Prediction of the Passive Intestinal Absorption of Medicinal Plant Extract Constituents with the Parallel Artificial Membrane Permeability Assay (PAMPA).

At the early drug discovery stage, the high-throughput parallel artificial membrane permeability assay is one of the most frequently used in vitro models to predict transcellular passive absorption. While thousands of new chemical entities have been screened with the parallel artificial membrane permeability assay, in general, permeation properties of natural products have been scarcely evaluated. In this study, the parallel artificial membrane permeability assay through a hexadecane membrane was used to predict the passive intestinal absorption of a representative set of frequently occurring natural products. Since natural products are usually ingested for medicinal use as components of complex extracts in traditional herbal preparations or as phytopharmaceuticals, the applicability of such an assay to study the constituents directly in medicinal crude plant extracts was further investigated. Three representative crude plant extracts with different natural product compositions were chosen for this study. The first extract was composed of furanocoumarins (Angelica archangelica), the second extract included alkaloids (Waltheria indica), and the third extract contained flavonoid glycosides (Pueraria montana var. lobata). For each medicinal plant, the effective passive permeability values Pe (cm/s) of the main natural products of interest were rapidly calculated thanks to a generic ultrahigh-pressure liquid chromatography-UV detection method and because Pe calculations do not require knowing precisely the concentration of each natural product within the extracts. The original parallel artificial membrane permeability assay through a hexadecane membrane was found to keep its predictive power when applied to constituents directly in crude plant extracts provided that higher quantities of the extract were initially loaded in the assay in order to ensure suitable detection of the individual constituents of the extracts. Such an approach is thus valuable for the high-throughput, cost-effective, and early evaluation of passive intestinal absorption of active principles in medicinal plants. In phytochemical studies, obtaining effective passive permeability values of pharmacologically active natural products is important to predict if natural products showing interesting activities in vitro may have a chance to reach their target in vivo.

HDM-PAMPA to predict gastrointestinal absorption, binding percentage, equilibrium and kinetics constants with human serum albumin and using 2 end-point measurements.

The parallel artificial membrane permeability assay (PAMPA) is a high-throughput screening (HTS) technique developed to predict passive permeability through numerous different biological membranes, such as the gastrointestinal tract (GIT), the blood brain barrier (BBB), and the dermal layer. PAMPA is based on an artificial membrane, such as hexadecane (HDM), which separates two compartments (i.e., a donor and an acceptor compartment). In the present study, an HDM-PAMPA method was developed with human serum albumin (HSA) under iso-pH and gradient-pH conditions to predict the percentage of binding, dissociation/association constants (Kd and Ka, respectively) and dissociation/association kinetic rates (koff and kon, respectively) between a given drug and HSA. Thanks to the kinetic properties of PAMPA, a two end-point assay was implemented to obtain all three properties. The assay was used to measure basic, acidic, and amphoteric compounds. The protein was free in solution, allowing a direct comparison between this assay and equilibrium dialysis (ED). The developed PAMPA enabled screening of up to 96 compounds in a single run, generating valuable information on absorption and distribution in a high-throughput and high-repeatable manner.

Modification of a PAMPA model to predict passive gastrointestinal absorption and plasma protein binding.

The Parallel Artificial Membrane Permeability Assay (PAMPA) is a well-known high throughput screening (HTS) technique for predicting in vivo passive absorption. In this technique, two compartments are separated by an artificial membrane that mimics passive permeability through biological membranes such as the dermal layer, the gastrointestinal tract (GIT), and the blood brain barrier (BBB). In the present study, a hexadecane artificial membrane (HDM)-PAMPA was used to predict the binding of compounds towards the human plasma using a mixture of human serum albumin (HSA) and alpha-1-acid glycoprotein (AGP). The ratio of HSA and AGP was equivalent to that found in the human plasma for both proteins (∼20:1). A pH gradient (5.0-7.4) was performed to increase the screening capacity and overcome the issue of passive permeability for acidic and amphoteric compounds. With this assay, the prediction of passive GIT absorption was maintained and the compounds were discriminated according to their permeability (on a no-to-high scale). The plasma protein binding (PPB) was estimated via the correlation of the differences between the amount of compound crossing the artificial membrane in assays conducted with and without protein using only a two end-point measurement. The use of a mixture of HSA and AGP to modulate drug permeation was compared to the use of the same concentrations of HSA and AGP used separately. The addition of HSA alone in the acceptor compartment was sufficient for estimating PPB, while it was demonstrated that AGP alone could enable the estimation of AGP binding.

Predicting both passive intestinal absorption and the dissociation constant toward albumin using the PAMPA technique.

The parallel artificial membrane permeability assay (PAMPA) is a high-throughput screening (HTS) method that is widely used to predict in vivo passive permeability through biological barriers, such as the skin, the blood brain barrier (BBB) and the gastrointestinal tract (GIT). The PAMPA technique has also been used to predict the dissociation constant (Kd) between a compound and human serum albumin (HSA) while disregarding passive permeability. Furthermore, the assay is based on the use of two separate 5-point kinetic experiments, which increases the analysis time. In the present study, we adapted the hexadecane membrane (HDM)-PAMPA assay to both predict passive gastrointestinal absorption via the permeability coefficient logPe value and determine the Kd. Two assays were performed: one in the presence and one in the absence of HSA in the acceptor compartment. In the absence of HSA, logPe values were determined after a 4-h incubation time, as originally described, but the dimethylsulfoxide (DMSO) percentage and pH were altered to be compatible with the protein. In parallel, a second PAMPA assay was performed in the presence of HSA during a 16-h incubation period. By adding HSA, a variation in the amount of compound crossing the membrane was observed compared to the permeability measured in the absence of HSA. The concentration of compound reaching the acceptor compartment in each case was used to determine both parameters (logPe and logKd) using numerical simulations, which highlighted the originality of this method because these calculations required only two endpoint measurements instead of a complete kinetic study. It should be noted that the amount of compound that reaches the acceptor compartment in the presence of HSA is modulated by complex dissociation in the receptor compartment. Only compounds that are moderately bound to albumin (-3

Detection of metabolite induction in fungal co-cultures on solid media by high-throughput differential ultra-high pressure liquid chromatography-time-of-flight mass spectrometry fingerprinting.

Access to new biological sources is a key element of natural product research. A particularly large number of biologically active molecules have been found to originate from microorganisms. Very recently, the use of fungal co-culture to activate the silent genes involved in metabolite biosynthesis was found to be a successful method for the induction of new compounds. However, the detection and identification of the induced metabolites in the confrontation zone where fungi interact remain very challenging. To tackle this issue, a high-throughput UHPLC-TOF-MS-based metabolomic approach has been developed for the screening of fungal co-cultures in solid media at the petri dish level. The metabolites that were overexpressed because of fungal interactions were highlighted by comparing the LC-MS data obtained from the co-cultures and their corresponding mono-cultures. This comparison was achieved by subjecting automatically generated peak lists to statistical treatments. This strategy has been applied to more than 600 co-culture experiments that mainly involved fungal strains from the Fusarium genera, although experiments were also completed with a selection of several other filamentous fungi. This strategy was found to provide satisfactory repeatability and was used to detect the biomarkers of fungal induction in a large panel of filamentous fungi. This study demonstrates that co-culture results in consistent induction of potentially new metabolites.