Molecular simulation as a computational pharmaceutics tool to predict drug solubility, solubilization processes and partitioning (original) (raw)
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J. Phys. Chem. B, 2011
The objectives of this study were (i) to develop a computational model based on molecular dynamics technique to predict the miscibility of indomethacin in carriers (polyethylene oxide, glucose, and sucrose) and (ii) to experimentally verify the in silico predictions by characterizing the drug-carrier mixtures using thermoanalytical techniques. Molecular dynamics (MD) simulations were performed using the COMPASS force field, and the cohesive energy density and the solubility parameters were determined for the model compounds. The magnitude of difference in the solubility parameters of drug and carrier is indicative of their miscibility. The MD simulations predicted indomethacin to be miscible with polyethylene oxide and to be borderline miscible with sucrose and immiscible with glucose. The solubility parameter values obtained using the MD simulations values were in reasonable agreement with those calculated using group contribution methods. Differential scanning calorimetry showed melting point depression of polyethylene oxide with increasing levels of indomethacin accompanied by peak broadening, confirming miscibility. In contrast, thermal analysis of blends of indomethacin with sucrose and glucose verified general immiscibility. The findings demonstrate that molecular modeling is a powerful technique for determining the solubility parameters and predicting miscibility of pharmaceutical compounds.
Journal of Physical Chemistry B, 2001
The expanded ensemble method, developed to calculate solvation free energies, is applied to calculate octanol/ water partition coefficients P for some organic drug-related molecules and compared with experimental results. The experimental log P results were obtained by a miniaturized vial procedure using liquid chromatography with UV for quantification. The expanded ensemble technique, implemented within molecular dynamics scheme, is adapted to treat molecules of arbitrary size and type. For octanol, both all-atom and united atom models are evaluated. The solvation free energy of the organic solute molecules is found to be sensitive to the used sets of partial charges on the atoms in polar groups, particularly in water but also in the saturated octanol phase. Although this effect partially cancels out in the calculated partition coefficients, the charges obtained from ab initio Mulliken population analysis give consistently larger log P values than those obtained in simulations with the larger empirical atomic charges included in the CHARMM force field. In general, calculated log P turned out to be systematically higher than those measured experimentally. The possibility of improving potential models for the solutes in water and oil phase, respectively, is discussed.
The Journal of Chemical Physics, 2019
A method to compute solubilities for molecular systems using atomistic simulations, based on an extension of the Einstein crystal method, has recently been presented [Li et al., J. Chem. Phys. 146, 214110 (2017)]. This methodology is particularly appealing to compute solubilities in cases of practical importance including, but not limited to, solutions where the solute is sparingly soluble and molecules of importance for the pharmaceutical industry, which are often characterized by strong polar interactions and slow relaxation time scales. The mathematical derivation of this methodology hinges on a factorization of the partition function which is not necessarily applicable in the case of a system subject to holonomic molecular constraints. We show here that, although the mathematical procedure to derive it is slightly different, essentially the same mathematical relation for calculating the solubility can be safely applied for computing the solubility of systems subject to constraints, which are the majority of the systems used for practical molecular simulations.
Journal of Computational Chemistry, 1995
The point-chart approximation of the Miertus-Scrocco-Tomasi solvation model (MST-PC) based on a continuum representation of the solvent has been incorporated in force field calculations. Application in molecular mechanics (MM) involves conformational equilibria in solution: rotational isomers of ethylene glycol (I), 1,2-difluoroethane (10, fluoroacetic acid (110, and representative conformers of macrocyclic receptors such as 18-crown-6 (IV), cryptand 2.2.2 (V), and t-butyl-calix[4]arenetetraamide (VI). Assessment of the MST-PC results is based on the comparison with ab initio reactive field calculations (for I-111), with the continuum model of Still (W. C. Still et al., J.
Journal of Molecular Liquids, 2017
In this work, solubility of four Active Pharmaceutical Ingredients (APIs) including Butyl Paraben, Fenoxycarb, Fenofibrate and Risperidone were predicted using Hansen Flory Huggins model using two different scenarios. In the first method, activity coefficient of APIs were obtained through fitting the experimental activity coefficients of solvents at particular temperature of 293 K, then components solubility in entire temperature range of study was predicted. In the second scenario, the model parameters were adjusted using experimental data of two selected solvents, then components solubility were predicted in other solvents. In order to check the physical meanings of obtained values, Molecular Dynamic (MD) simulations was utilized and the results were compared. Finally the predictive capabilities of two Hansen Flory Huggins models were compared to temperature-dependent NRTL-SAC model.
Molecular Thermodynamic Modeling of Mixed Solvent Solubility
Industrial & Engineering Chemistry Research, 2010
A method based on statistical mechanical fluctuation solution theory for composition derivatives of activity coefficients is employed for estimating dilute solubilities of 11 solid pharmaceutical solutes in nearly 70 mixed aqueous and nonaqueous solvent systems. The solvent mixtures range from nearly ideal to strongly nonideal. The database covers a temperature range from 293 to 323 K. Comparisons with available data and other existing solubility methods show that the method successfully describes a variety of observed mixed solvent solubility behaviors using solute-solvent parameters from global regression of ternary data as well as predictions based on pure solvent solubilities with an average error of about 10% on mole fractions.
Molecular simulations in drug delivery: Opportunities and challenges
WIREs Computational Molecular Science, 2018
Molecular simulations are promising tools for in silico design of drug delivery formulations, as they provide a prediction of formulation properties prior to synthesis thus minimizing the need for in vitro and in vivo experimentation. The detailed molecular insight obtained by these simulations is precious and often beyond the reach of sophisticated experimental facilities. Although initially limited to the prediction of single-molecule behavior (e.g., drug orientation in a bilayer), gradual advances in computing speed and efficient simulation approaches have made it feasible to employ these methods for phenomena occurring at substantially large length and time scales (e.g., carrier-drug complexation) with modest computational cost and resources. We present a nonmathematical review of molecular simulation methods and their applications in drug delivery, with special emphasis on the use of atomistic and coarse-grained Monte Carlo (MC) and molecular dynamics (MD) methods and excluding the drug docking studies used in drug discovery. Current capabilities and problems associated with the use of these methods in the context of drug delivery are highlighted, along with a discussion of representative applications of molecular simulations in drug delivery. We conclude that while molecular simulations are expected to play a central role in the future of drug delivery field, we require a concerted effort of computational scientists, experimentalists, and industry personnel working on drug delivery to identify specific areas where these simulations can be especially useful.
Experimental and computational screening models for prediction of aqueous drug solubility
Pharmaceutical Research, 2002
To devise experimental and computational models to predict aqueous drug solubility. Methods. A simple and reliable modification of the shake flask method to a small-scale format was devised, and the intrinsic solubilities of 17 structurally diverse drugs were determined. The experimental solubility data were used to investigate the accuracy of commonly used theoretical and semiexperimental models for prediction of aqueous drug solubility. Computational models for prediction of intrinsic solubility, based on lipophilicity and molecular surface areas, were developed. Results. The intrinsic solubilities ranged from 0.7 ng/mL to 6.0 mg/ mL, covering a range of almost seven log 10 units, and the values determined with the new small-scale shake flask method agreed well with published solubility data. Solubility data computed with established theoretical models agreed poorly with the experimentally determined solubilities, but the correlations improved when experimentally determined melting points were included in the models. A new, fast computational model based on lipophilicity and partitioned molecular surface areas, which predicted intrinsic drug solubility with a good accuracy (R 2 of 0.91 and RMSE tr of 0.61) was devised.
Advanced Drug Delivery Reviews, 1997
Experimental and computational approaches to estimate solubility and permeability in discovery and development settings are described. In the discovery setting 'the rule of 5' predicts that poor absorption or permeation is more likely when there are more than 5 H-bond donors, 10 H-bond acceptors, the molecular weight (MWT) is greater than 500 and the calculated Log P (CLogP) is greater than 5 (or MlogP . 4.15). Computational methodology for the rule-based Moriguchi Log P (MLogP) calculation is described. Turbidimetric solubility measurement is described and applied to known drugs. High throughput screening (HTS) leads tend to have higher MWT and Log P and lower turbidimetric solubility than leads in the pre-HTS era. In the development setting, solubility calculations focus on exact value prediction and are difficult because of polymorphism. Recent work on linear free energy relationships and Log P approaches are critically reviewed. Useful predictions are possible in closely related analog series when coupled with experimental thermodynamic solubility measurements.
Calculation of drug-like molecules solubility using predictive activity coefficient models
Fluid Phase Equilibria, 2012
The A-UNIFAC, UNIFAC, and NRTL-SAC models are used to predict solubility in pure solvents of a set of drug-like molecules. To apply A-UNIFAC, a new set of residual interaction parameters between the ACOH group and six other groups had to be estimated. The solute model parameters of NRTL-SAC were also estimated for this set of molecules. NRTL-SAC showed better performance at 298.15 K, with an average absolute deviation of 37.6%. Solubility dependence with temperature was also studied: all models presented average deviations around 40%. In general, there is an improvement given by the A-UNIFAC over the UNIFAC in aqueous systems, proving the importance of taking association into account.