Identification of substrates of P-Glycoprotein using in-silico methods

The ABC transporter superfamily is one of the largest and abundant families of proteins. It is a large group of proteins that transport a range of substances in cell systems. The ABC transporter P-glycoprotein (ABCB1, P-gp), a polyspecific protein has demonstrated its function as a transporter of hydrophobic drugs as well as transporting lipids, steroids and metabolic products. As well as this, previous studies have shown that P-gp is over expressed in cancerous tissues and plays a role in multidrug resistance. In this study, in-silico methods were used to dock a data set of compounds to P-glycoprotein structures available in the Protein data bank. Binding sites were defined using co-crystallised ligand structures of P-gp and docking energies were calculated using MOE. Statistical models were built to gain a better understanding of how compounds may interact with P-gp. The protein was able to bind to structurally different compounds and results indicate that LogP is the most important factor for drug binding to P-glycoprotein

QSAR models for the prediction of plasma protein binding

Introduction: The prediction of plasma protein binding (ppb) is of paramount importance in the pharmacokinetics characterization of drugs, as it causes significant changes in volume of distribution, clearance and drug half life. This study utilized Quantitative Structure - Activity Relationships (QSAR) for the prediction of plasma protein binding. Methods: Protein binding values for 794 compounds were collated from literature. The data was partitioned into a training set of 662 compounds and an external validation set of 132 compounds. Physicochemical and molecular descriptors were calculated for each compound using ACD labs/logD, MOE (Chemical Computing Group) and Symyx QSAR software packages. Several data mining tools were employed for the construction of models. These included stepwise regression analysis, Classification and Regression Trees (CART), Boosted trees and Random Forest. Results: Several predictive models were identified; however, one model in particular produced significantly superior prediction accuracy for the external validation set as measured using mean absolute error and correlation coefficient. The selected model was a boosted regression tree model which had the mean absolute error for training set of 13.25 and for validation set of 14.96. Conclusion: Plasma protein binding can be modeled using simple regression trees or multiple linear regressions with reasonable model accuracies. These interpretable models were able to identify the governing molecular factors for a high ppb that included hydrophobicity, van der Waals surface area parameters, and aromaticity. On the other hand, the more complicated ensemble method of boosted regression trees produced the most accurate ppb estimations for the external validation set. © 2013 by Tabriz University of Medical Sciences

Quantitative study of the structural requirements of phthalazine/quinazoline derivatives for interaction with human liver aldehyde oxidase

Aldehyde oxidase is a molybdenum-containing enzyme distributed throughout the animal kingdom. Although this enzyme is capable of metabolizing a wide range of aldehydes and N-heterocyclic compounds, there is no reported detailed study of physicochemical requirements of the enzyme-substrate interactions. The aim of this study, therefore, was to investigate quantitatively the relationships between the kinetic constants of aldehyde oxidase-catalyzed oxidation of some phthalazine and quinazoline derivatives (as substrates) and their structural parameters. Multiple regression and stepwise regression analyses showed that polarity of phthalazines (expressed as dipole moment μ, cohesive energy density δT and an indicator variable for hydrogen-bond acceptor ability of R1 substituent, HBA) had a negative effect on the enzyme activity (leading to the reduction of Vmax and increase of Km). Electron withdrawing substituents in the quinazoline series are favorable for interaction with the enzyme. This finding and also the relationships of 1/Km of phthalazines with the energy of the lowest unoccupied molecular orbital and log Vmax/logKm of phthalazines with degree of bonding of the two nitrogen atoms in the molecules are consistent with the mechanism of action. The reaction involves a nucleophilic attack on an electron-deficient sp2-hybridized carbon atom and formation of an epoxide intermediate following the disruption of the aromatic structure

Effect of OATP-binding on the prediction of biliary excretion

1.Biliary excretion of compounds is dependant on several transporter proteins for the active uptake of compounds from the blood into the hepatocytes. Organic anion-transporting polypeptides (OATPs) are some of the most abundant transporter proteins in the sinusoidal membrane and have been shown to have substrate specificity similar to the structural characteristics of cholephilic compounds. 2.In this study, we sought to use measures of OATP binding as predictors of biliary excretion in conjunction with molecular descriptors in a quantitative structure-activity relationship (QSAR) study. Percentage inhibitions of three subtypes of OATPs were used as surrogate indicators of OATP substrates. Several statistical modelling techniques were incorporated including classification and regression trees, boosted trees, random forest and multivariate adaptive regression splines (MARS) in order to first develop QSARs for the prediction of OATP inhibition of compounds. The predicted OATP percentage inhibition using selected models were then used as features of the QSAR models for the prediction of biliary excretion of compounds in rat. 3.The results indicated that incorporation of predicted OATP inhibition improves accuracy of biliary excretion models. The best result was obtained from a simple regression tree that used predicted OATP1B1 percentage inhibition at the root node of the tree

Liqui-pellet: the emerging next-generation oral dosage form which stems from liquisolid concept in combination with pelletization technology

In spite of the major advantages that the liquisolid technology offers, particularly in tackling poor bioavailability of poorly water-soluble drugs (i.e., BCS Class II drugs), there are a few critical drawbacks. The inability of a high liquid load factor, poor flowability, poor compactibility, and an inability to produce a high dose dosage form of a reasonable size for swallowing are major hurdles, hampering this technology from being commercially feasible. An attempt was therefore made to overcome these drawbacks whilst maintaining the liquisolid inherent advantages. This resulted in the emerging next generation of oral dosage forms called the liqui-pellet. All formulations were incorporated into capsules as the final product. Solubility studies of naproxen were conducted in different liquid vehicles, namely polyethylene glycol 200, propylene glycol, Tween 80, Labrafil, Labrasol, and Kolliphor EL. The scanning electron microscopy studies indicated that the liquid vehicle tends to reduce the surface roughness of the pellet. X-ray powder diffraction (XRPD) indicated no significant differences in the crystalline structure or amorphous content between the physical mixture and the liqui-pellet formulation. This was due to the presence of a high concentration of amorphous Avicel in the formulation which overshadowed the crystalline structure of naproxen in the physical mixtures. Flowability and dissolution tests confirmed that this next-generation oral dosage form has excellent flowability, whilst maintaining the typical liquisolid enhanced drug release performance in comparison to its physical mixture counterpart. The liqui-pellet also had a high liquid load factor of 1, where ~ 29% of the total mass was the liquid vehicle. This shows that a high liquid load factor can be achieved in a liqui-pellet without compromising flowability. Overall, the results showed that the poor flowability of a liquisolid formulation could be overcomed with the liqui-pellet, which is believed to be a major advancement into the commercial feasibility of the liquisolid concept

Optimising the release rate of naproxen liqui-pellet: a new technology for emerging novel oral dosage form

Liqui-pellet is a new dosage form stemming from pelletisation technology and concept from liquisolid technology. In spite of liqui- pellet overcoming a major hurdle in liquisolid technology through achieving excellent flow property with high liquid load factor, the formulation requires to be optimised in order to improve drug release rate. Liqui-pellets of naproxen containing Tween 80, Primojel, Avicel and Aerosil were extruded and spheronised. Flowability test confirmed that all liqui-pellet formulations have excellent-good flow property (Carr’s index between 3.9–11.17%), including liqui-pellets with a high liquid load factor of 1.52, where 38% of the total mass is co-solvent. This shows a relatively high liquid load factor can be achieved in liqui-pellet without compromising the flowability, which is one of the key novelty of this work. It was found that the improved drug release rate was due to the remarkably improved disintegration of the supposedly non-disintegrating microcrystalline-based pellet; the optimised liqui-pellet seems to explode into fragments in the dissolution medium. At pH 1.2, the optimised formulation had ~ 10% more drug release than non-optimised formulation after 2 h, and at pH 7.4, the drug release of the optimised pellet was nearing 100% at ~ 15 min, whereas the none- optimised pellet only achieved ~ 79% drug release after 2 h. DSC and XRPD indicated an increase in the dissolution rate could be due to molecularly dispersion of naproxen in the pellets. Overall results showed that liqui-pellet exhibited an enhanced drug release and the capacity for high liquid load factor whilst maintaining excellent flowability, rendering it a potentially commercially feasible drug delivery system

The effect of formulations and experimental conditions on in vitro human skin permeation: data from updated EDETOX database

In vitro methods are commonly used in order to estimate the extent of systemic absorption of chemicals through skin. Due to the wide variability of experimental procedures, types of skin and data analytical methods, the resulting permeation measures varies significantly between laboratories and individuals. Inter-laboratory and inter-individual variations with the in vitro measures of skin permeation lead to unreliable extrapolations to in vivo situations. This investigation aimed at a comprehensive assessment of the available data and development of validated models for in vitro skin flux of chemicals under various experimental and vehicle conditions. Following an exhaustive literature review, the human skin flux data were collated and combined with those from EDETOX database resulting in a dataset of a total of 536 flux reports. Quantitative structure-activity relationship techniques combined with data mining tools were used to develop models incorporating the effects of permeant molecular structure, properties of the vehicle, and the experimental conditions including the membrane thickness, finite/infinite exposure, skin pre-hydration and occlusion. The work resulted in statistically valid models for estimation of the skin flux from varying experimental conditions, including relevant real-world mixture exposure scenarios. The models indicated that the most prominent factors influencing flux values were the donor concentration, lipophilicity, size and polarity of the penetrant, and the melting and boiling points of the vehicle, with skin occlusion playing significant role in a non-linear way. The models will aid assessment of the utility of dermal absorption data collected under different conditions with broad implications on transdermal delivery research. © 2012 Elsevier B.V. All rights reserved

Enzastaurin inhibits ABCB1-mediated drug efflux independently of effects on protein kinase C signalling and the cellular p53 status

The PKCβ inhibitor enzastaurin was tested in parental neuroblastoma and rhabdomyosarcoma cell lines, their vincristine-resistant sub-lines, primary neuroblastoma cells, ABCB1-transduced, ABCG2-transduced, and p53-depleted cells. Enzastaurin IC50s ranged from 3.3 to 9.5 μM in cell lines and primary cells independently of the ABCB1, ABCG2, or p53 status. Enzastaurin 0.3125 μM interfered with ABCB1-mediated drug transport. PKCα and PKCβ may phosphorylate and activate ABCB1 under the control of p53. However, enzastaurin exerted similar effects on ABCB1 in the presence or absence of functional p53. Also, enzastaurin inhibited PKC signalling only in concentrations ≥ 1.25 μM. The investigated cell lines did not express PKCβ. PKCα depletion reduced PKC signalling but did not affect ABCB1 activity. Intracellular levels of the fluorescent ABCB1 substrate rhodamine 123 rapidly decreased after wash-out of extracellular enzastaurin, and enzastaurin induced ABCB1 ATPase activity resembling the ABCB1 substrate verapamil. Computational docking experiments detected a direct interaction of enzastaurin and ABCB1. These data suggest that enzastaurin directly interferes with ABCB1 function. Enzastaurin further inhibited ABCG2-mediated drug transport but by a different mechanism since it reduced ABCG2 ATPase activity. These findings are important for the further development of therapies combining enzastaurin with ABC transporter substrates

QSPR Modeling using Catalan Solvent and Solute Parameters

A área de correlação quantitativa entre estrutura e propriedade (QSPR) pode beneficiar-se de descritores moleculares que representam interações intermoleculares. Catalan desenvolveu um método de escalas solvatocrômicas para solventes que pode ser explorado para esta finalidade. Neste trabalho, escalas de solvente de Catalan foram usadas como descritores moleculares para o desenvolvimento de modelos QSPR, e para o cálculo de novos descritores de soluto para uso posterior em QSPR. As escalas Catalan para o solvente e os descritores de soluto derivados foram recentemente comparados com o método de descritores de Abraham, em termos da qualidade do QSPR desenvolvido. Os parâmetros Catalan para solventes, que mostraram uma correlação modesta com os correspondentes descritores de Abraham, mostraram-se bem sucedidos para modelar temperatura de fusão, temperatura de ebulição, ponto de ignição, índice de refração, tensão superficial, densidade e parâmetro de solubilidade dos solventes, com médias geométricas dos desvios relativos (GMRD) de 7,1, 6,6, 4,9, 3,8, 9,1, 6,0 e 4,2%, respectivamente. Os descritores do soluto foram obtidos a partir das equações de regressão entre a solubilidade de um soluto em diferentes solventes com um GMRD total de 30,0%. Os descritores de soluto obtidos desta maneira superam o modelo de solvatação geral de Abraham no cálculo de solubilidade em meio aquoso de 27 solutos de várias famílias químicas. Os descritores Catalan podem ser considerados como um recurso valioso para modelagem QSPR. The field of quantitative structure-property relationship (QSPR) can greatly benefit from molecular descriptors that particularly represent the intermolecular interactions. Catalan has developed a set of solvatochromic scales for solvents, which could be exploited for this purpose. In this work, Catalan solvent scales were explored as molecular descriptors for the development of QSPR models, and for the calculation of new solute descriptors for further use in QSPR. Catalan solvent scales and the newly derived solute descriptors were compared with the commonly used set of Abraham descriptors in terms of the quality of the developed QSPRs. Catalan solvent parameters, which showed modest correlation with the corresponding Abraham descriptors, proved to be successful in modeling melting point, boiling point, flash point, refractive index, surface tension, density, and solubility parameter of the solvents with geometric mean relative deviations (GMRD) of 7.1, 6.6, 4.9, 3.8, 9.1, 6.0, and 4.2%, respectively. The solute descriptors were obtained from regression equations between a solute's solubility in different solvents with an overall GMRD of 30.0%. The solute descriptors obtained in this way outperformed Abraham general solvation model in the calculation of aqueous solubility for 27 solutes of broad chemical ranges. It was concluded that Catalan descriptors can be regarded as a valuable resource for QSPR modeling