Correlation of blood–brain penetration using structural descriptors

Katritzky, Alan R.; Kuanar, Minati; Slavov, Svetoslav; Dobchev, Dimitar A.; Fara, Dan C.; Karelson, Mati; Acree, William E.; Соловьев, В.П.; Varnek, Alexandre

doi:10.1016/j.bmc.2006.03.012

Cited by 78 publications

(62 citation statements)

References 68 publications

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“…Nevertheless, the model presented in this study is comparable or better than other published 2D-QSAR BBB models and show similar descriptors used by other authors. (Norinder et al, 2002;Katritzky et al, 2006;van Damme et al, 2008;Iyer et al, 2002;Konovalov et al, 2007;Subramanian et al, 2003;Zhao et al, 2007;Zhang et al, 2008;Narayanan et al, 2005;Young et al, 1988;Abraham, 2004;Goodwin et al, 2005). These findings can help future decisions about which groups are favorable or otherwise for CNS entry by BBB permeation, based on the physicochemical properties evaluated here.…”

Section: Resultsmentioning

confidence: 99%

“…The experimental logBB values were assessed using animal models and synthesized radio-labeled compounds. Often, this measure is based on the degree of BBB penetration, defined as the ratio of the steady-state molar concentration of the drug molecule (radio-labeled) in the brain and in the blood (Katritzky et al, 2006). The logBB values are given in Table 1, comprising the dependent variables of this QSPR analysis.…”

Section: Methodsmentioning

confidence: 99%

“…In Equation 1, C brain and C blood are the equilibrium concentrations of a molecule in the brain and the blood, respectively (Katritzky et al, 2006). However, this experimental determination is time and cost consuming, preventing extended applications.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, computerassisted drug design methodologies (CADD), such as quantitative structure-property and/or structure-activity relationship studies (QSPR and QSAR, respectively), may help to estimate biological data, reducing synthetic steps, predicting pharmacokinetic and pharmacodynamic profiles, constituting an important tool in the design and development of new drugs and novel leads (Katritzky et al, 2006). A literature review reported several studies, carried out on a number of different chemical structures, and in which 2D and 3D QSPR models have been proposed to predict logBB values (Katritzky et al, 2006;Van Damme et al, 2008;Iyer et al, 2002;Konovalov et al, 2007;Subramanian et al, 2003;Zhao et al, 2007;Zhang et al, 2008;Narayanan et al, 2005). Some of these models show a correlation between logBB and some physicochemical parameters, such as molecular refractivity (MR), molecular volume (V), acid ionization constant (K a and pK a ), thermodynamic parameters (solvation energy, etc.…”

Section: Introductionmentioning

confidence: 99%

“…If the drug cannot cross the BBB, no biological effect in the CNS is observed. This penetration is also a concern in the development of other classes of drugs, for which penetration through the BBB could result in toxicity due to undesirable effects on nervous tissues (Li et al, 2005;Katritzky et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

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A 2D-QSPR approach to predict blood-brain barrier penetration of drugs acting on the central nervous system

Sá

Pasqualoto

Rangel-Yagui

2010

Braz. J. Pharm. Sci.

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Drugs acting on the central nervous system (CNS) have to cross the blood-brain barrier (BBB) in order to perform their pharmacological actions. Passive BBB diffusion can be partially expressed by the blood/ brain partition coefficient (logBB). As the experimental evaluation of logBB is time and cost consuming, theoretical methods such as quantitative structure-property relationships (QSPR) can be useful to predict logBB values. In this study, a 2D-QSPR approach was applied to a set of 28 drugs acting on the CNS, using the logBB property as biological data. The best QSPR model [n = 21, r = 0.94 (r² = 0.88), s = 0.28, and Q² = 0.82] presented three molecular descriptors: calculated n-octanol/water partition coefficient (ClogP), polar surface area (PSA), and polarizability (α). Six out of the seven compounds from the test set were well predicted, which corresponds to good external predictability (85.7%). These findings can be helpful to guide future approaches regarding those molecular descriptors which must be considered for estimating the logBB property, and also for predicting the BBB crossing ability for molecules structurally related to the investigated set.Uniterms: Two-dimensional quantitative structure-property relationships (2D-QSPR). Calculated n-octanol/water partition coefficient (ClogP). Blood-brain barrier. Benzodiazepines.Fármacos que atuam no sistema nervoso central (SNC) devem atravessar a barreira hematoencefálica (BHE) para exercerem suas ações farmacológicas. A difusão passiva através da BHE pode ser parcialmente expressa pelo coeficiente de partição entre os compartimentos encefálico e sanguíneo (logBB, brain/blood partition coefficient). Considerando-se que a avaliação experimental de logBB é dispendiosa e demorada, métodos teóricos como estudos das relações entre estrutura química e propriedade (QSPR, Quantitative Structure-Property Relationships) podem ser utilizados na previsão dos valores de logBB. Neste estudo, uma abordagem de QSPR-2D foi aplicada a um conjunto de 28 moléculas com ação central, usando logBB como propriedade biológica. O melhor modelo de QSPR [n = 21, r = 0,94 (r² = 0,88), s = 0,28 e Q² = 0,82] apresentou três descritores moleculares: o coeficiente calculado de partição n-octanol/água (ClogP), área de superfície polar (PSA) e polarizabilidade (α). Seis dos sete compostos do conjunto de avaliação foram bem previstos pelo modelo, o que corresponde a um bom poder de previsão externa (85,7%). Os resultados obtidos podem auxiliar de forma relevante em estudos futuros, orientando quais descritores moleculares devem ser considerados para estimar logBB e prever a passagem através da BHE de moléculas estruturalmente relacionadas às do conjunto investigado. Unitermos:Relações quantitativas bidimensionais entre estrutura química e propriedade (2D-QSPR). Coeficiente calculado de partição n-octanol/água (ClogP). Barreira hematoencefálica. Benzodiazepínicos.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A 2D-QSPR approach to predict blood-brain barrier penetration of drugs acting on the central nervous system

Sá

Pasqualoto

Rangel-Yagui

2010

Braz. J. Pharm. Sci.

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Quantitative Structure‐Activity Relationships and Computational Methods in Drug Discovery

Balaban

2016

Encyclopedia of Analytical Chemistry

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Among the various methods for finding new medicinal drugs, the approach using molecular descriptors for quantitative structure–activity relationships (QSAR) is described in more detail, after a brief historical introduction. Starting with Corwin Hansch's observation that for many organic compounds their biological activities can often be correlated with their lipophilicity (octanol–water partition coefficients), which in turn may be approximated by computational approaches, chemical structures proved to be the early key to drug design. How can one encode discrete chemical structures into numerical values that may then be compared with biological activities that are measured by continuous scales? One well‐working tool uses topological indices (TIs) that are graph‐theoretical invariants associated with the hydrogen‐depleted constitutional formulas. Several examples are provided evidencing that this pathway proved to be successful. For three‐dimensional (3D) chemical structures, more sophisticated theoretical methods (such as CoMFA) had to be implemented. Nowadays, powerful synthetic and analytical methods involving combinatorial chemistry and high‐throughput screening on one hand, together with refined computational approaches, try to lower the cost of each new medicinal drug, which may reach one billion US dollars.

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Insight into the Functional and Structural Properties of 3‐Arylcoumarin as an Interesting Scaffold in Monoamine Oxidase B Inhibition

et al. 2014

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The design, synthesis, pharmacological evaluation, and theoretical studies of a new series of halogenated 3-arylcoumarins were carried out with the aim of finding new structural and biological features. This series displays several alkyl, hydroxy, halogen, and/or alkoxy groups in both benzene rings of the 3-arylcoumarin scaffold. Most of the compounds studied show high affinity and selectivity for the human monoamine oxidase B (hMAO-B) isoenzyme, with IC50 values in the low nanomolar and picomolar range. Most of the evaluated compounds display higher MAO-B inhibitory activity and selectivity than selegiline (the reference compound). Coumarin 12 (3-(3-bromophenyl)-6-methylcoumarin) is the most active compound (IC50 =134 pM), being 140-fold more active than selegiline and showing the highest specificity for hMAO-B. To better understand the structure-activity relationships, docking experiments were carried out on human monoamine oxidase (A and B) structures. Finally, the prediction of passive blood-brain partitioning, based on in silico derived physicochemical descriptors, was performed.

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Correlation of blood–brain penetration using structural descriptors

Cited by 78 publications

References 68 publications

A 2D-QSPR approach to predict blood-brain barrier penetration of drugs acting on the central nervous system

A 2D-QSPR approach to predict blood-brain barrier penetration of drugs acting on the central nervous system

Quantitative Structure‐Activity Relationships and Computational Methods in Drug Discovery

Insight into the Functional and Structural Properties of 3‐Arylcoumarin as an Interesting Scaffold in Monoamine Oxidase B Inhibition

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