971 resultados para PARTITION-COEFFICIENT


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The n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter for drug discovery, design, and development. Here, we present a physics-based approach that shows a strong linear correlation between the computed solvation free energy in implicit solvents and the experimental log Po/w on a cleansed data set of more than 17,500 molecules. After internal validation by five-fold cross-validation and data randomization, the predictive power of the most interesting multiple linear model, based on two GB/SA parameters solely, was tested on two different external sets of molecules. On the Martel druglike test set, the predictive power of the best model (N = 706, r = 0.64, MAE = 1.18, and RMSE = 1.40) is similar to six well-established empirical methods. On the 17-drug test set, our model outperformed all compared empirical methodologies (N = 17, r = 0.94, MAE = 0.38, and RMSE = 0.52). The physical basis of our original GB/SA approach together with its predictive capacity, computational efficiency (1 to 2 s per molecule), and tridimensional molecular graphics capability lay the foundations for a promising predictor, the implicit log P method (iLOGP), to complement the portfolio of drug design tools developed and provided by the SIB Swiss Institute of Bioinformatics.

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The rationale of this study was to investigate molecular flexibility and its influence on physicochemical properties with a view to uncovering additional information on the fuzzy concept of dynamic molecular structure. Indeed, it is now known that computed molecular interaction fields (MIFs) such as molecular electrostatic potentials (MEPs) and lipophilicity potentials (MLPs) are conformation-dependent, as are dipole moments. A database of 125 compounds was used whose conformational space was explored, while conformation-dependent parameters were computed for each non-redundant conformer found in the conformational space of the compounds. These parameters were the virtual log P (log P(MLP), calculated by a MLP approach), the apolar surface area (ASA), polar surface area (PSA), and solvent-accessible surface (SAS). For each compound, the range taken by each parameter (its property space) was divided by the number of rotors taken as an index of flexibility, yielding a parameter termed 'molecular sensitivity'. This parameter was poorly correlated with others (i.e., it contains novel information) and showed the compounds to fall into two broad classes. 'Sensitive' molecules are those whose computed property ranges are markedly sensitive to conformational effects, whereas 'insensitive' (in fact, less sensitive) molecules have property ranges which are comparatively less affected by conformational fluctuations. A pharmacokinetic application is presented.

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In this paper, we report a new method based on supercritical carbon dioxide (scCO(2)) to fill and distribute the porous magnetic nanoparticles with n-octanol in a homogeneous manner. The high solubility of n-octanol in scCO(2) and high diffusivity and permeability of the fluid allow efficient delivery of n-octanol into the porous magnetic nanoparticles. Thus, the n-octanol-loaded magnetic nanoparticles can be readily dispersed into aqueous buffer (pH 7.40) to form a homogenous suspension consisting of nano-sized n-octanol droplets. We refer this suspension as the n-octanol stock solution. The n-octanol stock solution is then mixed with bulk aqueous phase (pH 7.40) containing an organic compound prior to magnetic separation. The small-size of the particles and the efficient mixing enable a rapid establishment of the partition equilibrium of the organic compound between the solid supported n-octanol nano-droplets and the bulk aqueous phase. UV-vis spectrophotometry is then applied to determine the concentration of the organic compound in the aqueous phase both before and after partitioning (after magnetic separation). As a result, log D values of organic compounds of pharmaceutical interest determined by this modified method are found to be in excellent agreement with the literature data. (c) 2006 Elsevier B.V. All rights reserved.

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Partition behavior of adenosine and guanine mononucleotides was examined in aqueous dextran-polyethylene glycol (PEG) and PEG-sodium sulfate two-phase systems. The partition coefficients for each series of mononucleotides were analyzed as a functions of the number of phosphate groups and found to be dependent on the nature of nucleic base and on the type of \ATPS\ utilized. It was concluded that an average contribution of a phosphate group into logarithm of partition coefficient of a mononucleotide cannot be used to estimate the difference between the electrostatic properties of the coexisting phases of ATPS. The data obtained in this study were considered together with those for other organic compounds and proteins reported previously, and the linear interrelationship between logarithms of partition coefficients in dextran-PEG, PEG-Na2SO4 and PEG-Na2SO4-0.215 M NaCl (all in 0.01 M Na- or K/Na-phosphate buffer, pH 7.4 or 6.8) was established. Similar relationship was found for the previously reported data for proteins in Dex-PEG, PEG-600-Na2SO4, and PEG-8000-Na2SO4 ATPS. It is suggested that the linear relationships of the kind established in \ATPS\ may be observed for biological properties of compounds as well.

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A novel and generic miniaturization methodology for the determination of partition coefficient values of organic compounds in noctanol/water by using magnetic nanoparticles is, for the first time, described. We have successfully designed, synthesised and characterised new colloidal stable porous silica-encapsulated magnetic nanoparticles of controlled dimensions. These nanoparticles absorbing a tiny amount of n-octanol in their porous silica over-layer are homogeneously dispersed into a bulk aqueous phase (pH 7.40) containing an organic compound prior to magnetic separation. The small size of the particles and the efficient mixing allow a rapid establishment of the partition equilibrium of the organic compound between the solid supported n-octanol nano-droplets and the bulk aqueous phase. UV-vis spectrophotometry is then applied as a quantitative method to determine the concentration of the organic compound in the aqueous phase both before and after partitioning (after magnetic separation). log D values of organic compounds of pharmaceutical interest (0.65-3.50), determined by this novel methodology, were found to be in excellent agreement with the values measured by the shake-flask method in two independent laboratories, which are also consistent with the literature data. It was also found that this new technique gives a number of advantages such as providing an accurate measurement of log D value, a much shorter experimental time and a smaller sample size required. With this approach, the formation of a problematic emulsion, commonly encountered in shake-flask experiments, is eliminated. It is envisaged that this method could be applicable to the high throughput log D screening of drug candidates. (c) 2005 Elsevier B.V. All rights reserved.

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In the present work, a new approach for the determination of the partition coefficient in different interfaces based on the density function theory is proposed. Our results for log P(ow) considering a n-octanol/water interface for a large super cell for acetone -0.30 (-0.24) and methane 0.95 (0.78) are comparable with the experimental data given in parenthesis. We believe that these differences are mainly related to the absence of van der Walls interactions and the limited number of molecules considered in the super cell. The numerical deviations are smaller than that observed for interpolation based tools. As the proposed model is parameter free, it is not limited to the n-octanol/water interface.

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Stratum corneum (SC) desorption experiments have yielded higher calculated steady-state fluxes than those obtained by epidermal penetration studies. A possible explanation of this result is a variable diffusion or partition coefficient across the SC. We therefore developed the diffusion model for percutaneous penetration and desorption to study the effects of either a variable diffusion coefficient or variable partition coefficient in the SC over the diffusion path length. Steady-state flux, lag time, and mean desorption time were obtained from Laplace domain solutions. Numerical inversion of the Laplace domain solutions was used for simulations of solute concentration-distance and amount penetrated (desorbed)-time profiles. Diffusion and partition coefficients heterogeneity were examined using six different models. The effect of heterogeneity on predicted flux from desorption studies was compared with that obtained in permeation studies. Partition coefficient heterogeneity had a more profound effect on predicted fluxes than diffusion coefficient heterogeneity. Concentration-distance profiles show even larger dependence on heterogeneity, which is consistent with experimental tape-stripping data reported for clobetasol propionate and other solutes. The clobetasol propionate tape-stripping data were most consistent with the partition coefficient decreasing exponentially for half the SC and then becoming a constant for the remaining SC. (C) 2004 Wiley-Liss, Inc.

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Peptides are of great therapeutic potential as vaccines and drugs. Knowledge of physicochemical descriptors, including the partition coefficient P (commonly expressed in logarithm form: logP), is useful for screening out unsuitable molecules and also for the development of predictive Quantitative Structure-Activity Relationships (QSARs). In this paper we develop a new approach to the prediction of LogP values for peptides based on an empirical relationship between global molecular properties and measured physical properties. Our method was successful in terms of peptide prediction (total r2 = 0.641). The final model consisted of 5 physicochemical descriptors (molecular weight, number of single bonds, 2D-VDW volume, 2D-VSA hydrophobic and 2D-VSA polar). The approach is peptide specific and its predictive accuracy was high. Overall, 67% of the peptides were able to be predicted within +/-0.5 log units from the experimental values. Our method thus represents a novel prediction method with proven predictive ability.