Recent Experimental Developments in Studying Passive Membrane Transport of Drug Molecules

A methodology of quantifying membrane permeability based on returning probability theory and molecular dynamics simulation

We propose a theoretical approach to estimate the permeability coefficients of substrates (permeants) for crossing membranes from donor (D) phase to acceptor (A) phase by means of molecular dynamics (MD) simulation. A fundamental aspect of our approach involves reformulating the returning probability (RP) theory, a rigorous bimolecular reaction theory, to describe permeation phenomena. This reformulation relies on the parallelism between permeation and bimolecular reaction processes. In the present method, the permeability coefficient is represented in terms of the thermodynamic and kinetic quantities for the reactive (R) phase that exists within the inner region of a membrane. One can evaluate these quantities using multiple MD trajectories starting from phase R. We apply the RP theory to the permeation of ethanol and methylamine at different concentrations (infinitely dilute and 1 mol % conditions of permeants). Under the 1 mol% condition, the present method yields a larger permeability coefficient for ethanol (0.12 ± 0.01 cm s-1) than for methylamine (0.069 ± 0.006 cm s-1), while the values of the permeability coefficient are satisfactorily close to those obtained from the brute-force MD simulations (0.18 ± 0.03 and 0.052 ± 0.005 cm s-1 for ethanol and methylamine, respectively). Moreover, upon analyzing the thermodynamic and kinetic contributions to the permeability, we clarify that a higher concentration dependency of permeability for ethanol, as compared to methylamine, arises from the sensitive nature of ethanol's free-energy barrier within the inner region of the membrane against ethanol concentration.

Improving the Accuracy of Permeability Data to Gain Predictive Power: Assessing Sources of Variability in Assays Using Cell Monolayers

The ability to predict the rate of permeation of new compounds across biological membranes is of high importance for their success as drugs, as it determines their efficacy, pharmacokinetics, and safety profile. In vitro permeability assays using Caco-2 monolayers are commonly employed to assess permeability across the intestinal epithelium, with an extensive number of apparent permeability coefficient (Papp) values available in the literature and a significant fraction collected in databases. The compilation of these Papp values for large datasets allows for the application of artificial intelligence tools for establishing quantitative structure-permeability relationships (QSPRs) to predict the permeability of new compounds from their structural properties. One of the main challenges that hinders the development of accurate predictions is the existence of multiple Papp values for the same compound, mostly caused by differences in the experimental protocols employed. This review addresses the magnitude of the variability within and between laboratories to interpret its impact on QSPR modelling, systematically and quantitatively assessing the most common sources of variability. This review emphasizes the importance of compiling consistent Papp data and suggests strategies that may be used to obtain such data, contributing to the establishment of robust QSPRs with enhanced predictive power.

Transient theory for scanning electrochemical microscopy of biological membrane transport: uncovering membrane-permeant interactions

Scanning electrochemical microscopy (SECM) has emerged as a powerful method to quantitatively investigate the transport of molecules and ions across various biological membranes as represented by living cells. Advantageously, SECM allows for the in situ and non-destructive imaging and measurement of high membrane permeability under simple steady-state conditions, thereby facilitating quantitative data analysis. The SECM method, however, has not provided any information about the interactions of a transported species, i.e., a permeant, with a membrane through its components, e.g., lipids, channels, and carriers. Herein, we propose theoretically that SECM enables the quantitative investigation of membrane-permeant interactions by employing transient conditions. Specifically, we model the membrane-permeant interactions based on a Langmuir-type isotherm to define the strength and kinetics of the interactions as well as the concentration of interaction sites. Finite element simulation predicts that each of the three parameters uniquely affects the chronoamperometric current response of an SECM tip to a permeant. Significantly, this prediction implies that all three parameters are determinable from an experimental chronoamperometric response of the SECM tip. Complimentarily, the steady-state current response of the SECM tip yields the overall membrane permeability based on the combination of the three parameters. Interestingly, our simulation also reveals the optimum strength of membrane-permeant interactions to maximize the transient flux of the permeant from the membrane to the tip.

Observing mechanosensitive channels in action in living bacteria

Mechanosensitive (MS) channels act to protect the cytoplasmic membrane (CM) of living cells from environmental changes in osmolarity. In this report, we demonstrate the use of time-resolved second-harmonic light scattering (SHS) as a means of experimentally observing the relative state (open versus closed) of MS channels in living bacteria suspended in different buffer solutions. Specifically, the state of the MS channels was selectively controlled by changing the composition of the suspension medium, inducing either a transient or persistent osmotic shock. SHS was then used to monitor transport of the SHG-active cation, malachite green, across the bacterial CM. When MS channels were forced open, malachite green cations were able to cross the CM at a rate at least two orders of magnitude faster compared with when the MS channels were closed. These observations were corroborated using both numerical model simulations and complementary fluorescence experiments, in which the propensity for the CM impermeant cation, propidium, to stain cells was shown to be contingent upon the relative state of the MS channels (i.e., cells with open MS channels fluoresced red, cells with closed MS channels did not). Application of time-resolved SHS to experimentally distinguish MS channels opened via osmotic shock versus chemical activation, as well as a general comparison with the patch-clamp method is discussed.

Combining SILCS and Artificial Intelligence for High-Throughput Prediction of the Passive Permeability of Drug Molecules

Membrane permeability of drug molecules plays a significant role in the development of new therapeutic agents. Accordingly, methods to predict the passive permeability of drug candidates during a medicinal chemistry campaign offer the potential to accelerate the drug design process. In this work, we combine the physics-based site identification by ligand competitive saturation (SILCS) method and data-driven artificial intelligence (AI) to create a high-throughput predictive model for the passive permeability of druglike molecules. In this study, we present a comparative analysis of four regression models to predict membrane permeabilities of small druglike molecules; of the tested models, Random Forest was the most predictive yielding an R2 of 0.81 for the independent data set. The input feature vector used to train the developed prediction model includes absolute free energy profiles of ligands through a POPC-cholesterol bilayer based on ligand grid free energy (LGFE) profiles obtained from the SILCS approach. The use of the membrane free energy profiles from SILCS offers information on the physical forces contributing to ligand permeability, while the use of AI yields a more predictive model trained on experimental PAMPA permeability data for a collection of 229 molecules. This combination allows for rapid estimations of ligand permeability at a level of accuracy beyond currently available predictive models while offering insights into the contributions of the functional groups in the ligands to the permeability barrier, thereby offering quantitative information to facilitate rational ligand design.

Recent advances on molecular dynamics-based techniques to address drug membrane permeability with atomistic detail

Several factors affect the passive membrane permeation of small molecules, including size, charge, pH, or the presence of specific chemical groups. Understanding these features is paramount to identifying or designing drug candidates with optimal ADMET properties and this can be achieved through experimental/knowledge-based methodologies or using computational approaches. Empirical methods often lack detailed information about the underlying molecular mechanism. In contrast, Molecular Dynamics-based approaches are a powerful strategy, providing an atomistic description of this process. This technique is continuously growing, featuring new related methodologies. In this work, the recent advances in this research area will be discussed.

Designing a green-emitting viscosity-sensitive 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY) probe for plasma membrane viscosity imaging

Viscosity is a key characteristic of lipid membranes - it governs the passive diffusion of solutes and affects the lipid raft formation and membrane fluidity. Precise determination of viscosity values in biological systems is of great interest and viscosity-sensitive fluorescent probes offer a convenient solution for this task. In this work we present a novel membrane-targeting and water-soluble viscosity probe BODIPY-PM, which is based on one of the most frequently used probes BODIPY-C₁₀. Despite its regular use, BODIPY-C₁₀ suffers from poor integration into liquid-ordered lipid phases and lack of water solubility. Here, we investigate the photophysical characteristics of BODIPY-PM and demonstrate that solvent polarity only slightly affects the viscosity-sensing qualities of BODIPY-PM. In addition, with fluorescence lifetime imaging microscopy (FLIM), we imaged microviscosity in complex biological systems - large unilamellar vesicles (LUVs), tethered bilayer membranes (tBLMs) and live lung cancer cells. Our study showcases that BODIPY-PM preferentially stains the plasma membranes of live cells, equally well partitions into both liquid-ordered and liquid-disordered phases and reliably distinguishes lipid phase separation in tBLMs and LUVs.

The Transport of Charged Molecules across Three Lipid Membranes Investigated with Second Harmonic Generation

Subtle variations in the structure and composition of lipid membranes can have a profound impact on their transport of functional molecules and relevant cell functions. Here, we present a comparison of the permeability of bilayers composed of three lipids: cardiolipin, DOPG (1,2-dioleoyl-sn-glycero-3-phospho-(1'-rac-glycerol), and POPG (1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-(1'-rac-glycerol)). The adsorption and cross-membrane transport of a charged molecule, D289 (4-(4-diethylaminostyry)-1-methyl-pyridinium iodide), on vesicles composed of the three lipids were monitored by second harmonic generation (SHG) scattering from the vesicle surface. It is revealed that structural mismatching between the saturated and unsaturated alkane chains in POPG leads to relatively loose packing structure in the lipid bilayers, thus providing better permeability compared to unsaturated lipid bilayers (DOPG). This mismatching also weakens the efficiency of cholesterol in rigidifying the lipid bilayers. It is also revealed that the bilayer structure is somewhat disturbed by the surface curvature in small unilamellar vesicles (SUVs) composed of POPG and the conical structured cardiolipin. Such subtle information on the relationship between the lipid structure and the molecular transport capability of the bilayers may provide clues for drug development and other medical and biological studies.

MemCross: Accelerated Weight Histogram method to assess membrane permeability

Passive permeation events across biological membranes are determining steps in the pharmacokinetics of xenobiotics. To reach an accurate and rapid prediction of membrane permeation coefficients of drugs is a complex challenge, which can efficiently support drug discovery. Such predictions are indeed highly valuable as they may guide the selection of potential leads with optimum bioavailabilities prior to synthesis. Theoretical models exist to predict these coefficients. Many of them are based on molecular dynamics (MD) simulations, which allow calculation of permeation coefficients through the evaluation of both the potential of mean force (PMF) and the diffusivity profiles. However, these simulations still require intensive computational efforts, and novel methodologies should be developed and benchmarked. Free energy perturbation (FEP) method was recently shown to estimate PMF with a significantly reduced computational cost compared to the adaptive biasing force method. This benchmarking was achieved with small molecules, namely short-chain alcohols. Here, we show that to estimate the PMF of bulkier, drug-like xenobiotics, conformational sampling is a critical issue. To reach a sufficient sampling with FEP calculations requires a relatively long time-scale, which can lower the benefits related to the computational gain. In the present work, the Accelerated Weight Histogram (AWH) method was employed for the first time in all-atom membrane models. The AWH-based protocol, named MemCross, appears affordable to estimate PMF profiles of a series of drug-like xenobiotics, compared to other enhanced sampling methods. The continuous exploration of the crossing pathway by MemCross also allows modeling subdiffusion by computing fractional diffusivity profiles. The method is also versatile as its input parameters are largely insensitive to the molecule properties. It also ensures a detailed description of the molecule orientations along the permeation pathway, picturing all intermolecular interactions at an atomic resolution. Here, MemCross was applied on a series of 12 xenobiotics, including four weak acids, and a coherent structure-activity relationship was established.

Permeability Assessment of a High-Throughput Mucosal Platform

Permeability across cellular membranes is a key factor that influences absorption and distribution. Before absorption, many drugs must pass through the mucus barrier that covers all the wet surfaces of the human body. Cell-free in vitro tools currently used to evaluate permeability fail to effectively model the complexity of mucosal barriers. Here, we present an in vitro mucosal platform as a possible strategy for assessing permeability in a high-throughput setup. The PermeaPad 96-well plate was used as a permeability system and further coupled to a pathological, tridimensional mucus model. The physicochemical determinants predicting passive diffusion were determined by combining experimental and computational approaches. Drug solubility, size, and shape were found to be the critical properties governing permeability, while the charge of the drug was found to be influential on the interaction with mucus. Overall, the proposed mucosal platform could be a promising in vitro tool to model the complexity of mucosal tissues and could therefore be adopted for drug-permeability profiling.

Assessing the role of membrane lipids in the action of ruthenium(III) anticancer compounds

This work addresses the possible role of the cell membrane in the molecular mechanism of action of two salan-type ruthenium complexes that were previously shown to be active against human tumor cells, namely [Ru(III)(L1)(PPh₃)Cl] and [Ru(III)(L2)(PPh₃)Cl] (where L1 is 6,6'-(1R,2R)-cyclohexane-1,2-diylbis(azanediyl)bis(methylene)bis(3-methoxyphenol); and L2 is 2,2'-(1R,2R)-cyclohexane-1,2-diylbis(azanediyl)bis(methylene)bis(4-methoxyphenol)). One-component membrane models were first used, a disordered fluid bilayer of dioleoylphosphatodylcholine (DOPC), and an ordered rigid gel bilayer of dipalmitoylphosphatidylcholine. In addition, two quaternary mixtures of phosphatidylcholine, phosphatidylethanolamine, sphingomyelin and cholesterol were used to mimic the lipid composition either of mammalian plasma membrane (1:1:1:1 mol ratio) or of a cancer cell line membrane (36.2:23.6:6.8:33.4 mol ratio). The results show that both salan ligands L1 and L2 bind relatively strongly to DOPC bilayers, but without significantly affecting their structure. The ruthenium complexes have moderate affinity for DOPC. However, their impact on the membranes was notable, leading to a significant increase in the permeability of the lipid vesicles. None of the compounds compromised liposome integrity, as revealed by dynamic light scattering. Fluorescence spectroscopy studies revealed changes in the biophysical properties of all membrane models analyzed in the presence of the two complexes, which promoted an increased fluidity and water penetration into the lipid bilayer in the one-component systems. In the quaternary mixtures, one of the complexes had an analogous effect (increasing water penetration), whereas the other complex reorganized the liquid ordered and liquid disordered domains. Thus, small structural differences in the metal ligands may lead to different outcomes. To better understand the effect of these complexes in cancer cells, the membrane dipole potential was also measured. For both Ru complexes, an increase in the dipole potential was observed for the cancer cell membrane model, while no alteration was detected on the non-cancer plasma membrane model. Our results show that the action of the Ru(III) complexes tested involves changes in the biophysical properties of the plasma membrane, and that it also depends on membrane lipid composition, which is frequently altered in cancer cells when compared to their normal counterparts.

Monitoring membranes: The exploration of biological bilayers with second harmonic generation

Nature's seemingly controlled chaos in heterogeneous two-dimensional cell membranes stands in stark contrast to the precise, often homogeneous, environment in an experimentalist's flask or carefully designed material system. Yet cell membranes can play a direct role, or serve as inspiration, in all fields of biology, chemistry, physics, and engineering. Our understanding of these ubiquitous structures continues to evolve despite over a century of study largely driven by the application of new technologies. Here, we review the insight afforded by second harmonic generation (SHG), a nonlinear optical technique. From potential measurements to adsorption and diffusion on both model and living systems, SHG complements existing techniques while presenting a large exploratory space for new discoveries.

Multimodal Investigation into the Interaction of Quinacrine with Microcavity-Supported Lipid Bilayers

Quinacrine is a versatile drug that is widely recognized for its antimalarial action through its inhibition of the phospholipase enzyme. It also has antianthelmintic and antiprotozoan activities and is a strong DNA binder that may be used to combat multidrug resistance in cancer. Despite extensive cell-based studies, a detailed understanding of quinacrine's influence on the cell membrane, including permeability, binding, and rearrangement at the molecular level, is lacking. Herein, we apply microcavity-suspended lipid bilayers (MSLBs) as in vitro models of the cell membrane comprising DOPC, DOPC:Chol(3:1), and DOPC:SM:Chol(2:2:1) to investigate the influence of cholesterol and intrinsic phase heterogeneity induced by mixed-lipid composition on the membrane interactions of quinacrine. Using electrochemical impedance spectroscopy (EIS) and surface-enhanced Raman spectroscopy (SERS) as label-free surface-sensitive techniques, we have studied quinacrine interaction and permeability across the different MSLBs. Our EIS data reveal that the drug is permeable through ternary DOPC:SM:Chol and DOPC-only bilayer compositions. In contrast, the binary cholesterol/DOPC membrane arrested permeation, yet the drug binds or intercalates at this membrane as reflected by an increase in membrane impedance. SERS supported the EIS data, which was utilized to gain structural insights into the drug-membrane interaction. Our SERS data also provides a simple but powerful label-free assessment of drug permeation because a significant SERS enhancement of the drug's Raman signature was observed only if the drug accessed the plasmonic interior of the pore cavity passing through the membrane. Fluorescent lifetime correlation spectroscopy (FLCS) provides further biophysical insight, revealing that quinacrine binding increases the lipid diffusivity of DOPC and the ternary membrane while remarkably decreasing the lipid diffusivity of the DOPC:Chol membrane. Overall, because of its adaptability to multimodal approaches, the MSLB platform provides rich and detailed insights into drug-membrane interactions, making it a powerful tool for in vitro drug screening.

Calculation of Permeability Coefficients from Solute Equilibration Dynamics: An Assessment of Various Methods

Predicting the rate at which substances permeate membrane barriers in vivo is crucial for drug development. Permeability coefficients obtained from in vitro studies are valuable for this goal. These are normally determined by following the dynamics of solute equilibration between two membrane-separated compartments. However, the correct calculation of permeability coefficients from such data is not always straightforward. To address these problems, here we develop a kinetic model for solute permeation through lipid membrane barriers that includes the two membrane leaflets as compartments in a four-compartment model. Accounting for solute association with the membrane allows assessing various methods in a wide variety of conditions. The results showed that the often-used expression Papp= β × r/3 is inapplicable to very large or very small vesicles, to moderately or highly lipophilic solutes, or when the development of a significant pH gradient opposes the solute’s flux. We establish useful relationships that overcome these limitations and allow predicting permeability in compartmentalised in vitro or in vivo systems with specific properties. Finally, from the parameters for the interaction of the solute with the membrane barrier, we defined an intrinsic permeability coefficient that facilitates quantitative comparisons between solutes.

Cystic Fibrosis Mucus Model to Design More Efficient Drug Therapies

Mucus represents a strong barrier to tackle for oral or pulmonary administered drugs, especially in mucus-related disorders. This study uses a pathological cystic fibrosis (CF) mucus model to investigate how mucus impacts the passive diffusion of 45 ad hoc commercial drugs selected to maximize physicochemical variability. An in vitro mucosal surface was recreated by coupling the mucus model to a 96-well permeable support precoated with structured layers of phospholipids (parallel artificial membrane permeability assay, PAMPA). Results show that the mucus model was not a mere physical barrier but it behaves like an interactive filter. In nearly one-half of the investigated compounds, the diffusion was reduced by mucus, while other drugs were not sensitive to the mucus barriers. We also found that permeability can be enhanced when drug-calcium salts are formed. This was confirmed with cystic fibrosis sputum as a rough ex vivo model of CF mucus. Since the drug discovery process is characterized by a high rate of failure, the mucus platform is expected to provide an efficient support to early reduce the number of poor-performing drug candidates.

Mechanistic Understanding from Molecular Dynamics in Pharmaceutical Research 2: Lipid Membrane in Drug Design

We review the use of molecular dynamics (MD) simulation as a drug design tool in the context of the role that the lipid membrane can play in drug action, i.e., the interaction between candidate drug molecules and lipid membranes. In the standard "lock and key" paradigm, only the interaction between the drug and a specific active site of a specific protein is considered; the environment in which the drug acts is, from a biophysical perspective, far more complex than this. The possible mechanisms though which a drug can be designed to tinker with physiological processes are significantly broader than merely fitting to a single active site of a single protein. In this paper, we focus on the role of the lipid membrane, arguably the most important element outside the proteins themselves, as a case study. We discuss work that has been carried out, using MD simulation, concerning the transfection of drugs through membranes that act as biological barriers in the path of the drugs, the behavior of drug molecules within membranes, how their collective behavior can affect the structure and properties of the membrane and, finally, the role lipid membranes, to which the vast majority of drug target proteins are associated, can play in mediating the interaction between drug and target protein. This review paper is the second in a two-part series covering MD simulation as a tool in pharmaceutical research; both are designed as pedagogical review papers aimed at both pharmaceutical scientists interested in exploring how the tool of MD simulation can be applied to their research and computational scientists interested in exploring the possibility of a pharmaceutical context for their research.