approach for the derivation of extrathermodynamic equations is reviewed. Some examples of QSAR models published in the literature are analyzed and criticized.Keywords: quantitative structure-activity relationships; multiple linear regression; validation of QSAR models. Quim. Nova, Vol. 24, No. 5, 658-671, 2001. Divulgação INTRODUÇÃOEm sua sétima edição do ano de 1973, o Journal of Medicinal Chemistry publicou um artigo de autoria de Unger e Hansch 1 que é considerado por muitos como um marco no desenvolvimento de QSAR, abreviação em inglês para Relações Quantitativas entre Estrutura e Atividade. O artigo tornou-se célebre por estabelecer regras gerais para a elaboração e validação dos modelos matemáticos que correlacionam estrutura química e atividade biológica. A publicação desse artigo foi conseqüência da publicação anterior de dois outros artigos, em que seus autores apresentaram modelos matemáticos distintos para analisar a atividade biológica da mesma série de compostos.Tudo começou com o artigo de Hansch e Lien 2 , em que se analisou a atividade antiadrenérgica de vinte e dois compostos derivados da N,N-dimetil-α-bromo-feniletilamina (1), substituídos nas posições meta e para do anel fenila, cujos valores haviam sido determinados cinco anos antes 3 .desvio-padrão do modelo. Neste ponto cabe um esclarecimento. Optou-se por apresentar as equações citadas em sua forma original. Assim que o formato apropriado de apresentação dos modelos matemáticos de QSAR for mostrado (ver adiante), o leitor poderá comparar as diversas formas de apresentação já utilizadas ao longo do tempo. Em 1972, Cammarata 6 apresentou a eq 2 como alternativa para a representação da atividade dos compostos derivados da estrutura 1. Na eq 2, π m e σ m são as constantes lipofílica e eletrônica dos grupos químicos presentes na posição meta do anel fenila da estrutura 1 (X), r v p é o raio de van der Waals do substituinte na posição para (Y) e os números entre parênteses correspondem aos desvios-padrão dos coeficientes da equação.Os valores numéricos de R e s na eq 2 indicam que o modelo de Cammarata consegue explicar maior quantidade da variabilidade dos valores da atividade biológica do que o modelo representado pela eq 1. No entanto, deve-se levar em consideração que o segundo membro da eq 2 contém uma variável a mais do que a eq 1, o que certamente contribui para sua melhor qualidade.Em 1973, Unger e Hansch 1 reagiram ao modelo proposto por Cammarata, afirmando que o mesmo continha inconsistên-cias relativas às variáveis utilizadas para descrever a atividade biológica e de forma alguma apresentava embasamento bioquí-mico, o que o invalidava. Alguns dos argumentos citados foram: (a) o modelo não atribui efeito hidrofóbico aos substituintes presentes n...

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Quantitative structure-activity relationships in 1-aryl-2-(alkylamino)ethanol antimalarials

Cited by 37 publications

References 10 publications

The physicochemical approach to drug design and discovery (QSAR)

The physicochemical approach to drug design and discovery (QSAR)

<p>Glucoside Derivatives Of Podophyllotoxin: Synthesis, Physicochemical Properties, And Cytotoxicity</p>

Proposição, validação e análise dos modelos que correlacionam estrutura química e atividade biológica

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