Computational Models of the Intestinal Environment. 3. The Impact

Article pubs.acs.org/molecularpharmaceutics

Computational Models of the Intestinal Environment. 3. The Impact of Cholesterol Content and pH on Mixed Micelle Colloids Estelle J. A. Suys,‡,§ Dallas B. Warren,‡ Christopher J. H. Porter,‡,§ Hassan Benameur,∥ Colin W. Pouton,*,‡ and David K. Chalmers*,† †

Medicinal Chemistry, ‡Drug Delivery, Disposition and Dynamics, and §ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, Monash Institute of Pharmaceutical Sciences, Monash University, 381 Royal Parade Parkville, Victoria 3052, Australia ∥ Capsugel Research & Development, Parc d’Innovation, Strasbourg, France S Supporting Information *

ABSTRACT: In this study, we use molecular dynamics (MD) and experimental techniques (nephelometry and dynamic light scattering) to investigate the influence of cholesterol content and pH on the colloidal structures that form in the gastrointestinal (GI) tract upon lipid digestion. We demonstrate that the ionization state of the molecular species is a primary driver for the selfassembly of aggregates formed by model bile and therefore should be considered when performing in silico modeling of colloidal drug delivery systems. Additionally, the incorporation of physiological concentrations of cholesterol within the model systems does not affect size, number, shape, or dynamics of the aggregates to a significant degree. The MD data shows a reduction in aggregate size with increasing pH, a preference for glycodeoxycholate (GDX) to occupy the aggregate surface, and that the mixed micellar aggregates are oblate spheroids (disc-like). The results obtained assist in understanding the process by which pH and cholesterol influence self-assembly of mixed micelles within the GI tract. The MD approach provides a platform for investigation of interactions of drugs and formulation excipients with the endogenous contents of the GI tract. KEYWORDS: bile, gastrointestinal, mixed micelle, colloids, molecular dynamics, phase behavior, ternary phase diagram, digested phospholipid, bile salts, oleic acid, cholesterol, pH, dynamic light scattering, nephelometry

■

INTRODUCTION The evanescent phases formed during lipid digestion play a significant role in drug solubilization and trafficking within the gastrointestinal (GI) tract, and markedly impact the overall performance of oral formulations. Poorly water-soluble drugs (PWSDs) require these colloidal phases to maintain drug solubilization and enable absorption from the GI tract into the systemic circulation.1 A better understanding of the factors that enhance the solubilization of PWSDs within the GI tract can provide important information to guide the development of improved drug formulations. There is therefore a need for wellcharacterized in vitro models that reproduce the key features of the GI environment. Further, there is much to be gained from closely coupled computational models that can help us to understand the physicochemical behavior of drugs within the GI environment. The development of such models is a growing area of research.2−8 The intestinal secretions from the gallbladder and pancreas consist of bile salts (67% w/w), phospholipids (22% w/w, © XXXX American Chemical Society

primarily phosphatidylcholines, PC), and cholesterol (4% w/ w), accompanied by small amounts of inorganic ions, proteins, and pigments.9−11 The most abundant constituents of bile are glycine- and taurine-conjugated bile salts, which have strong surfactant properties.12 Bile salts aggregate spontaneously in aqueous environments and function as endogenous solubilizers for sparingly soluble lipid digestion products, i.e., fatty acids (FA) and monoglycerides, forming mixed micellar and/or vesicular species.10 The bile salts thereby promote lipid digestion and absorption within the small intestine. It has become increasingly apparent that digestion by pancreatic enzymes changes the properties of luminal content. In vitro lipolysis experiments show that digestion of PC by pancreatic lipases is rapid and that the hydrolysis products Received: May 29, 2017 Revised: September 14, 2017 Accepted: September 20, 2017

A

DOI: 10.1021/acs.molpharmaceut.7b00446 Mol. Pharmaceutics XXXX, XXX, XXX−XXX

Article

Molecular Pharmaceutics quickly become more abundant than undigested phospholipid within the intestinal colloids.13 As a result, the major components of GI aggregates are bile salts, lyso-phosphatidylcholine (LPC), and FA, which are responsible for solubilization of PWSDs in the gut.14 Ternary systems consisting of dilute mixtures of bile salts, long chain PC, and water are commonly used as representative simplified model systems for fasted human bile.15,16 Early experimental work on the water−phospholipid−bile salt−cholesterol quaternary system investigated phase behavior and determined the micellar zone of cholesterol solubility.17−21 More recently, a variety of techniques have been utilized to study the self-assembly of bile components including: microscopic examination,15,22,23 small-angle neutron and X-ray scattering,24−26 laser light scattering,27,28 and NMR spectroscopy.29,30 In addition, molecular dynamics (MD) simulation has become an important tool for the study of the microscopic properties of biological systems that are difficult or impossible to probe experimentally. By delivering atomistic-scale models, MD enables the detailed investigation of molecular interactions and the dynamic properties of physiologically relevant structures. A pioneering paper by Marrink and Mark investigated the structure of ternary and quaternary systems using MD.31 Although this work provided insight into the structure of colloids present in a quaternary system, the simulations did not include different ionization states of titratable residues, used undigested phospholipid, and modeled only a single aggregate within the simulation cell. In the past decade, modeling has been extended from single micelles to more complex systems, and multiple MD studies have explored gut processes, including modeling of the spontaneous aggregation of bile salts in water,32−34 the nature of bile salt− PC mixed micelles or vesicles,31,35,36 and the fate of drugs in lipid-based formulations,37 generally providing good agreement with experimental observations. The recent work of Birru et al.38 demonstrated that the use of digested phospholipid, rather that the undigested species, resulted in more micelle-like colloidal structures, in agreement with the colloids present in the fasted state simulated human intestinal fluids.23 In the same paper, the impact of fatty acid ionization on the phase behavior of digested bile was explored, demonstrating that fatty acid ionization played a significant role in the micelle formation. Cholesterol is an important factor in the biochemical milieu; it is a precursor to a variety of hormones and to the bile acids and is an important component of membranes, where it modulates membrane biophysical properties.39 The impact of cholesterol incorporation into bile colloidal complexes has not yet been explored in a satisfactory manner. We have previously reported model bile systems that omit cholesterol,37,38 and we here extend this work to evaluate the behavior of cholesterol within bile and to establish more complete model systems. Additionally, the current work investigates the impact of pH changes on bile. In light of this, the objectives of this study are two-fold. The first objective is to examine the influence of cholesterol addition and pH variation over a wide range on the phase behavior model digested bile system (GDX, LPC, and oleic acid, OA) or the capacity of GDX to solubilize endogenous lipid products in silico (Figure 1). The second is to complement the MD study by identifying experimentally the phase boundary at biorelevant pH between micellar and vesicular species using dynamic light scattering (DLS) and nephelometry.

Figure 1. Pure components used to model digested bile in the MD simulations. Asterisks indicate the reference atoms used for the calculations of SDFs around GDX (red) and cholesterol (blue).

■

METHODS MD Simulations. Molecular dynamics simulations were performed using GROMACS40 version 5.0.4. The total computation time required for the simulations presented within this study was approximately 750,000 CPU hours (IBM Blue Gene/Q and x86 clusters). Isotropic periodic boundary conditions were applied to cubic simulation cells to emulate an infinite system. Simulations were conducted with the Verlet cutoff scheme41 using a cutoff distance of 1.4 nm applied for short-range nonbonded forces (Coulombic and vdW interactions), beyond which the electrostatic effects were treated by the particle mesh Ewald summation method using a 3D FFT with a grid spacing of 0.12 nm, interpolation order of 4, and relative strength of Ewald-shifted direct potential42 of 1 × 10−5. The isothermal−isobaric or NPT ensemble (constant number of particles, pressure, and temperature) was used. All the systems were represented by the GROMOS 53A6 unitedatom force field.43 The cis double bond in oleic acid (OA) and sodium oleate (OLAT) was built using the dihedral parameters developed by Bachar et al.36,44,45 The rigid simple point charge (SPC) water model was used. Water molecules were constrained using the SETTLE algorithm,46 while solute bond lengths were constrained by the LINCS algorithm.47 A 5 fs time step for the production run was enabled by increasing the mass of the polar hydrogen atoms by a factor of 4 while subtracting this mass increase from the bonded heavy atoms to conserve the total molecule mass, as commonly used in MD simulations.2,31,36,48 The initial system geometries were generated by randomly placing molecules within the simulation cell using the script random_box from the Silico package v1.01.49 The compositions of the simulated systems were chosen to reflect the conventionally reported content of human bile, being approximately 90:10% w/w water/solutes.16 Both intestinal bile fluid models represent systems after rapid digestion of the phospholipid 1palmitoyl-2-oleoyl-sn-glycerol-3-phosphocholine (POPC) by phospholipase A2, resulting in LPC and OA in a 1:1 molar ratio. Simulations without cholesterol used a molar ratio of 4:1 bile salt (GDX) to phospholipid (LPC + OA).50 Simulations containing cholesterol used a ratio of 16:4:128,51 for bile salt, digested phospholipid, and cholesterol. The number of lipid molecules in each protonation state at a specific pH in the simulation was calculated based on the molecular intrinsic pKa (that of the monomeric form in free solution) (see Supporting Information, Figure S1). Water molecules were added to the B


Article

Molecular Pharmaceutics system, and counterions were included to generate systems with a zero net charge. MD trajectories were analyzed using programs distributed as part of the GROMACS 5.0.4 software package, unless otherwise stated. The radii of gyration about the principal axes of an aggregate were computed with gmx gyrate. The principal radii of gyration are calculated by taking the squared radius of gyration tensor of each aggregate. Since the gyration tensor is a symmetric 3 × 3 matrix, a Cartesian coordinate system can be found, where the axes are chosen such that the diagonal elements are ordered (rx > ry > rz). Thus, analyzing the principal radii of gyration is a way of characterizing the average shape of aggregates. The solvent accessible surface area (SASA) of the aggregates was computed using the GROMACS tool gmx sasa, which uses the double cubic lattice method, a numerical algorithm developed by Eisenhaber et al.52 The SASA is that part of the surface of a sphere (probe) centered at an atom with radius (vdW + solvent), where the center of a probe can be placed in contact with the atomic vdW sphere without penetrating other atoms. The spatial distributions of atoms around the bile salt and cholesterol reference molecules were calculated using g_sdf version 1.25, distributed with GROMACS 4.0.7 using a bin width of 0.09 nm and a 10 × 10 × 10 nm grid.53 The chosen atoms of the reference molecules are located in the rigid steroidal skeleton, rather than in the more flexible carbon sidechain, to reduce atom displacement and thus ensure a more representative spatial distribution function (SDF) during the duration of the simulations. Visualization of the simulation trajectories was performed using VMD54 version 1.9.2. Molecular aggregation was examined using the script f ind_aggregate from the Silico package,49 which identifies hydrophobic aggregates of molecules (e.g., micelles, vesicles, or lamellae) in a periodic system. Molecules were defined as belonging to the same aggregate if two carbon atoms were within a cutoff distance of 0.4 nm. Any remaining molecules were subsequently identified as being free monomers. Replica-Exchange MD (REMD). To confirm convergence of the system at pH 7, temperature replica-exchange MD (REMD) and subsequent analysis was performed with GROMACS version 2016.3. Independent simulations were conducted on a set of 16 noninteracting replicas of the same molecular system over a range of temperatures (300−315 K). Pairs of replicas can exchange configurations at the fixed time intervals according to the Metropolis criterion.55 The temperature spacing was obtained using the web-based temperature generator, developed by Patriksson and van der Spoel.56 Experimental Methods. The lyso-phospholipid, 1-palmitoyl-2-hydroxy-sn-glycerol-3-phosphocholine (LPC), was obtained from Avanti Polar Lipids, Inc. (Alabaster, Alabama, US) in powder form. Glycodeoxycholic acid sodium salt (GDX) was obtained from Merk Millipore Calbiochem (Billerica, Massachussetts, US). Oleic acid (OA) (>90% pure) and cholesterol (CHL) were purchased from Sigma-Aldrich (St. Louis, Missouri, US). Dibasic (sodium) hydrogen phosphate and potassium chloride came from Analytical Univar Reagent Ajax Finechem Pty Ltd. (Thermo Fisher Scientific, Scoresby, Australia), and citric acid was obtained from Merck (Darmstadt, Germany). All water used was obtained from a Milli-Q water purification system (Millipore, Billerica, Massachusetts, US). Buffer Solution. A McIlvaine’s binary buffer mixture was prepared to obtain two buffer solutions of pH 6 and pH 7.57

The ionic strength was adjusted to 0.152 M with potassium chloride as described by Elving et al.,58 thereby approximately reflecting the ionic strength present within the human small intestine.59 This medium was filtered through polypropylene filters with 0.2 μm pore size to remove any dust particles and then incubated at 37 °C. Bile Stock Solutions. An aqueous bile salt stock solution of 73.91 mM (3% w/w) was prepared by dissolving GDX into preheated pH-specific buffer solution. This solution was optically clear since bile salt aggregates spontaneously to form small micelles (less than 10 nm)60 above their critical micelle concentration (CMC), which are too small to scatter light in the visible range. For cholesterol containing samples, an 8% w/ w stock solution (GDX + CHL) was prepared by dissolving weighed amounts of GDX and CHL in an ethanol−water 4:1 solution, followed by rotary evaporation to dryness in a roundbottomed flask. The flask was subsequently placed on a vacuum pump overnight to remove residual organic solvent, resulting in a thin film. This GDX/CHL film was reconstituted by adding preheated aqueous buffer solution, vortex-mixed for 30 min and placed on an orbital mixed at 37 °C for 72 h, a method adapted from F. P. Woodford.61 Lipid Stock Solutions. Lipid stock solutions were prepared using the evaporated film method. A stock solution of LPC + OA (60.53 mM, 3% w/w) was made by dissolving weighed amounts of LPC and OA in a chloroform−methanol 80:20 solution, evaporated, and put on vacuum overnight, as described above. Flasks were sealed and wrapped in foil to limit any potential lipid oxidation. The resulting lipid film was hydrated by preheated buffer solution, vortex-mixed for 30 min, and kept on an orbital mixer incubator at 37 °C for 24 h. A stock solution of LPC/OA/CHL (8% w/w total lipid) was prepared by weighing out the appropriate amount of LPC, OA, and CHL dissolved in a chloroform−methanol 80:20 solution, evaporated until dryness in a round-bottomed flask wrapped in aluminum foil, to prevent UV-degradation of cholesterol, and rehydrated as described above. Sample solutions were prepared by mixing both stock solutions to achieve lipid ratios in the region of the phase boundary, previously identified by turbidity measurements. Dynamic Light Scattering. A Malvern Zetasizer Nano ZS ZEN3600 (Worcestershire, United Kingdom) equipped with a 4 mW He−Ne laser and an avalanche photodiode detector was used to measure the hydrodynamic diameter of particles. The backscattered laser light (λ = 633 nm) was monitored at a measurement angle of 173° (Non-Invasive Back-Scatter default). The equipment was calibrated using 60 ± 2.7 and 220 ± 6 nm diameter nanosphere size standards of polystyrene polymer latex (supplied by Ducke Scientific Corporation, USA) in water with a polydispersity index (PDI) of rz), with the shortest dimension being approximately half the large dimensions; i.e., the F


Article

Molecular Pharmaceutics

Figure 5. SDFs represented as isosurfaces using GDX (A,B) and cholesterol (C) as the reference molecule. The reference atoms were C6, C12, and C17 for GDX and C3, C15, and C19 for cholesterol. The reference molecules, GDX (A, B) and CHL (C), are shown as stick figures.

the phosphate group of the phospholipid. Similarly, the hydrophilic atoms of LPC (P1) and OA (C1) tend to be located in this region. Figure 5C shows the SDFs of LPC, OA, and GDX around the cholesterol reference molecule at pH 1 and pH 7. In both cases, the hydrophobic GDX C19 atom and LPC atom C15 make contact with the hydrophobic regions of cholesterol. A high probability water region is found around the cholesterol hydroxyl group. By comparing the simulations at pH 1 and pH 7, we find that the high probability regions for all molecules are much larger at pH 7 (i.e., pink cloud) than at pH 1. The higher probability of finding the OA and LPC atoms around GDX at pH 7 reflects the specific orientation of GDX within the micelles that form at higher pH. This shows that there is greater ordering of GDX in the micelle phase than in the oil phase that forms at low pH. Interestingly, the SDFs also reveal the general shape of the aggregates. At pH 7, all titratable groups are ionized, and this increases the electrostatic repulsion in the colloids causing them to adopt a rather disc-like shape, as discussed above. This is in agreement with the study by Poša62 in which this interaction was likewise determined to contribute to the micellar cholesterol solubilization. Experimental Investigation of Model Bile Phase Behavior. To complement the computational studies described above, experimental models of intestinal fluid consisting of GDX, LPC, OA, and CHL were constructed to examine how micelle-to-vesicle transition is affected by (1) changing the ratio of bile salt to digested phospholipid at pH 6 and pH 7 and (2) adding cholesterol at a fixed ratio. At pH values lower than 6, we found that the GDX precipitated from solution, which precluded determination of the phase boundary at lower pH values. Changes in the location of the phase boundary were initially investigated using nephelometry, with cross-validation by DLS.

residues. LPC is shown to also have an increased surface area with increasing pH value. It can be seen that GDX and LPC are the dominant species on the aggregate surface. The individual cholesterol molecules occupy less than 1% present of total SASA. For simulations both with and without cholesterol, similar SASA values were obtained for the other species in the system. Molecular Interactions within Colloidal Particles. Individual frames from MD simulations do not contain the full information encoded within the trajectory. Therefore, a method that analyzes full MD simulations is necessary to take advantage of the transient information embedded in those trajectories. Such an analysis may be carried out using the SDF, which is the three-dimensional equivalent of the radial distribution function, and describes the three-dimensional probability of finding a particle at a given distance from a reference particle. We used SDFs to investigate the dynamic behavior of the individual molecular species within the simulated systems upon pH alteration and the addition of cholesterol. The time-averaged localization of LPC, OA, GDX, and cholesterol relative to each other were analyzed over the last 20 ns of the trajectory and are shown in Figure 5. The probability cut-offs, used to generate the isosurfaces, are listed in Supporting Information Tables S1 and S2. The SDFs around the GDX were calculated using C6, C12, and C17 as reference atoms, while those around CHL used C3, C15, and C19. The SDFs around the GDX(H) reference molecule in the simulations at pH 1 and pH 7 in the presence and absence of cholesterol are shown in Figures 5A,B, respectively. These SDFs show that the hydrophobic parts of LPC and OA (OA C12 and LPC C8 atoms) interact strongly with the convex side (β-face) of GDX. Water oxygen atoms (OW) atoms are predominantly located at the hydrophilic, concave face of the bile salt molecule. This region is also strongly associated with G


Article


Figure 6. Nephelometry measurements displayed versus weight fraction of LPC + OA at pH 6 (blue) and pH 7 (black) at 0.873, 1.0, and 1.5% w/w solutes for the system with cholesterol (green) compared to the system without cholesterol (black), and error bars are plotted as SD. The weight fraction of GDX and buffer solution is not displayed in this graph. The dashed lines represent best fit of the micellar and vesicular regions of the turbidity data (phase boundary) at both pH values.

(nephelometry) and backscattered light (DLS) is low, indicating that LPC and OA are solubilized by GDX to form mixed micelles. As WLPC+OA increases, mixed micelles keep swelling upon incorporation of lipids until a critical value for WLPC+OA is reached at which vesicles start to appear (the phase boundary). This phase change is characterized by a sharp increase in particle size and subsequently in turbidity. The transition from micelles to vesicles is smooth and involves a region where micelles and vesicles coexist. The micellar− vesicular phase boundary was identified as the intersection between the lines of best fit of the micellar and vesicular phases (Figure S6). Beyond the phase boundary, the amount of phospholipid exceeds the solubilizing capacity of the bile salt, and vesicles are formed. Further increase in the lipid/bile salt ratio drives the formation of larger vesicles producing a

Nephelometry is a sensitive high-throughput method that has the ability to discriminate between micelles and vesicles based on the amount of forward scattered light (turbidity).63 DLS, which detects the amount of backscattered light by particles in solution, was used to measure the average size of the colloids. The appearance of vesicles was monitored during DLS measurements using the intensity distribution. All the experimental model systems contained GDX mixed with equimolar amounts of LPC and OA (LPC + OA). Phase boundary experiments were performed by mixing lipid and bile salt stock solutions in different ratios to obtain sample sets with a constant solute content, which ranged from 0.873 to 1.5% w/ w; this concentration range encompasses the FeSSIF (fed) composition.64−66 At low mass fraction of digested phospholipid (WLPC+OA), the amount of forward scattered light H


Article


Figure 7. Ternary phase diagrams of mixtures of GDX/LPC + OA/buffer at pH 6 and pH 7 and ±cholesterol derived from DLS measurements. Filled circles (blue) represent micelles, and empty circles (brown) represent vesicles. Stars show points where mixed micelle and vesicles coexist. Bright colors and solid lines represent the regions constructed by interpolation of measurements. Faded colors and dotted lines represent a region constructed by extrapolation of measurements. Red squares and diamonds symbolize the compositions of FaSSIF and FeSSIF, respectively. Note: NaTCH is replaced by NaGDX in the FaSSIF and FeSSIF compositions.64

set at 1:22. The same % w/w of cholesterol was added to both LPC + OA stock solutions in order to maintain a constant fraction of cholesterol across the GDX + (LPC + OA) mixtures. Figure 6 shows the nephelometry plots for the systems without cholesterol at 0.873% w/w solutes where the micelleto-vesicle transitions occurs around 0.45−0.47% w/w LPC + OA at pH 6 and at 0.6−0.63% w/w LPC + OA at pH 7. For 1.0% w/w solutes, these transitions were seen at 0.45−0.47 and 0.63−0.65% w/w LPC + OA at pH 6 and pH 7, respectively. The phase boundary occurs around 0.9−0.95 and 1.0−1.1% w/ w LPC + OA at pH 6 and pH 7, respectively, for 1.5%, w/w solutes. The micelle-to-vesicle transition for the systems with cholesterol at pH 7 were observed at 0.5−0.53 for 0.873% w/w, at 0.47−0.5 for 1.0% w/w, and at 0.76−0.79 for 1.5% w/w solutes. Additional plots are provided in Figure S7. The impact of pH change and cholesterol addition is represented in the ternary diagrams shown in Figure 7. In the absence of cholesterol, a pH change from 6 to 7 markedly changes the position of the boundary between micelle and vesicle regions of the phase diagram, with the size of the vesicle region being substantially reduced at pH 7. The addition of cholesterol at either pH 6 or pH 7 moves the phase boundary upward. In the presence of cholesterol, a change in pH from 6

decrease in turbidity, as seen in Figure 6. Detection of the phase boundary (appearance of vesicles) by DLS is clear since the hydrodynamic diameter of mixed micelles (5−13 nm) is significantly smaller than that of vesicles (200−600 nm). The DLS technique also measures the colloidal polydispersity. The presence of more than one colloid population (e.g., micelles + vesicles) leads to the observation of multiple intensities (a biphasic size distribution) and thus an increase in PDI up to 0.55. The average PDI of this system in the micellar region was in the range of 0.06−0.4, indicating low polydispersity. Impact of pH and Cholesterol on the Phase Boundary. To explore whether a pH shift alters the phase boundary, the ternary phase diagrams of the GDX/LPC + OA/ buffer systems at pH 6 and pH 7 were compared. The impact of cholesterol on the phase formation of bile salt and digested phospholipid in buffer was examined by adding cholesterol in a constant ratio relative to the corresponding total bile salt and lipid fraction. The cholesterol fractions were 0.03, 0.04, and 0.05% w/w for concentrations of 0.873, 1.0, and 1.5%, w/w GDX + LPC + OA, respectively. Since GDX has a maximum cholesterol solubility of 1:19 (cholesterol/GDX molar ratio),67,68 the ratio of the GDX + CHL stock solution was I


Article


natural lipid, at a molar ratio of approximately 1/16 with respect to bile salts. The localization of cholesterol inside the colloidal structures, formed by GDX, LPC, and OA, can be attributed to the fact that cholesterol is a relatively insoluble amphiphile (solubility of 20−30 × 10−9 M), which requires species such as bile salts and phospholipid to be solubilized.16,74 Our simulations show that this cholesterol internalization within micelles occurs quickly, although the cholesterol SASA is not zero due to the dynamic behavior of the cholesterol molecules, which present their hydrophilic hydroxyl group to the colloid surface for a short period of time before moving back inside the micellar core. To better understand the impact of changes in pH and cholesterol content on the morphology of the self-assembled structures, the radius of gyration was examined. The formation of disc-like aggregates of surfactant and phospholipid has been reported previously for bile salt−phospholipid mixed micelles,26,75,76 and results obtained here suggest that the colloidal shape is similar upon phospholipid digestion. Self-assembly of amphiphiles is directed to achieve a minimal exposure of hydrophobic moieties to water. Intuitively the nature of this self-assembly (oblate spheroid) is governed by the molecular structure of the amphiphile. This molecular geometry is reflected by a dimensionless value, called the “critical packing parameter”. Bile salts will form spherical micelles, while lysophospholipids and free fatty acids will tend to form cylindrical, rod-like micelles.77 Mixing phospholipids with a detergent (bile salt) will yield layers that are not ideal for either of the two amphiphiles. Instead, the two components are forced by entropy to reside in mixed aggregates. We found that the addition of cholesterol does not alter the morphology of the final colloids. Swelling of cholesterol in bile salt aggregates has been reported,61 but the low cholesterol concentration present in these MD simulations was not sufficient to produce this effect. Microstructure of Aggregates. The tendency of a species to be positioned at a colloidal surface is directly related to the nature and spatial distribution of its hydrophilic groups. Bile salts cannot be considered as traditional, flexible, aliphatic surfactants with a distinct head-to-tail polarity. However, they still possess this crucial dual nature due to their rigid, bifacial structure of the steroid nucleus, which allows GDX to expose all hydrophilic groups (two hydroxyls and one carboxylic acid) to the surrounding water. This explains the large extent to which GDX is present at the interface. The low SASA of cholesterol shown in Figure 4 is not surprising since cholesterol contains only a single hydrophilic group and is present only in very small amounts. The similar SASA values for all species in systems with and without cholesterol is expected, as the SASA due to cholesterol is negligible and both systems have identical ratios of bile salt to phospholipid. The SASA of all residue types is lower at pH 1 than at pH 7 in both systems because the anionic form of each species, present at the higher pH, possesses a higher desolvation penalty. The formation of anions within a colloidal system generates electrostatic headgroup repulsion, resulting in smaller micelles. The smaller, and therefore more numerous, aggregates that emerge in the simulated systems increase, in turn, the extent to which molecules are exposed to water. The large increase in SASA occurring between pH 3 and 4 corresponds to that the phase boundary is evident in the simulations as micelles form (Figure 2). This observation suggests that ionization of GDX drives the formation of micelles at pH 4,

to 7 does not appreciably move the phase boundary. It was observed, from the DLS measurements, that the addition of cholesterol at either pH did not alter the general size of the micelles or vesicles.

■

DISCUSSION After oral administration, drugs travel along the GI tract where they are exposed to a dynamic pH profile and a variety of different endogenous compounds. Drugs with a low aqueous solubility rely on colloidal structures formed in the intestinal juices to eventually be absorbed across the intestinal barrier. By developing an understanding of the natural phenomena that occur in the intestinal fluids, one can then piggy-back on those processes to engineer smart ways to overcome the hurdle of poor water solubility and obtain satisfactory drug absorption. This work therefore aims to provide better insight into the influence of cholesterol on intraluminal colloid formation and its pH dependency. Molecular Dynamics Simulations. The spontaneous aggregation of bile salts and phospholipids is a cooperative phenomenon that was observed experimentally more than 70 years ago by Roepke et al.69 and is reproducible by MD simulations.36,70,71 In the current work, aggregation used a digested phospholipid, i.e., lysophospholipid plus fatty acid, to reflect the contents of the gut lumen downstream of the pancreatic duct. The major driving force underlying this spontaneous aggregation of lipids in the aqueous environment is the hydrophobic effect, arising from transfer of hydrocarbon chains from aqueous surroundings into an oil-like interior. Above the critical micellar concentration (CMC), the hydrophobic tails of the amphiphiles become buried into the micellar core. This generates a more disordered state for water molecules compared to when they were surrounded by monomers, which means a gain in entropy from the water molecules. This increase in entropy compensates for the more organized colloid formation.72 The pH along the digestive tract varies from 1.0 to 3.1 in the stomach and to 4.8−8.2 in the duodenum.59 Therefore, it can be stated that simulations at a single pH do not give a holistic perspective of the bile phases. The pH of a solution is an important thermodynamic variable; it influences the structure, dynamics, and function of molecules in solution. Additionally, it has long been known that pH plays an important role in controlling the phase and morphological behavior of ionizable lipids and surfactants.73 The final colloidal structures, illustrated in Figure 2, reveal the structural consequences resulting from ionization of the titratable residues (GDX and OLAT) at higher pH values. Deprotonation of the GDX and OLAT carboxylic acid groups makes them avidly more water-soluble. In contrast, low pH values promote the formation of a water insoluble species (oil) that may be observed experimentally as a floating oil phase or as a dense lipidic phase. In our simulations we observed phase separation at lower pH, which occurred due to the presence of the nonionic forms of the bile salt and the free fatty acids at pH 1 to pH 3. It is well-known that unionized bile salts have lower aqueous solubility than their ionized counterparts and do not form micellar structures. On the transition from pH 3 to pH 4, the content of deprotonated bile salt in the simulation increases from approximately 20% to 70%, which provides the major driving force for the formation of micelles at pH 4. We investigated the influence of cholesterol on a mixed micelle structure, as bile is known to contain low levels of this J


Molecular Pharmaceutics consistent with the intrinsic pKa (3.58). The SASA of the LPC molecules follows the same general trend. The higher probability in the SDF of the atomic groups around GDX at pH 7 compared to pH 1 (Figure 5) is due to the desolvation penalty of the carboxylic group. At pH 1, the formal charge of the GDX molecules is zero, and therefore, the GDX molecules do not adopt a preferred orientation, which results in multiple possible positions of GDX at pH 1 and thus lower isovalues for the neighboring molecules. At pH 7, in contrast, the carboxylic groups of the GDX residues are fully deprotonated, resulting in a specific preferred orientation that favors the positioning of the charged groups toward the surrounding water, burying the hydrophobic groups in the core of the micelle. Experimental Models. The pH in the small intestinal lumen, and more precisely the duodenum and jejunum, in the fasted state ranges from 6 to 7.78,79 Our nephelometry results show that, in the absence of cholesterol, decreasing the pH from 7 to 6 leads to a marked shift of the phase boundary toward a lower WLPC+OA. This indicates that GDX has a higher solubilizing capacity when more ionized. This trend was observed for all concentrations of GDX + (LPC + OA) (Figure 7). DLS measurements confirmed the location of the phase boundary. This shift of the phase boundary from pH 6 to pH 7 was unexpectedly large considering the small change in the ratio of ionized to unionized species at these two pH values that would be expected based on the intrinsic pKa of the ionizable molecules. However, the intrinsic pKa differs from the apparent pKa,80 which is elevated in lipid colloidal structures such as micelles and vesicles, with values ranging from 7.2 to 7.5,81 up to 8.82 The same reasoning can also be applied to the behavior of bile salt molecules for which apparent pKa values ranging from 6.1 to 6.8 have been reported.83 With the apparent pKa values of OA and GDX to values being greater than 6, the difference in ionization for these molecules between pH 6 and pH 7 is large, which explains the large shift in phase boundary when going from pH 6 to pH 7. This trend indicates that homeostasis and regulation of the pH within small intestine can have a substantial impact of the phase behavior of intestinal colloids. The addition of cholesterol to the GDX/LPC + OA/buffer system moves the phase boundary upward (i.e., favoring vesicle formation), which indicates a decrease in the solubilizing capacity of the bile salt. This phenomenon occurs at both pH 6 and pH 7. A similar observation was reported by Small and Bourges84 for a system containing nondigested phospholipid, at a fixed pH value and at 25 °C. In addition, a larger biphasic region (mixed vesicles and micelles) in the presence of cholesterol suggests that cholesterol has an impact on vesicle formation, rather than on the micellar colloids. This finding is comparable to the phenomenon observed by Ladbrooke et al.,85 in which the addition of cholesterol to dipalmitoyl-Llecithin in water lowers the gel−crystalline transition temperature and causes a decrease in heat absorption at that transition. The effect of cholesterol was attributed to the inhibition of the phospholipid hydrocarbon chain motion. Cholesterol, when added to the ternary systems, could stabilize the lamellar structure so that the micelle-to-vesicle transition requires a higher lipid/bile salt ratio than in absence of cholesterol. It is also important to note that the effects of cholesterol on the micelle-to-vesicle transitions in the studied systems occurred when relatively low concentrations of cholesterol were added to the ternary GDX/LPC + OA/buffer systems.

Article

■

CONCLUSIONS

■

ASSOCIATED CONTENT

In this study we have explored the influence of cholesterol and of pH change on the colloid formation in a fasted state human bile using MD simulations and experimentally with DLS and nephelometry. The components GDX, LPC, and OA were used to represent a physiologically relevant environment produced by the digestion of the phospholipids present in bile. The modeling data provides a qualitative view that helps us understand the molecular events observed experimentally. Above pH 4, the simulations show spontaneous and rapid aggregation of the bile components from an initial random distribution of molecules, being driven by the hydrophobic effect to form mixed micelles with a generally disc-like structure and with GDX preferentially localized on the colloid surface. A decrease in aggregate size was observed with increasing pH. Below pH 4, the lipids form a separated, oily phase. This aggregation behavior is driven by differences in the ionization state of the titratable groups. When cholesterol is added to the ternary system at physiological concentration, the simulations show that it is internally solubilized within the micelles and that it does not significantly influence the aggregate size, number, shape or dynamics of mixed micellar colloids. To complement the MD simulations, we performed experimental DLS and nephelometry studies that shed light on the influence of the two variables (pH and cholesterol) on the transition between micelle and vesicle containing phases. In the absence of cholesterol, changing the system pH from 6 to 7 generates a shift in the phase boundary on the ternary phase diagram due to the improved solubilizing capacity of GDX. The addition of small amounts of cholesterol generated a larger biphasic (vesicle) region on the ternary diagram, likely caused by stabilizing the vesicle bilayer. The addition of physiological quantities of cholesterol did not measurably alter the colloids in the micellar region of FaSSIF and FeSSIF, meaning that those systems can correctly be modeled using MD in the absence of cholesterol, although systems modeling the biphasic region may require the inclusion of cholesterol to establish more complete models. This study contributes to a better understanding of the emergence, nature, and evolution of colloidal phases in the small intestine and the key molecular processes that govern drug absorption. This is of particular interest for studies of PWSDs that require the colloidal phases formed in the gut to circumvent the dissolution step and thereby increase their apparent solubility. In turn, these insights will aid in rational design of superior formulations for PWSDs with enhanced in vivo performance.

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.molpharmaceut.7b00446. Henderson−Hasselbach ionization plots for GDX and OA, micellar aggregation process, plots showing system equilibration, final frames from the large simulation cell, workflow of the REMD, spatial distribution probability cutoff values used for the reference atoms, graph with the phase boundary determination, additional nephelometry plots, and PDB files containing the final simulations geometries of simulations 1−14 (ZIP) K


Article


■

Lipids during Duodenal Fat Digestion in Healthy Adult HumanBeings. Biochemistry 1990, 29 (8), 2041−2056. (11) Albers, C. J.; Huizenga, J. R.; Krom, R. A.; Vonk, R. J.; Gips, C. H. Composition of human hepatic bile. Ann. Clin. Biochem. 1985, 22, 129−132. (12) Carey, M. C.; Small, D. M. Micelle Formation by Bile-Salts Physical-Chemical and Thermodynamic Considerations. Arch. Intern. Med. 1972, 130 (4), 506−527. (13) Williams, H. D.; Sassene, P.; Kleberg, K.; Bakala-N’Goma, J. C.; Calderone, M.; Jannin, V.; Igonin, A.; Partheil, A.; Marchaud, D.; Jule, E.; Vertommen, J.; Maio, M.; Blundell, R.; Benameur, H.; Carriere, F.; Mullertz, A.; Porter, C. J. H.; Pouton, C. W. Toward the establishment of standardized in vitro tests for lipid-based formulations, part 1: method parameterization and comparison of in vitro digestion profiles across a range of representative formulations. J. Pharm. Sci. 2012, 101 (9), 3360−3380. (14) Birru, W. A.; Warren, D. B.; Ibrahim, A.; Williams, H. D.; Benameur, H.; Porter, C. J.; Chalmers, D. K.; Pouton, C. W. Digestion of phospholipids after secretion of bile into the duodenum changes the phase behavior of bile components. Mol. Pharmaceutics 2014, 11 (8), 2825−2834. (15) Small, D. M.; Bourges, M. C.; Dervichian, D. G. The biophysics of lipidic associations. I. The ternary systems: lecithin-bile salt-water. Biochim. Biophys. Acta, Lipids Lipid Metab. 1966, 125 (3), 563−580. (16) Cabral, D. J.; Small, D. M., Supplement 18: Handbook of Physiology, The Gastrointestinal System, Salivary, Gastric, Pancreatic, and Hepatobiliary Secretion. In Physical Chemistry of Bile; John Wiley & Sons, Inc.: 2011. (17) Admirand, W. H.; Small, D. M. The physicochemical basis of cholesterol gallstone formation in man. J. Clin. Invest. 1968, 47 (5), 1043−1052. (18) Bourges, M.; Small, D. M.; Dervichian, D. G. Biophysics of Lipid Associations 0.3. Quaternary Systems Lecithin-Bile Salt-CholesterolWater. Biochim. Biophys. Acta, Lipids Lipid Metab. 1967, 144 (2), 189− 201. (19) Isaksson, B. On the Lipids and Bile Acids in Normal and Pathological Bladder Bile: A Study of the Main Cholesterol Dissolving Components of Human Bile; Förf: Lund, 1954; p 21. (20) Ginanni Corradini, S.; Ripani, C.; Della Guardia, P.; Giovannelli, L.; Elisei, W.; Cantafora, A.; Pisanelli, M. C.; Tebala, G. D.; Nuzzo, G.; Corsi, A.; Attili, A. F.; Capocaccia, L.; Ziparo, V. The human gallbladder increases cholesterol solubility in bile by differential lipid absorption: A study using a new in vitro model of isolated intraarterially perfused gallbladder. Hepatology 1998, 28 (2), 314−322. (21) Long, M. A.; Kaler, E. W.; Lee, S. P. Structural characterization of the micelle-vesicle transition in lecithin-bile salt solutions. Biophys. J. 1994, 67 (4), 1733−1742. (22) Lindstrom, M.; Ljusbergwahren, H.; Larsson, K.; Borgstrom, B. Aqueous Lipid Phases of Relevance to Intestinal Fat Digestion and Absorption. Lipids 1981, 16 (10), 749−754. (23) Riethorst, D.; Baatsen, P.; Remijn, C.; Mitra, A.; Tack, J.; Brouwers, J.; Augustijns, P. An In-Depth View into Human Intestinal Fluid Colloids: Intersubject Variability in Relation to Composition. Mol. Pharmaceutics 2016, 13 (10), 3484−3493. (24) Hjelm, R. P. The Small-Angle Approximation of X-Ray and Neutron Scatter from Rigid Rods of Non-Uniform Cross-Section and Finite Length. J. Appl. Crystallogr. 1985, 18 (Dec), 452−460. (25) Rezhdo, O.; Di Maio, S.; Le, P.; Littrell, K. C.; Carrier, R. L.; Chen, S. H. Characterization of colloidal structures during intestinal lipolysis using small-angle neutron scattering. J. Colloid Interface Sci. 2017, 499, 189−201. (26) Muller, K. Structural Dimorphism of Bile-Salt Lecithin Mixed Micelles - a Possible Regulatory Mechanism for Cholesterol Solubility in Bile - X-Ray Structure-Analysis. Biochemistry 1981, 20 (2), 404− 414. (27) Mazert, N. A. Laser Light Scattering in Micellar Systems. In Dynamic Light Scattering: Applications of Photon Correlation Spectroscopy; Pecora, R., Ed.; Springer US: Boston, MA, 1985; pp 305−346.

AUTHOR INFORMATION

Corresponding Authors

*E-mail: [email protected]. *E-mail: [email protected]. ORCID

Christopher J. H. Porter: 0000-0003-3474-7551 Colin W. Pouton: 0000-0003-0224-3308 David K. Chalmers: 0000-0003-2366-569X Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS We would like to thank the Victorian Life Sciences Computation Initiative (VLSCI), MASSIVE, and the National Computational Infrastructure (NCI) for technical support and Merit Allocation Scheme grants of CPU time through grants VR0004 and y96, respectively. We acknowledge partial funding for this work from ARC Linkage grant LP120100600 and from Capsugel R&D, Ilkirch, France.

■

ABBREVIATIONS GI, gastrointestinal; MD, molecular dynamics; DLS, dynamic light scattering; NTU, nephelometric turbidity units; PC, phosphatidylcholines; GDX, glycodeoxycholic acid, sodium salt; LPC, 1-palmitoyl-2-hydroxy-sn-glycerol-3-phosphocholine; OA, oleic acid; CHL, cholesterol; PWSDs, poorly water-soluble drugs; SASA, solvent-accessible surface area; FaSSIF, fastedstate simulated intestinal fluid; FeSSIF, fed-state simulated intestinal fluid; CMC, critical micellar concentration

■

REFERENCES

(1) Porter, C. J.; Williams, H. D.; Trevaskis, N. L. Recent advances in lipid-based formulation technology. Pharm. Res. 2013, 30 (12), 2971− 5. (2) Warren, D. B.; King, D.; Benameur, H.; Pouton, C. W.; Chalmers, D. K. Glyceride Lipid Formulations: Molecular Dynamics Modeling of Phase Behavior During Dispersion and Molecular Interactions Between Drugs and Excipients. Pharm. Res. 2013, 30 (12), 3238− 3253. (3) Benson, S. P.; Pleiss, J. Molecular dynamics simulations of selfemulsifying drug-delivery systems (SEDDS): influence of excipients on droplet nanostructure and drug localization. Langmuir 2014, 30 (28), 8471−80. (4) Jha, P. K.; Larson, R. G. Assessing the Efficiency of Polymeric Excipients by Atomistic Molecular Dynamics Simulations. Mol. Pharmaceutics 2014, 11 (5), 1676−1686. (5) Mahmoudzadeh, M.; Fassihi, A.; Dorkoosh, F.; Heshmatnejad, R.; Mahnam, K.; Sabzyan, H.; Sadeghi, A. Elucidation of Molecular Mechanisms Behind the Self-Assembly Behavior of Chitosan Amphiphilic Derivatives Through Experiment and Molecular Modeling. Pharm. Res. 2015, 32 (12), 3899−3915. (6) Alskar, L. C.; Porter, C. J. H.; Bergstrom, C. A. S. Tools for Early Prediction of Drug Loading in Lipid-Based Formulations. Mol. Pharmaceutics 2016, 13 (1), 251−261. (7) Bergstrom, C. A. S.; Charman, W. N.; Porter, C. J. H. Computational prediction of formulation strategies for beyond-ruleof-5 compounds. Adv. Drug Delivery Rev. 2016, 101, 6−21. (8) Jha, P. K.; Larson, R. G. Assessing the Efficiency of Polymeric Excipients by Atomistic Molecular Dynamics Simulations. Mol. Pharmaceutics 2014, 11 (5), 1676−1686. (9) Carey, M. C.; Small, D. M.; Bliss, C. M. Lipid digestion and absorption. Annu. Rev. Physiol. 1983, 45 (1), 651−677. (10) Hernell, O.; Staggers, J. E.; Carey, M. C. Physical-Chemical Behavior of Dietary and Biliary Lipids during Intestinal Digestion and Absorption 0.2. Phase-Analysis and Aggregation States of Luminal L


Article

Molecular Pharmaceutics (28) Staggers, J. E.; Hernell, O.; Stafford, R. J.; Carey, M. C. PhysicalChemical Behavior of Dietary and Biliary Lipids during Intestinal Digestion and Absorption 0.1. Phase-Behavior and Aggregation States of Model Lipid Systems Patterned after Aqueous Duodenal Contents of Healthy Adult Human-Beings. Biochemistry 1990, 29 (8), 2028− 2040. (29) Small, D. M.; Penkett, S. A.; Chapman, D. Studies on simple and mixed bile salt micelles by nuclear magnetic resonance spectroscopy. Biochim. Biophys. Acta, Lipids Lipid Metab. 1969, 176 (1), 178−189. (30) Gouin, S.; Zhu, X. X. Fluorescence and NMR Studies of the Effect of a Bile Acid Dimer on the Micellization of Bile Salts. Langmuir 1998, 14 (15), 4025−4029. (31) Marrink, S. J.; Mark, A. E. Molecular dynamics simulations of mixed micelles modeling human bile. Biochemistry 2002, 41 (17), 5375−5382. (32) Warren, D. B.; Chalmers, D. K.; Hutchison, K.; Dang, W.; Pouton, C. W. Molecular dynamics simulations of spontaneous bile salt aggregation. Colloids Surf., A 2006, 280 (1−3), 182−193. (33) Pártay, L. B.; Jedlovszky, P.; Sega, M. Molecular Aggregates in Aqueous Solutions of Bile Acid Salts. Molecular Dynamics Simulation Study. J. Phys. Chem. B 2007, 111 (33), 9886−9896. (34) Verde, A. V.; Frenkel, D. Simulation study of micelle formation by bile salts. Soft Matter 2010, 6 (16), 3815−3825. (35) Turner, D. C.; Yin, F.; Kindt, J. T.; Zhang, H. Molecular dynamics simulations of glycocholate-oleic acid mixed micelle assembly. Langmuir 2010, 26 (7), 4687−4692. (36) King, D. T.; Warren, D. B.; Pouton, C. W.; Chalmers, D. K. Using molecular dynamics to study liquid phase behavior: simulations of the ternary sodium laurate/sodium oleate/water system. Langmuir 2011, 27 (18), 11381−11393. (37) Birru, W. A.; Warren, D. B.; Han, S.; Benameur, H.; Porter, C. J.; Pouton, C. W.; Chalmers, D. K. Computational Models of the Gastrointestinal Environment. 2. Phase Behavior and Drug Solubilization Capacity of a Type I Lipid-Based Drug Formulation after Digestion. Mol. Pharmaceutics 2017, 14 (3), 580−592. (38) Birru, W. A.; Warren, D. B.; Headey, S. J.; Benameur, H.; Porter, C. J.; Pouton, C. W.; Chalmers, D. K. Computational Models of the Gastrointestinal Environment. 1. The Effect of Digestion on the Phase Behavior of Intestinal Fluids. Mol. Pharmaceutics 2017, 14 (3), 566− 579. (39) Ikonen, E. Cellular cholesterol trafficking and compartmentalization. Nat. Rev. Mol. Cell Biol. 2008, 9 (2), 125−138. (40) Pronk, S.; Pall, S.; Schulz, R.; Larsson, P.; Bjelkmar, P.; Apostolov, R.; Shirts, M. R.; Smith, J. C.; Kasson, P. M.; van der Spoel, D.; Hess, B.; Lindahl, E. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 2013, 29 (7), 845−854. (41) Verlet, L. Computer Experiments on Classical Fluids.I. Thermodynamical Properties of Lennard-Jones Molecules. Phys. Rev. 1967, 159 (1), 98. (42) Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. A Smooth Particle Mesh Ewald Method. J. Chem. Phys. 1995, 103 (19), 8577−8593. (43) Oostenbrink, C.; Villa, A.; Mark, A. E.; Van Gunsteren, W. F. A biomolecular force field based on the free enthalpy of hydration and solvation: The GROMOS force-field parameter sets 53A5 and 53A6. J. Comput. Chem. 2004, 25 (13), 1656−1676. (44) Bachar, M.; Brunelle, P.; Tieleman, D. P.; Rauk, A. Molecular dynamics simulation of a polyunsaturated lipid bilayer susceptible to lipid peroxidation. J. Phys. Chem. B 2004, 108 (22), 7170−7179. (45) Martinez-Seara, H.; Róg, T.; Karttunen, M.; Reigada, R.; Vattulainen, I. Influence of cis double-bond parametrization on lipid membrane properties: how seemingly insignificant details in force-field change even qualitative trends. J. Chem. Phys. 2008, 129 (10), 105103. (46) Miyamoto, S.; Kollman, P. A. Settle: An analytical version of the SHAKE and RATTLE algorithm for rigid water models. J. Comput. Chem. 1992, 13 (8), 952−962.

(47) Hess, B.; Bekker, H.; Berendsen, H. J. C.; Fraaije, J. G. E. M. LINCS: A linear constraint solver for molecular simulations. J. Comput. Chem. 1997, 18 (12), 1463−1472. (48) Tieleman, D. P.; van der Spoel, D.; Berendsen, H. J. C. Molecular dynamics simulations of dodecylphosphocholine micelles at three different aggregate sizes: Micellar structure and chain relaxation. J. Phys. Chem. B 2000, 104 (27), 6380−6388. (49) Chalmers, D. K.; Roberts, B. P. Silico−a Perl Molecular Modelling Toolkit, 2011. http://silico.sourceforge.net. (50) Galia, E.; Nicolaides, E.; Horter, D.; Lobenberg, R.; Reppas, C.; Dressman, J. B. Evaluation of various dissolution media for predicting in vivo performance of class I and II drugs. Pharm. Res. 1998, 15 (5), 698−705. (51) Persson, E. M.; Nilsson, R. G.; Hansson, G. I.; Lofgren, L. J.; Liback, F.; Knutson, L.; Abrahamsson, B.; Lennernas, H. A clinical single-pass perfusion investigation of the dynamic in vivo secretory response to a dietary meal in human proximal small intestine. Pharm. Res. 2006, 23 (4), 742−751. (52) Eisenhaber, F.; Lijnzaad, P.; Argos, P.; Sander, C.; Scharf, M. The Double Cubic Lattice Method - Efficient Approaches to Numerical-Integration of Surface-Area and Volume and to Dot Surface Contouring of Molecular Assemblies. J. Comput. Chem. 1995, 16 (3), 273−284. (53) Freudenberger, C. g_sdf, 1.25 ed.; University of Ulm, 2003. (54) Humphrey, W.; Dalke, A.; Schulten, K. VMD: visual molecular dynamics. J. Mol. Graphics 1996, 14 (1), 33−8. (55) Sugita, Y.; Okamoto, Y. Replica-exchange molecular dynamics method for protein folding. Chem. Phys. Lett. 1999, 314 (1−2), 141− 151. (56) Patriksson, A.; van der Spoel, D. A temperature predictor for parallel tempering simulations. Phys. Chem. Chem. Phys. 2008, 10 (15), 2073−2077. (57) McIlvaine, T. C. A buffer solution for colorimetric comparison. J. Biol. Chem. 1921, 49 (1), 183−186. (58) Elving, P. J.; Markowitz, J. M.; Rosenthal, I. Preparation of Buffer Systems of Constant Ionic Strength. Anal. Chem. 1956, 28 (7), 1179−1180. (59) Lindahl, A.; Ungell, A. L.; Knutson, L.; Lennernas, H. Characterization of fluids from the stomach and proximal jejunum in men and women. Pharm. Res. 1997, 14 (4), 497−502. (60) Small, D. M. Size and Structure of Bile Salt Micelles - Influence of Structure Concentration Counterion Concentration Ph and Temperature. Adv. Chem. Ser. 1968, 84, 31−52. (61) Woodford, F. P. Enlargement of Taurocholate Micelles by Added Cholesterol and Monoolein - Self-Diffusion Measurements. J. Lipid Res. 1969, 10 (5), 539−545. (62) Poša, M., Chromatographic Retention Parameters as Molecular Descriptors for Lipophilicity in QSA(P)R Studies of Bile Acid. In Chromatography - The Most Versatile Method of Chemical Analysis; Calderon, L., Ed.; InTech: 2012. (63) Lawler, D. M., Turbidimetry and Nephelometry. In Encyclopedia of Analytical Science; Academic Press Ltd: 1995. (64) Marques, M. R. C.; Loebenberg, R.; Almukainzi, M. Simulated Biological Fluids with Possible Application in Dissolution Testing. Dissolution Technol. 2011, 18 (3), 15−28. (65) Jantratid, E.; Janssen, N.; Reppas, C.; Dressman, J. B. Dissolution media simulating conditions in the proximal human gastrointestinal tract: An update. Pharm. Res. 2008, 25 (7), 1663− 1676. (66) Kalantzi, L.; Goumas, K.; Kalioras, V.; Abrahamsson, B.; Dressman, J. B.; Reppas, C. Characterization of the human upper gastrointestinal contents under conditions simulating bioavailability/ bioequivalence studies. Pharm. Res. 2006, 23 (1), 165−176. (67) Hegardt, F.; Dam, H. The solubility of cholesterol in aqueous solutions of bile salts and lecithin. Z. Ernaehrungswiss. 1971, 10 (3), 223−233. (68) Bashour, J. T.; Bauman, L. The solubility of cholesterol in bile salt solutions. J. Biol. Chem. 1937, 121 (1), 1−3. M


Article

Molecular Pharmaceutics (69) Roepke, R. R.; Mason, H. L. Micelle formation in aqueous solutions of bile salts. J. Biol. Chem. 1940, 133 (1), 103−108. (70) Sayyed-Ahmad, A.; Lichtenberger, L. M.; Gorfe, A. A. Structure and dynamics of cholic acid and dodecylphosphocholine-cholic acid aggregates. Langmuir 2010, 26 (16), 13407−13414. (71) Prakash, P.; Sayyed-Ahmad, A.; Zhou, Y.; Volk, D. E.; Gorenstein, D. G.; Dial, E.; Lichtenberger, L. M.; Gorfe, A. A. Aggregation behavior of ibuprofen, cholic acid and dodecylphosphocholine micelles. Biochim. Biophys. Acta, Biomembr. 2012, 1818 (12), 3040−3047. (72) Evans, D. F.; Wennerström, H. The Colloidal Domain: Where Physics, Chemistry, Biology, and Technology Meet; Wiley: 1999. (73) Cistola, D. P.; Hamilton, J. A.; Jackson, D.; Small, D. M. Ionization and Phase-Behavior of Fatty-Acids in Water - Application of the Gibbs Phase Rule. Biochemistry 1988, 27 (6), 1881−1888. (74) Hanahan, D. J.; Small, D. M. The Physical Chemistry of Lipids: From Alkanes to Phospholipids; Plenum Press: 1986. (75) Dennis, E. A. Micellization and Solubilization of Phospholipids by Surfactants. Adv. Colloid Interface Sci. 1986, 26 (2−4), 155−175. (76) Konikoff, F. M.; Danino, D.; Weihs, D.; Rubin, M.; Talmon, Y. Microstructural evolution of lipid aggregates in nucleating model and human biles visualized by cryogenic transmission electron microscopy. Hepatology 2000, 31 (2), 261−268. (77) Bourges, M.; Small, D. M.; Dervichian, D. G. Biophysics of lipidic associations. II. The ternary systems: cholesterol-lecithin-water. Biochim. Biophys. Acta, Lipids Lipid Metab. 1967, 137 (1), 157−167. (78) Lennernas, H. Modeling gastrointestinal drug absorption requires more in vivo biopharmaceutical data: experience from in vivo dissolution and permeability studies in humans. Curr. Drug Metab. 2007, 8 (7), 645−657. (79) Brener, W.; Hendrix, T. R.; Mchugh, P. R. Regulation of the Gastric-Emptying of Glucose. Gastroenterology 1983, 85 (1), 76−82. (80) Tsui, F. C.; Ojcius, D. M.; Hubbell, W. L. The Intrinsic Pka Values for Phosphatidylserine and Phosphatidylethanolamine in Phosphatidylcholine Host Bilayers. Biophys. J. 1986, 49 (2), 459−468. (81) Small, D. M.; Cabral, D. J.; Cistola, D. P.; Parks, J. S.; Hamilton, J. A. The ionization behavior of fatty acids and bile acids in micelles and membranes. Hepatology 1984, 4, 77S−79S. (82) Cistola, D. P.; Hamilton, J. A.; Jackson, D.; Small, D. M. Ionization and phase behavior of fatty acids in water: application of the Gibbs phase rule. Biochemistry 1988, 27 (6), 1881−1888. (83) Cabral, D. J.; Hamilton, J. A.; Small, D. M. The ionization behavior of bile acids in different aqueous environments. J. Lipid Res. 1986, 27 (3), 334−343. (84) Small, D. M.; Bourges, M. Lyotropic Paracrystalline Phases Obtained with Ternary and Quaternary Systems of Amphiphilic Substances in Water - Studies on Agreous Systems of Lecithin Bile Salt and Cholesterol. Mol. Cryst. 1966, 1 (4), 541−561. (85) Ladbrooke, B. D.; Williams, R. M.; Chapman, D. Studies on lecithin-cholesterol-water interactions by differential scanning calorimetry and X-ray diffraction. Biochim. Biophys. Acta, Biomembr. 1968, 150 (3), 333−340.

N


Computational Models of the Intestinal Environment. 3. The Impact

Recommend Documents