The relationship between permeant size and permeability in lipid bilayer membranes

Reaction-diffusion modeling provides insights into biophysical carbon-concentrating mechanisms in land plants

Carbon-concentrating mechanisms (CCMs) have evolved numerous times in photosynthetic organisms. They elevate the concentration of CO2 around the carbon-fixing enzyme rubisco, thereby increasing CO2 assimilatory flux and reducing photorespiration. Biophysical CCMs, like the pyrenoid-based CCM (PCCM) of Chlamydomonas reinhardtii or carboxysome systems of cyanobacteria, are common in aquatic photosynthetic microbes, but in land plants appear only among the hornworts. To predict the likely efficiency of biophysical CCMs in C3 plants, we used spatially resolved reaction-diffusion models to predict rubisco saturation and light use efficiency. We found that the energy efficiency of adding individual CCM components to a C3 land plant is highly dependent on the permeability of lipid membranes to CO2, with values in the range reported in the literature that are higher than those used in previous modeling studies resulting in low light use efficiency. Adding a complete PCCM into the leaf cells of a C3 land plant was predicted to boost net CO2 fixation, but at higher energetic costs than those incurred by photorespiratory losses without a CCM. Two notable exceptions were when substomatal CO2 levels are as low as those found in land plants that already use biochemical CCMs and when gas exchange is limited, such as with hornworts, making the use of a biophysical CCM necessary to achieve net positive CO2 fixation under atmospheric CO2 levels. This provides an explanation for the uniqueness of hornworts' CCM among land plants and the evolution of pyrenoids multiple times.

Exploration of lipid bilayer mechanical properties using molecular dynamics simulation

Important biological structures known for their exceptional mechanical qualities, lipid bilayers are essential to many cellular functions. Fluidity, elasticity, permeability, stiffness, tensile strength, compressibility, shear viscosity, line tension, and curvature elasticity are some of the fundamental characteristics affecting their behavior. The purpose of this review is to examine these characteristics in more detail by molecular dynamics simulation, elucidating their importance and the elements that lead to their appearance in lipid bilayers. Comprehending the mechanical characteristics of lipid bilayers is critical for creating medications, drug delivery systems, and biomaterials that interact with biological membranes because it allows one to understand how these materials respond to different stresses and deformations. The influence of mechanical characteristics on important lipid bilayer properties is examined in this review. The mechanical properties of lipid bilayers were clarified through the use of molecular dynamics simulation analysis techniques, including bilayer thickness, stress-strain analysis, lipid bilayer area compressibility, membrane bending rigidity, and time- or ensemble-averaged the area per lipid evaluation. We explain the significance of molecular dynamics simulation analysis methods, providing important new information about the stability and dynamic behavior of the bilayer. In the end, we hope to use molecular dynamics simulation to provide a comprehensive understanding of the mechanical properties and behavior of lipid bilayers, laying the groundwork for further studies and applications. Taken together, careful investigation of these mechanical aspects deepens our understanding of the adaptive capacities and functional roles of lipid bilayers in biological environments.

Application of Generative Artificial Intelligence in Predicting Membrane Partitioning of Drugs: Combining Denoising Diffusion Probabilistic Models and MD Simulations Reduces the Computational Cost to One-Third

The optimal interaction of drugs with plasma membranes and membranes of subcellular organelles is a prerequisite for desirable pharmacology. Importantly, for drugs targeting the transmembrane lipid-facing sites of integral membrane proteins, the relative affinity of a drug to the bilayer lipids compared to the surrounding aqueous phase affects the partitioning, access, and binding of the drug to the target site. Molecular dynamics (MD) simulations, including enhanced sampling techniques such as steered MD, umbrella sampling (US), and metadynamics, offer valuable insights into the interactions of drugs with the membrane lipids and water in atomistic detail. However, these methods are computationally prohibitive for the high-throughput screening of drug candidates. This study shows that applying denoising diffusion probabilistic models (DDPMs), a generative AI method, to US simulation data reduces the computational cost significantly. Specifically, the models used only partial (one-third) data from the US simulations and reproduced the complete potential of mean force (PMF) profiles for three FDA-approved drugs (β2-adrenergic agonists) and ∼20 biologically relevant chemicals with known experimentally characterized bilayer locations. Intriguingly, the model can predict the solvation-free energies for partitioning and crossing the bilayer, preferred bilayer locations (low-energy well), and orientations of the ligands with high accuracy. The results indicate that DDPMs can be used to characterize the complete membrane partitioning profile of drug molecules using fewer umbrella sampling simulations at select positions along the bilayer normal (z-axis), irrespective of their amphiphilic-lipophilic-cephalophilic characteristics.

Bacterial adenine cross-feeding stems from a purine salvage bottleneck

Diverse ecosystems host microbial relationships that are stabilized by nutrient cross-feeding. Cross-feeding can involve metabolites that should hold value for the producer. Externalization of such communally valuable metabolites is often unexpected and difficult to predict. Previously, we discovered purine externalization by Rhodopseudomonas palustris by its ability to rescue an Escherichia coli purine auxotroph. Here we found that an E. coli purine auxotroph can stably coexist with R. palustris due to purine cross-feeding. We identified the cross-fed purine as adenine. Adenine was externalized by R. palustris under diverse growth conditions. Computational modeling suggested that adenine externalization occurs via diffusion across the cytoplasmic membrane. RNAseq analysis led us to hypothesize that adenine accumulation and externalization stem from a salvage pathway bottleneck at the enzyme encoded by apt. Ectopic expression of apt eliminated adenine externalization, supporting our hypothesis. A comparison of 49 R. palustris strains suggested that purine externalization is relatively common, with 16 strains exhibiting the trait. Purine externalization was correlated with the genomic orientation of apt, but apt orientation alone could not always explain purine externalization. Our results provide a mechanistic understanding of how a communally valuable metabolite can participate in cross-feeding. Our findings also highlight the challenge in identifying genetic signatures for metabolite externalization.

Predictions from First-Principles of Membrane Permeability to Small Molecules: How Useful Are They in Practice?

Predicting from first-principles the rate of passive permeation of small molecules across the biological membrane represents a promising strategy for screening lead compounds upstream in the drug-discovery and development pipeline. One popular avenue for the estimation of permeation rates rests on computer simulations in conjunction with the inhomogeneous solubility-diffusion model, which requires the determination of the free-energy change and position-dependent diffusivity of the substrate along the translocation pathway through the lipid bilayer. In this Perspective, we will clarify the physical meaning of the membrane permeability inferred from such computer simulations, and how theoretical predictions actually relate to what is commonly measured experimentally. We will also examine why these calculations remain both technically challenging and overly computationally expensive, which has hitherto precluded their routine use in nonacademic settings. We finally synopsize possible research directions to meet these challenges, increase the predictive power of physics-based rates of passive permeation, and, by ricochet, improve their practical usefulness.

APPLICATION OF MICELLAR LIQUID CHROMATOGRAPHY TO MODEL ECOTOXICITY OF PESTICIDES. COMPARISON WITH IMMOBILIZED ARTIFICIAL MEMBRANE CHROMATOGRAPHY AND N-OCTANOL-WATER PARTITIONING

The potential of Micellar Liquid Chromatography (MLC) to model ecotoxicological endpoints for a series of pesticides was investigated. To exploit the flexibility in MLC conditions, different surfactants were employed and retention mechanism was tracked and compared to Immobilized Artificial Membrane (IAM) chromatographic retention and n-octanol- water partitioning, logP. Neutral polyoxyethylene (23) lauryl ether (Brij-35), anionic sodium dodecyl sulfate (SDS) and cationic cetyltrimethylammonium bromide (CTAB) were used in presence of PBS at pH=7.40 and acetonitrile as organic modifier when necessary. Similarities/ dissimilarities between MLC retention and IAM or logP were investigated by Principal Component Analysis (PCA) and Liner Solvation Energy Relationships (LSER). LSER revealed that hydrogen bonding acidity is the most important factor for differentiation between MLC and IAM or logP. The impact of hydrogen bonding is exemplified in the relationships of MLC retention factors with IAM or logP, which necessitate the inclusion of a relevant descriptor. PCA further revealed that MLC retention factors are clustered together with IAM indices and logP within a broader ellipse formed by ecotoxicological endpoints, involving LC₅₀/ EC₅₀ values of six aquatic organisms namely Rainbow Trout, Fathead Minnow, Bluegill Sunfish, Sheepshead Minnow, Eastern Oyster and Water Flea as well as LD₅₀ values of Honey Bee, thus justifying their use to construct relevant models. Satisfactory specific models for individual organisms, as well as general fish models, were obtained, in most cases, upon combination of MLC retention factors with Molecular Weight (MW) or/ and hydrogen bond parameters. All models were evaluated and compared to previously reported IAM and logP based models using an external validation data set. Predictions with Brij-35 and SDS based models were comparable, although slightly inferior than those obtained with IAM, while they were in all cases better than those obtained with logP. CTAB led to a satisfactory prediction model for Honey Bee, but it was found less suitable for aquatic organisms.

Lessons for Oral Bioavailability: How Conformationally Flexible Cyclic Peptides Enter and Cross Lipid Membranes

Cyclic peptides extend the druggable target space due to their size, flexibility, and hydrogen-bonding capacity. However, these properties impact also their passive membrane permeability. As the "journey" through membranes cannot be monitored experimentally, little is known about the underlying process, which hinders rational design. Here, we use molecular simulations to uncover how cyclic peptides permeate a membrane. We show that side chains can act as "molecular anchors", establishing the first contact with the membrane and enabling insertion. Once inside, the peptides are positioned between headgroups and lipid tails─a unique polar/apolar interface. Only one of two distinct orientations at this interface allows for the formation of the permeable "closed" conformation. In the closed conformation, the peptide crosses to the lower leaflet via another "anchoring" and flipping mechanism. Our findings provide atomistic insights into the permeation process of flexible cyclic peptides and reveal design considerations for each step of the process.

Physicochemical and biopharmaceutical aspects influencing skin permeation and role of SLN and NLC for skin drug delivery

The skin is a complex and multifunctional organ, in which the static versus dynamic balance is responsible for its constant adaptation to variations in the external environment that is continuously exposed. One of the most important functions of the skin is its ability to act as a protective barrier, against the entry of foreign substances and against the excessive loss of endogenous material. Human skin imposes physical, chemical and biological limitations on all types of permeating agents that can cross the epithelial barrier. For a molecule to be passively permeated through the skin, it must have properties, such as dimensions, molecular weight, pKa and hydrophilic-lipophilic gradient, appropriate to the anatomy and physiology of the skin. These requirements have limited the number of commercially available products for dermal and transdermal administration of drugs. To understand the mechanisms involved in the drug permeation process through the skin, the approach should be multidisciplinary in order to overcome biological and pharmacotechnical barriers. The study of the mechanisms involved in the permeation process, and the ways to control it, can make this route of drug administration cease to be a constant promise and become a reality. In this work, we address the physicochemical and biopharmaceutical aspects encountered in the pathway of drugs through the skin, and the potential added value of using solid lipid nanoparticles (SLN) and nanostructured lipid vectors (NLC) to drug permeation/penetration through this route. The technology and architecture for obtaining lipid nanoparticles are described in detail, namely the composition, production methods and the ability to release pharmacologically active substances, as well as the application of these systems in the vectorization of various pharmacologically active substances for dermal and transdermal applications. The characteristics of these systems in terms of dermal application are addressed, such as biocompatibility, occlusion, hydration, emollience and the penetration of pharmacologically active substances. The advantages of using these systems over conventional formulations are described and explored from a pharmaceutical point of view.

Alkane/Water Partition Coefficient Calculation Based on the Modified AM1 Method and Internal Hydrogen Bonding Sampling Using COSMO-RS

We introduce a physics-based model for calculating partition coefficients of solutes between water and alkanes, using a combination of a semi-empirical method for COSMO charge density calculation and statistical sampling of internal hydrogen bonds (IHBs). We validate the model on the experimental partition data (∼3500 molecules) of small organics, drug-like molecules, and statistical assessment of modeling of proteins and ligand drugs. The model combines two novel algorithms: a bond-correction method for improving the calculation of COSMO charge density from AM1 calculations and a sampling method to deal with IHBs. From a comparison of simulated and experimental partition coefficients, we find a root-mean-square deviation of roughly one log 10 unit. From IHB analysis, we know that IHBs can be present in two states: open (in water) and closed (in apolar solvent). The difference can lead to a shift of as much as two log 10 units per IHB; not taking this effect into account can lead to substantial errors. The method takes a few minutes of calculation time on a single core, per molecule. Although this is still much slower than quantitative structure–activity relationship, it is much faster than molecular simulations and can be readily incorporated into any screening method.

Recent Experimental Developments in Studying Passive Membrane Transport of Drug Molecules

The ability to measure the passive membrane permeation of drug-like molecules is of fundamental biological and pharmaceutical importance. Of significance, passive diffusion across the cellular membranes plays an effective role in the delivery of many pharmaceutical agents to intracellular targets. Hence, approaches for quantitative measurement of membrane permeability have been the topics of research for decades, resulting in sophisticated biomimetic systems coupled with advanced techniques. In this review, recent developments in experimental approaches along with theoretical models for quantitative and real-time analysis of membrane transport of drug-like molecules through mimetic and living cell membranes are discussed. The focus is on time-resolved fluorescence-based, surface plasmon resonance, and second-harmonic light scattering approaches. The current understanding of how properties of the membrane and permeant affect the permeation process is discussed.

Blood-Brain Barrier (BBB) Permeability and Transport Measurement In Vitro and In Vivo

Quantification of the blood-brain barrier (BBB) permeability and transport in brain tissue is crucial in understanding brain disorders and developing systemic and non-systemic drug delivery strategies to the brain. This chapter summarizes BBB permeability measurement in vitro (Part I) and the in vivo non-invasive methods for quantifying the BBB permeability to solutes and brain tissue transport in rat brain by employing intravital multiphoton microscopy and a curving fitting method by using an unsteady mass transfer mathematical model (Part II).

Stability, Structure, and Permeability Studies of Copper Tripeptide Species in Aqueous Solution

The use of copper complexes to alleviate inflammation associated with rheumatoid arthritis (RA) is well known. This study focuses on designing a new drug that could be used to increase the bioavailability of copper and hence be more effective. The ligand chosen was sarcosyl-l-lysyl-l-lysine (Sar-Lys-Lys). The thermodynamic stability of H+, CuII, NiII, and ZnII complexes of Sar-Lys-Lys was measured in an aqueous solution at 298±0.01°C and an ionic strength of 0.15M (NaCl) using glass electrode potentiometry. UV-Vis, ESR, and 1H NMR spectroscopy was used to investigate the solution structures of the different species. At physiological pH, the ligand was found to coordinate via two amide nitrogens, the terminal amine, and the terminal carboxy group. The ε-amino group of lysine did not coordinate with the metal ion. Dermal absorption is the preferred method of administration and so this study used partition coefficients and tissue permeability studies to assess the bioavailability of the different complexes. Sar-Lys-Lys was found to increase the copper lipophilicity by a factor of 10 and increased tissue permeability by 30%.

Modeling the interaction of amphiphilic polymer nanoparticles with biomembranes to Guide rational design of drug delivery systems

Nanoparticle assisted drug delivery to the cytoplasm is limited by sequestration of nanoparticles in endosomes. Endosomal escape through polymer-induced membrane destabilization is one of a few well characterized mechanisms to overcome it. Aiming to utilize this method in vivo, it is necessary to understand how modulating the structural and chemical features of the polymer and the presence of proteins in biological fluids can affect this activity. Here, as a model for the endosomal membrane, we use the membrane of red blood cells to evaluate the membrane destabilization ability of a model amphiphilic polymer in the presence of blood plasma using a hemolysis assay. This allows determination of red blood cells membrane permeabilization through the quantification of hemoglobin leakage. Our results showed a strong inhibitory effect of plasma, and that hemolytic activity can be improved by chemical modification of the polymeric micelle, reducing its interaction with plasma proteins. Finally, a second mechanism of pH-induced direct diffusion is proposed and tested using an oil/water partitioning model. These results offer a body of knowledge to improve delivery of drugs across biological membranes using carefully designed polymeric nanocarriers.

Understanding and Improving the Membrane Permeability of VH032-Based PROTACs

Proteolysis targeting chimeras (PROTACs) are catalytic heterobifunctional molecules that can selectively degrade a protein of interest by recruiting a ubiquitin E3 ligase to the target, leading to its ubiquitylation and degradation by the proteasome. Most degraders lie outside the chemical space associated with most membrane-permeable drugs. Although many PROTACs have been described with potent activity in cells, our understanding of the relationship between structure and permeability in these compounds remains limited. Here, we describe a label-free method for assessing the permeability of several VH032-based PROTACs and their components by combining a parallel artificial membrane permeability assay (PAMPA) and a lipophilic permeability efficiency (LPE) metric. Our results show that the combination of these two cell-free membrane permeability assays provides new insight into PROTAC structure–permeability relationships and offers a conceptual framework for predicting the physicochemical properties of PROTACs in order to better inform the design of more permeable and more effective degraders.

Translocation of a hydroxyl functionalized carbon dot across a lipid bilayer: an all-atom molecular dynamics simulation study

Passive permeation of CD across lipid bilayer is almost impossible. Forced permeation results membrane rupture.

Understanding Cell Penetration of Cyclic Peptides

Approximately 75% of all disease-relevant human proteins, including those involved in intracellular protein-protein interactions (PPIs), are undruggable with the current drug modalities (i.e., small molecules and biologics). Macrocyclic peptides provide a potential solution to these undruggable targets because their larger sizes (relative to conventional small molecules) endow them the capability of binding to flat PPI interfaces with antibody-like affinity and specificity. Powerful combinatorial library technologies have been developed to routinely identify cyclic peptides as potent, specific inhibitors against proteins including PPI targets. However, with the exception of a very small set of sequences, the vast majority of cyclic peptides are impermeable to the cell membrane, preventing their application against intracellular targets. This Review examines common structural features that render most cyclic peptides membrane impermeable, as well as the unique features that allow the minority of sequences to enter the cell interior by passive diffusion, endocytosis/endosomal escape, or other mechanisms. We also present the current state of knowledge about the molecular mechanisms of cell penetration, the various strategies for designing cell-permeable, biologically active cyclic peptides against intracellular targets, and the assay methods available to quantify their cell-permeability.

Modulation of membrane permeability by carbon dioxide

Promoting drug delivery across the biological membrane is a common strategy to improve bioavailability. Inspired by the observation that carbonated alcoholic beverages can increase the absorption rate of ethanol, we speculate that carbon dioxide (CO₂ ) molecules could also enhance membrane permeability to drugs. In the present work, we have investigated the effect of CO₂ on the permeability of a model membrane formed by 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine lipids to three drug-like molecules, namely, ethanol, 2',3'-dideoxyadenosine, and trimethoprim. The free-energy and fractional-diffusivity profiles underlying membrane translocation were obtained from μs-timescale simulations and combined in the framework of the fractional solubility-diffusion model. We find that addition of CO₂ in the lipid environment results in an increase of the membrane permeability to the three substrates. Further analysis of the permeation events reveals that CO₂ expands and loosens the membrane, which, in turn, facilitates permeation of the drug-like molecules. © 2019 Wiley Periodicals, Inc.

PerMM: A Web Tool and Database for Analysis of Passive Membrane Permeability and Translocation Pathways of Bioactive Molecules

The PerMM web server and database were developed for quantitative analysis and visualization of passive translocation of bioactive molecules across lipid membranes. The server is the first physics-based web tool that calculates membrane binding energies and permeability coefficients of diverse molecules through artificial and natural membranes (phospholipid bilayers, PAMPA-DS, blood-brain barrier, and Caco-2/MDCK cell membranes). It also visualizes the transmembrane translocation pathway as a sequence of translational and rotational positions of a permeant as it moves across the lipid bilayer, along with the corresponding changes in solvation energy. The server can be applied for prediction of permeability coefficients of compounds with diverse chemical scaffolds to facilitate selection and optimization of potential drug leads. The complementary PerMM database allows comparison of computationally and experimentally determined permeability coefficients for more than 500 compounds in different membrane systems. The website and database are freely accessible at https://permm.phar.umich.edu/ .

Physics-Based Method for Modeling Passive Membrane Permeability and Translocation Pathways of Bioactive Molecules

Assessment of permeability is a critical step in the drug development process for selection of drug candidates with favorable ADME properties. We have developed a novel physics-based method for fast computational modeling of passive permeation of diverse classes of molecules across lipid membranes. The method is based on heterogeneous solubility-diffusion theory and operates with all-atom 3D structures of solutes and the anisotropic solvent model of the lipid bilayer characterized by transbilayer profiles of dielectric and hydrogen bonding capacity parameters. The optimal translocation pathway of a solute is determined by moving an ensemble of representative conformations of the molecule through the dioleoyl-phosphatidylcholine (DOPC) bilayer and optimizing their rotational orientations in every point of the transmembrane trajectory. The method calculates (1) the membrane-bound state of the solute molecule; (2) free energy profile of the solute along the permeation pathway; and (3) the permeability coefficient obtained by integration over the transbilayer energy profile and assuming a constant size-dependent diffusivity along the membrane normal. The accuracy of the predictions was evaluated against experimental permeability coefficients measured in pure lipid membranes (for 78 compounds, R² was 0.88 and rmse was 1.15 log units), PAMPA-DS (for 280 compounds, R² was 0.75 and rmse was 1.59 log units), BBB (for 182 compounds, R² was 0.69 and rmse was 0.87 log units), and Caco-2/MDCK assays (for 165 compounds, R² was 0.52 and rmse was 0.89 log units).

Immobilized artificial membrane chromatography as a tool for the prediction of ecotoxicity of pesticides

The potential of Immobilized Artificial Membrane (IAM) chromatography to predict ecotoxicological endpoints of pesticides was investigated. For this purpose, retention factors of 39 structurally-diverse pesticides were measured on an IAM stationary phase. A representative test set of 6 pesticides was carefully selected. The training set, involving the remaining pesticides for which experimental data were available, served to establish linear IAM models with LC₅₀/EC₅₀ values in a series of aquatic organisms involving Rainbow Trout, Fathead Minnow, Bluegill Sunfish, Sheepshead Minnow, Eastern Oyster and Water Flea as well as LD₅₀ values in honey bee, compiled from literature sources. For reasons of comparison, corresponding models were derived by replacing IAM retention factors with octanol-water partition coefficients (logP). Considering the similar regression equations obtained for the 4 fish species, general models to predict toxicity in fish were established. Most models were improved upon inclusion of additional physicochemical parameters. The positive contribution of Molecular Weight to ecotoxicity along with the positive sign of hydrogen bond indices in most cases implies that toxic action is manifested mainly by accumulation on the membrane rather than through diffusion across them. IAM models are generally followed by better statistics and superior predictive performance than those based on experimental or computed logP. Predictions based on IAM chromatography were comparable or even superior with those performed by EPI Suite Software. Hence, IAM retention factors are suggested as promising indices in order to screen or rank chemicals with respect to their ecotoxicological risk, especially in the case of new entities.

Prediction of Membrane Permeation of Drug Molecules by Combining an Implicit Membrane Model with Machine Learning

Lipid membrane permeation of drug molecules was investigated with Heterogeneous Dielectric Generalized Born (HDGB)-based models using solubility-diffusion theory and machine learning. Free energy profiles were obtained for neutral molecules by the standard HDGB and Dynamic HDGB (DHDGB) to account for the membrane deformation upon insertion of drugs. We also obtained hybrid free energy profiles where the neutralization of charged molecules was taken into account upon membrane insertion. The evaluation of the predictions was done against experimental permeability coefficients from Parallel Artificial Membrane Permeability Assays (PAMPA), and effects of partial charge sets, CGenFF, AM1-BCC, and OPLS, on the performance of the predictions were discussed. (D)HDGB-based models improved the predictions over the two-state implicit membrane models, and partial charge sets seemed to have a strong impact on the predictions. Machine learning increased the accuracy of the predictions, although it could not outperform the physics-based approach in terms of correlations.

Mathematical Modeling of Release Kinetics from Supramolecular Drug Delivery Systems

Embedding of active substances in supramolecular systems has as the main goal to ensure the controlled release of the active ingredients. Whatever the final architecture or entrapment mechanism, modeling of release is challenging due to the moving boundary conditions and complex initial conditions. Despite huge diversity of formulations, diffusion phenomena are involved in practically all release processes. The approach in this paper starts, therefore, from mathematical methods for solving the diffusion equation in initial and boundary conditions, which are further connected with phenomenological conditions, simplified and idealized in order to lead to problems which can be analytically solved. Consequently, the release models are classified starting from the geometry of diffusion domain, initial conditions, and conditions on frontiers. Taking into account that practically all solutions of the models use the separation of variables method and integral transformation method, two specific applications of these methods are included. This paper suggests that "good modeling practice" of release kinetics consists essentially of identifying the most appropriate mathematical conditions corresponding to implied physicochemical phenomena. However, in most of the cases, models can be written but analytical solutions for these models cannot be obtained. Consequently, empiric models remain the first choice, and they receive an important place in the review.

Effects of lipid composition on membrane permeation

Passive permeation through lipid membranes is an essential process in biology. In vivo membranes typically consist of mixtures of lamellar and nonlamellar lipids. Lamellar lipids are characterized by their tendency to form lamellar sheet-like structures, which are predominant in nature. Nonlamellar lipids, when isolated, instead form more geometrically complex nonlamellar phases. While mixed lamellar/nonlamellar lipid membranes tend to adopt the ubiquitous lamellar bilayer structure, the presence of nonlamellar lipids is known to have profound effects on key membrane properties, such as internal distributions of stress and elastic properties, which in turn may alter related biological processes. This work focuses on one such process, i.e., permeation, by utilising atomistic molecular dynamics simulations in order to obtain transfer free energy profiles, diffusion profiles and permeation coefficients for a series of thirteen small molecules and drugs. Each permeant is tested on two bilayer membranes of different lipid composition, i.e., purely lamellar and mixed lamellar/nonlamellar. Our results indicate that the presence of nonlamellar lipids reduces permeation for smaller molecules (molecular weight < 100) but facilitates it for the largest ones (molecular weight > 100). This work represents an advancement towards the development of more realistic in silico permeability assays, which may have a substantial future impact in the area of rational drug design.

Contribution assessment of multiparameter optimization descriptors in CNS penetration

Assessment of the influence of six physicochemical properties used in the multiparameter optimization (MPO) approach for chemical penetration of the blood-brain barrier was carried out by means of application of logistic regression and multiple linear regression, using a data set of 578 diverse chemicals. It was found that use of an aggregation MPO-score descriptor did not give satisfactory results with central nervous system (CNS)/non-CNS classification. Thus an application of the MPO approach for CNS penetration is ambiguous. An alternative to the MPO approach in this work contains detailed (quantitative) structure-activity relationship analysis using a number of methods (linear discriminant analysis, random forest, support vector machine, Gaussian process). Three properties (molecular weight, number of H-bond donors and octanol-water partition coefficient) yielded optimal categorical models with modest statistical parameters (accuracy 0.730-0.765 for CNS/non-CNS classification). The poor statistics of regression models for the common data set suggested the presence of subsets with different mechanisms of penetrations. Based on graphic comparison of experimental and calculated C_u,b values, subset clusters have satisfactory statistics. The regression models obtained allowed the estimation of descriptor contributions in log C_u,b. This means that medicinal chemists now have a simple additive scheme for at least preliminary quantitative assessment of this important pharmacokinetic parameter.

Skin Permeation Enhancement in Aqueous Solution: Correlation With Equilibrium Enhancer Concentration and Octanol/Water Partition Coefficient

The effectiveness of skin penetration enhancers and the enhancer concentration required for effective skin permeation enhancement are difficult to predict. A comprehensive quantitative structure-enhancement relationship of chemical penetration enhancers for skin permeation is not currently available. The present study (a) investigated the relationship between skin permeation enhancement and chemical enhancer concentration and (b) examined a simple quantitative structure-enhancement relationship for predicting skin permeation enhancement to guide enhancer formulation development. In the present analysis, data from previous skin permeation studies that used the symmetric/equilibrium configuration and skin parallel pathway model were summarized to determine the relationship between enhancement factor and enhancer concentration. Under the equilibrium conditions, semilogarithmic linear relationships between enhancement factor (E) and enhancer aqueous concentration (C) were observed and an enhancer potency parameter (α) was defined. A correlation between the potency parameter α and enhancer octanol/water partition coefficient (Koct) was obtained. The enhancement factor relationship was derived: Log E = 0.32 ∙ C ∙ Koct. The results suggest that a "threshold" of (C ∙ Koct) > 0.5 M is required to induce effective skin permeation enhancement under these conditions. Consistent with the analyses in previous studies, the data suggest that octanol represents the skin barrier microenvironment for the penetration enhancers.

Carbonate Disequilibrium in the External Boundary Layer of Freshwater Chrysophytes: Implications for Contaminant Uptake

The interplay between biological and chemical reactions in the freshwater phytoplankton phycosphere and the resulting modulations of contaminant speciation and uptake is poorly characterized. Here we modeled the effect of algal C and N uptake on carbonate cycling and speciation of selected contaminants in the phycosphere (external boundary layer) of chrysophytes, a key phytoplankton group in oligotrophic systems. We calculated an enrichment in H⁺ concentration relative to that in the bulk solution (pH 7.0) of approximately 40% or a depletion of approximately 30% for NH₄⁺ or NO₃^--grown cells, respectively, at the algal membrane surface of a 5-μm radius cell. Such changes are mainly due to direct H⁺ uptake or release at the plasmalemma if NO₃^- or NH₄⁺ is the N source, respectively. Due to these pH changes in the external boundary layer, competition between H⁺ and metals for uptake is enhanced, for NH₄⁺-grown cells which contributes to a decrease in potential metal uptake. Our model suggests that the uptake of protonated weakly acidic organic acids (HA) is greater in NH₄⁺-grown cells compared to that in NO₃^--grown cells. The account of chemical reactions in the algal external boundary layer could improve ecological risk assessments for a wide range of contaminants.

Link between Membrane Composition and Permeability to Drugs

Prediction of membrane permeability to small molecules represents an important aspect of drug discovery. First-principles calculations of this quantity require an accurate description of both the thermodynamics and kinetics that underlie translocation of the permeant across the lipid bilayer. In this contribution, the membrane permeability to three drugs, or drug-like molecules, namely, 9-anthroic acid (ANA), 2',3'-dideoxyadenosine (DDA), and hydrocortisone (HYL), are estimated in a pure 1-palmitoyl-2-oleoylphosphatidylcholine (POPC) and in a POPC:cholesterol (2:1) mixture. On the basis of independent 2-5-μs free-energy calculations combined with a time-fractional Smoluchowski determination of the diffusivity, the estimated membrane permeabilities to these chemically diverse permeants fall within an order of magnitude from the experimental values obtained in egg-lecithin bilayers, with the exception of HYL in pure POPC. This exception is particularly interesting because the calculated permeability of the sterol-rich bilayer to HYL, in close agreement with the experimental value, is about 600 times lower than that of the pure POPC bilayer to HYL. In contrast, the permeabilities to ANA and DDA differ by less than a factor of 10 between the pure POPC and POPC:cholesterol bilayers. The unusual behavior of HYL, a large, amphiphilic compound, may be linked with the longer range perturbation of the lipid bilayer it induces, compared to ANA and DDA, suggestive of a possibly different translocation mechanism. We find that the tendency of lower permeabilities of the POPC:cholesterol bilayer relative to those of the pure POPC one is a consequence of increased free-energy barriers. Beyond reporting accurate estimates of the membrane permeability, the present contribution also demonstrates that rigorous free-energy calculations and a fractional-diffusion model are key in revealing the molecular phenomena linking the composition of a membrane to its permeability to drugs.

Impact of Dynamically Exposed Polarity on Permeability and Solubility of Chameleonic Drugs Beyond the Rule of 5

Conformational flexibility has been proposed to significantly affect drug properties outside rule-of-5 (Ro5) chemical space. Here, we investigated the influence of dynamically exposed polarity on cell permeability and aqueous solubility for a structurally diverse set of drugs and clinical candidates far beyond the Ro5, all of which populated multiple distinct conformations as revealed by X-ray crystallography. Efflux-inhibited (passive) Caco-2 cell permeability correlated strongly with the compounds' minimum solvent-accessible 3D polar surface areas (PSA), whereas aqueous solubility depended less on the specific 3D conformation. Inspection of the crystal structures highlighted flexibly linked aromatic side chains and dynamically forming intramolecular hydrogen bonds as particularly effective in providing "chameleonic" properties that allow compounds to display both high cell permeability and aqueous solubility. These structural features, in combination with permeability predictions based on the correlation to solvent-accessible 3D PSA, should inspire drug design in the challenging chemical space far beyond the Ro5.

Predicting apparent passive permeability of Caco-2 and MDCK cell-monolayers: A mechanistic model

Experimentally derived apparent permeabilities, Papp, through cell monolayers such as Caco-2 and MDCK are considered to be an in-vitro gold standard for assessing the uptake efficiency of drugs. Here, we present a mechanistic model that describes 'passive' Papp values (i.e., neglecting active transport) by accounting for the different resistances solutes encounter when permeating a cell monolayer. We described three parallel permeation pathways, namely a cytosolic-, paracellular-, and lateral route, each of which consists of a number of serial resistances. These resistances were accounted for via a mechanistic depiction of the underlying processes that are largely based on literature work. For the present Papp dataset, about as much chemicals are dominated by the cytosolic route as were dominated by the paracellular route, while the lateral route was negligible. For the cytosolic route by far the most chemicals found their main resistance in the various water layers and not in the membrane. Although correlations within the subclasses of chemicals dominated by a specific permeation route were rather poor, we could overall satisfyingly predict Papp for 151 chemicals at a pH of 7.4 (R2 = 0.77, RMSE = 0.48). For a specific evaluation of the intrinsic membrane permeability, Pm, a second experimental dataset based on experiments with black lipid membranes, BLM, was evaluated. Pm could be predicted for 37 chemicals with R2 = 0.91 and RMSE = 0.64 log units.

A Universal Correlation Predicts Permeability Coefficients of Fluid- and Gel-Phase Phospholipid and Phospholipid-Cholesterol Bilayers for Arbitrary Solutes

The permeability of gel-phase phospholipids is typically about an order of magnitude lower than that of the same compositions in the fluid phase, yet a quantitative description of the ordering factors leading to this difference has been elusive. The present analysis examines these factors with particular focus on the area per phospholipid chain, Ac, and its relationship to the minimum area per molecule in the crystalline state, A0. It is shown that fluid- and gel-phase phospholipid permeabilities can be reconciled by postulating a minimum area per chain Ac,0 = 17.1 Å(2), substantially less than one would estimate by dividing the accepted value A0 = 40.8 Å(2) by 2. An extended data set of phospholipid and phospholipid-cholesterol bilayer permeability data extending over 9 orders of magnitude is analyzed and correlated according to the developed relationship (N = 85, s = 0.3024, r(2) = 0.9332). Individual permeability values are consequently predicted to within an average deviation of 10(0.3024) or about a factor of 2. The analysis is broadly applicable in the fluid phase but is restricted to gel-phase phospholipid compositions that do not contain cholesterol. Guidance for the latter scenario is provided.

Modeling the Kinetics of the Permeation of Antibacterial Agents into Growing Bacteria and Its Interplay with Efflux

A mathematical model of the passive permeation of a novel solute into bacteria that explicitly accounts for intracellular dilution through growth was developed. A bacterial cell envelope permeability coefficient of approximately >10^-8 cm² · s^-1 is predicted to ensure passive permeation into rapidly replicating bacterial cells. The relative importance of the permeability coefficients of the cytoplasmic and outer membranes of Gram-negative bacteria in determining the overall envelope permeability coefficient was analyzed quantitatively. A mathematical description of the balance between passive influx and active efflux was also developed and shows that bacterial expansion through growth can usually be neglected for compounds likely to be prepared in antibacterial drug discovery programs and the balance between passive inward permeation and active outwardly directed efflux predominates. A new parameter, efflux efficiency (η, where η is equal to k/P, in which k is the rate coefficient for the efflux pump and P is the permeability coefficient for the membrane across which the pump acts), is introduced, and the consequences for the efficiency of efflux pumping by a single pump, two pumps in parallel across either the cytoplasmic or the outer membrane, and two pumps in series, one across the cytoplasmic membrane and one across the outer membrane of Gram-negative bacteria, are explored. The results, showing additive efficiency for two pumps acting across a single membrane and multiplicative efficiency for two pumps acting in series across the cytoplasmic and outer membranes, can be quantitatively related to the ratios between MICs measured against pump-sufficient and pump deletion strains and agree with those of previous experimental and theoretical studies.

Triggered Release from Lipid Bilayer Vesicles by an Artificial Transmembrane Signal Transduction System

The on-demand delivery of drug molecules from nanoscale carriers with spatiotemporal control is a key challenge in modern medicine. Here we show that lipid bilayer vesicles (liposomes) can be triggered to release an encapsulated molecular cargo in response to an external control signal by employing an artificial transmembrane signal transduction mechanism. A synthetic signal transducer embedded in the lipid bilayer membrane acts as a switchable catalyst, catalyzing the formation of surfactant molecules inside the vesicle in response to a change in external pH. The surfactant permeabilizes the lipid bilayer membrane to facilitate release of an encapsulated hydrophilic cargo. In the absence of the pH control signal, the catalyst is inactive, and the cargo remains encapsulated within the vesicle.

Physical insights into the blood-brain barrier translocation mechanisms

The number of individuals suffering from diseases of the central nervous system (CNS) is growing with an aging population. While candidate drugs for many of these diseases are available, most of these pharmaceutical agents cannot reach the brain rendering most of the drug therapies that target the CNS inefficient. The reason is the blood-brain barrier (BBB), a complex and dynamic interface that controls the influx and efflux of substances through a number of different translocation mechanisms. Here, we present these mechanisms providing, also, the necessary background related to the morphology and various characteristics of the BBB. Moreover, we discuss various numerical and simulation approaches used to study the BBB, and possible future directions based on multi-scale methods. We anticipate that this review will motivate multi-disciplinary research on the BBB aiming at the design of effective drug therapies.

Scalable Synthesis and Purification of Acetylated Phosphatidyl Choline Headgroup

The acetylated headgroup of the most abundant mammalian phospholipid, 1,2-diacetyl-3-sn-phosphatidyl choline (DAcPC), has several important applications in research. For instance, it can be dissolved in the same amount of water as in the fluid PC bilayer, to create a surrogate of a PC headgroup stratum, for studying solvation of small molecules and the influence of their structure on the process. In contrast to PC derivatives with longer acyl chains, DAcPC does not self-aggregate, rendering the aqueous solution homogeneous and suitable for simplified analyses of interactions of molecules with the headgroups. Several studies have been published where DAcPC was used in a crudely purified form. Here we describe a one-step preparation of DAcPC from commercially available bulk chemicals and purification of the product by crystallization and washing. The process gives a good yield and is easily scalable. The availability of enantiopure, crystalline DAcPC could open the door to more extensive biochemical, pharmacological, and nutritional studies of this interesting chemical.

Nonclassical Size Dependence of Permeation Defines Bounds for Passive Adsorption of Large Drug Molecules

Macrocyclic peptides are considered large enough to inhibit "undruggable" targets, but the design of passively cell-permeable molecules in this space remains a challenge due to the poorly understood role of molecular size on passive membrane permeability. Using split-pool combinatorial synthesis, we constructed a library of cyclic, per-N-methlyated peptides spanning a wide range of calculated lipohilicities (0 < AlogP < 8) and molecular weights (∼800 Da < MW < ∼1200 Da). Analysis by the parallel artificial membrane permeability assay revealed a steep drop-off in apparent passive permeability with increasing size in stark disagreement with current permeation models. This observation, corroborated by a set of natural products, helps define criteria for achieving permeability in larger molecular size regimes and suggests an operational cutoff, beyond which passive permeability is constrained by a sharply increasing penalty on membrane permeation.

Passive Membrane Permeability in Cyclic Peptomer Scaffolds Is Robust to Extensive Variation in Side Chain Functionality and Backbone Geometry

Synthetic and natural cyclic peptides provide a testing ground for studying membrane permeability in nontraditional drug scaffolds. Cyclic peptomers, which incorporate peptide and N-alkylglycine (peptoid) residues, combine the stereochemical and geometric complexity of peptides with the functional group diversity accessible to peptoids. We synthesized cyclic peptomer libraries by split-pool techniques, separately permuting side chain and backbone geometry, and analyzed their membrane permeabilities using the parallel artificial membrane permeability assay. Nearly half of the side chain permutations had permeability coefficients (P_app) > 1 × 10^-6 cm/s. Some backbone geometries enhanced permeability due to their ability to form more stable intramolecular hydrogen bond networks compared with other scaffolds. These observations suggest that hexameric cyclic peptomers can have good passive permeability even in the context of extensive side chain and backbone variation, and that high permeability can generally be achieved within a relatively wide lipophilicity range.

pH determines the energetic efficiency of the cyanobacterial CO2 concentrating mechanism

Many carbon-fixing bacteria rely on a CO2 concentrating mechanism (CCM) to elevate the CO2 concentration around the carboxylating enzyme ribulose bisphosphate carboxylase/oxygenase (RuBisCO). The CCM is postulated to simultaneously enhance the rate of carboxylation and minimize oxygenation, a competitive reaction with O2 also catalyzed by RuBisCO. To achieve this effect, the CCM combines two features: active transport of inorganic carbon into the cell and colocalization of carbonic anhydrase and RuBisCO inside proteinaceous microcompartments called carboxysomes. Understanding the significance of the various CCM components requires reconciling biochemical intuition with a quantitative description of the system. To this end, we have developed a mathematical model of the CCM to analyze its energetic costs and the inherent intertwining of physiology and pH. We find that intracellular pH greatly affects the cost of inorganic carbon accumulation. At low pH the inorganic carbon pool contains more of the highly cell-permeable H2CO3, necessitating a substantial expenditure of energy on transport to maintain internal inorganic carbon levels. An intracellular pH ≈8 reduces leakage, making the CCM significantly more energetically efficient. This pH prediction coincides well with our measurement of intracellular pH in a model cyanobacterium. We also demonstrate that CO2 retention in the carboxysome is necessary, whereas selective uptake of HCO3 (-) into the carboxysome would not appreciably enhance energetic efficiency. Altogether, integration of pH produces a model that is quantitatively consistent with cyanobacterial physiology, emphasizing that pH cannot be neglected when describing biological systems interacting with inorganic carbon pools.

The cytochrome bd oxidase of Escherichia coli prevents respiratory inhibition by endogenous and exogenous hydrogen sulfide

When sulfur compounds are scarce or difficult to process, Escherichia coli adapts by inducing the high-level expression of sulfur-compound importers. If cystine then becomes available, the cystine is rapidly overimported and reduced, leading to a burgeoning pool of intracellular cysteine. Most of the excess cysteine is exported, but some is adventitiously degraded, with the consequent release of sulfide. Sulfide is a potent ligand of copper and heme moieties, raising the prospect that it interferes with enzymes. We observed that when cystine was provided and sulfide levels rose, E. coli became strictly dependent upon cytochrome bd oxidase for continued respiration. Inspection revealed that low-micromolar levels of sulfide inhibited the proton-pumping cytochrome bo oxidase that is regarded as the primary respiratory oxidase. In the absence of the back-up cytochrome bd oxidase, growth failed. Exogenous sulfide elicited the same effect. The potency of sulfide was enhanced when oxygen concentrations were low. Natural oxic-anoxic interfaces are often sulfidic, including the intestinal environment where E. coli dwells. We propose that the sulfide resistance of the cytochrome bd oxidase is a key trait that permits respiration in such habitats.

Simple Predictive Models of Passive Membrane Permeability Incorporating Size-Dependent Membrane-Water Partition

We investigate the relationship between passive permeability and molecular size, in the context of solubility-diffusion theory, using a diverse compound set with molecular weights ranging from 151 to 828, which have all been characterized in a consistent manner using the RRCK cell monolayer assay. Computationally, each compound was subjected to extensive conformational search and physics-based permeability prediction, and multiple linear regression analyses were subsequently performed to determine, empirically, the relative contributions of hydrophobicity and molecular size to passive permeation in the RRCK assay. Additional analyses of Log D and PAMPA data suggest that these measurements are not size selective, a possible reason for their sometimes weak correlation with cell-based permeability.

Solution equilibria and the X-ray structure of Cu(ii) complexation with 3-amino-N-(pyridin-2-ylmethyl)propanamide, a pseudo-mimic of human serum albumin

Copper complexes have anti-inflammatory activity in the treatment of inflammation associated with rheumatoid arthritis (RA).

From dioxin to dioxin congeners: understanding the differences in hydrophobic aggregation in water and absorption into lipid membranes by means of atomistic simulations

Molecular dynamics simulations indicate that dioxin likely accumulates in cell membranes more than its congeners (anthracene, tetrahydrodioxin, 3,3′,5,5′-tetrachlorobiphenyl, and 1,2-dihydroxytetrahydrodibenzo-p-dioxin).

A Permeability Study of O2 and the Trace Amine p-Tyramine through Model Phosphatidylcholine Bilayers

We study here the permeability of the hydrophobic O2 molecule through a model DPPC bilayer at 323K and 350K, and of the trace amine p-tyramine through PC bilayers at 310K. The tyramine results are compared to previous experimental work at 298K. Nonequilibrium work methods were used in conjunction to simultaneously obtain both the potential of mean force (PMF) and the position dependent transmembrane diffusion coefficient, D(z), from the simulations. These in turn were used to calculate the permeability coefficient, P, through the inhomogeneous solubility-diffusion model. The results for O2 are consistent with previous simulations, and agree with experimentally measured P values for PC bilayers. A temperature dependence in the permeability of O2 through DPPC was obtained, with P decreasing at higher temperatures. Two relevant species of p-tyramine were simulated, from which the PMF and D(z) were calculated. The charged species had a large energetic barrier to crossing the bilayer of ~ 21 kcal/mol, while the uncharged, deprotonated species had a much lower barrier of ~ 7 kcal/mol. The effective in silico permeability for p-tyramine was calculated by applying three approximations, all of which gave nearly identical results (presented here as a function of the pKa). As the permeability value calculated from simulation was highly dependent on the pKa of the amine group, a further pKa study was performed that also varied the fraction of the uncharged and zwitterionic p-tyramine species. Using the experimental P value together with the simulated results, we were able to label the phenolic group as responsible for the pKa1 and the amine for the pKa2, that together represent all of the experimentally measured pKa values for p-tyramine. This agrees with older experimental results, in contrast to more recent work that has suggested there is a strong ambiguity in the pKa values.

A semi-empirical model for transport of inorganic nanoparticles across a lipid bilayer: implications for uptake by living cells

Due to increasing application, release of nanoparticles (NPs) and nanomaterials into the environment becomes likely. Knowledge about NP uptake in organisms is crucial for risk assessment including estimations on the behavior of NPs based on their physicochemical properties. In the present study, the authors have applied current scientific knowledge to construct a mathematical model, which estimates the transport of NPs through a model biological membrane. The semi-empirical model developed showed all parameters studied to substantially affect the agglomeration of the NPs in suspension, thereby also affecting passive transport. The authors quantified the effects of pH, ionic strength, organic matter concentration of medium, and NP size of several inorganic NPs on the permeation through the lipid membrane. Model outcomes and experimental results described in literature were strongly correlated for several metal oxide NPs. With caution, the model may be used to explain some of the existing variance in nano-uptake and toxicity experiments.

Structure-based prediction of drug distribution across the headgroup and core strata of a phospholipid bilayer using surrogate phases

Solvation of drugs in the core (C) and headgroup (H) strata of phospholipid bilayers affects their physiological transport rates and accumulation. These characteristics, especially a complete drug distribution profile across the bilayer strata, are tedious to obtain experimentally, to the point that even simplified preferred locations are only available for a few dozen compounds. Recently, we showed that the partition coefficient (P) values in the system of hydrated diacetyl phosphatidylcholine (DAcPC) and n-hexadecane (C16), as surrogates of the H- and C-strata of the bilayer composed of the most abundant mammalian phospholipid, PC, agree well with the preferred bilayer location of compounds. High P values are typical for lipophiles accumulating in the core, and low P values are characteristic of cephalophiles preferring the headgroups. This simple pattern does not hold for most compounds, which usually have more even distribution and may also accumulate at the H/C interface. To model complete distribution, the correlates of solvation energies are needed for each drug state in the bilayer: (1) for the H-stratum it is the DAcPC/W P value, calculated as the ratio of the C16/W and C16/DAcPC (W for water) P values; (2) for the C-stratum, the C16/W P value; (3) for the H/C interface, the P values for all plausible molecular poses are characterized using the fragment DAcPC/W and C16/W solvation parameters for the parts of the molecule embedded in the H- and C-strata, respectively. The correlates, each scaled by two Collander coefficients, were used in a nonlinear, mass-balance based model of intrabilayer distribution, which was applied to the easily measurable overall P values of compounds in the DMPC (M = myristoyl) bilayers and monolayers as the dependent variables. The calibrated model for 107 neutral compounds explains 94% of experimental variance, achieves similar cross-validation levels, and agrees well with the nontrivial, experimentally determined bilayer locations for 27 compounds. The resulting structure-based prediction system for intrabilayer distribution will facilitate more realistic modeling of passive transport and drug interactions with those integral membrane proteins, which have the binding sites located in the bilayer, such as some enzymes, influx and efflux transporters, and receptors. If only overall bilayer accumulation is of interest, the 1-octanol/W P values suffice to model the studied set.

Local partition coefficients govern solute permeability of cholesterol-containing membranes

The permeability of lipid membranes for metabolic molecules or drugs is routinely estimated from the solute's oil/water partition coefficient. However, the molecular determinants that modulate the permeability in different lipid compositions have remained unclear. Here, we combine scanning electrochemical microscopy and molecular-dynamics simulations to study the effect of cholesterol on membrane permeability, because cholesterol is abundant in all animal membranes. The permeability of membranes from natural lipid mixtures to both hydrophilic and hydrophobic solutes monotonously decreases with cholesterol concentration [Chol]. The same is true for hydrophilic solutes and planar bilayers composed of dioleoyl-phosphatidylcholine or dioleoyl-phosphatidyl-ethanolamine. However, these synthetic lipids give rise to a bell-shaped dependence of membrane permeability on [Chol] for very hydrophobic solutes. The simulations indicate that cholesterol does not affect the diffusion constant inside the membrane. Instead, local partition coefficients at the lipid headgroups and at the lipid tails are modulated oppositely by cholesterol, explaining the experimental findings. Structurally, these modulations are induced by looser packing at the lipid headgroups and tighter packing at the tails upon the addition of cholesterol.

Pyruvate protects pathogenic spirochetes from H2O2 killing

Pathogenic spirochetes cause clinically relevant diseases in humans and animals, such as Lyme disease and leptospirosis. The causative agent of Lyme disease, Borrelia burgdorferi, and the causative agent of leptospirosis, Leptospria interrogans, encounter reactive oxygen species (ROS) during their enzootic cycles. This report demonstrated that physiologically relevant concentrations of pyruvate, a potent H2O2 scavenger, and provided passive protection to B. burgdorferi and L. interrogans against H2O2. When extracellular pyruvate was absent, both spirochetes were sensitive to a low dose of H2O2 (≈0.6 µM per h) generated by glucose oxidase (GOX). Despite encoding a functional catalase, L. interrogans was more sensitive than B. burgdorferi to H2O2 generated by GOX, which may be due to the inherent resistance of B. burgdorferi because of the virtual absence of intracellular iron. In B. burgdorferi, the nucleotide excision repair (NER) and the DNA mismatch repair (MMR) pathways were important for survival during H2O2 challenge since deletion of the uvrB or the mutS genes enhanced its sensitivity to H2O2 killing; however, the presence of pyruvate fully protected ΔuvrB and ΔmutS from H2O2 killing further demonstrating the importance of pyruvate in protection. These findings demonstrated that pyruvate, in addition to its classical role in central carbon metabolism, serves as an important H2O2 scavenger for pathogenic spirochetes. Furthermore, pyruvate reduced ROS generated by human neutrophils in response to the Toll-like receptor 2 (TLR2) agonist zymosan. In addition, pyruvate reduced neutrophil-derived ROS in response to B. burgdorferi, which also activates host expression through TLR2 signaling. Thus, pathogenic spirochetes may exploit the metabolite pyruvate, present in blood and tissues, to survive H2O2 generated by the host antibacterial response generated during infection.