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

Towards development of new antimalarial compounds through in silico and in vitro assays

Malaria is one of most widespread infectious disease in world. The antimalarial therapy presents a series of limitations, such as toxicity and the emergence of resistance, which makes the search for new drugs urgent. Thus, it becomes necessary to explore essential and exclusive therapeutic targets of the parasite to achieve selective inhibition. Enoyl-ACP reductase is an enzyme of the type II fatty acid biosynthetic pathway and is responsible for the rate-limiting step in the fatty acid elongation cycle. In this work, we use hierarchical virtual screening and drug repositioning strategies to prioritize compounds for phenotypic assays and molecular dynamics studies. The molecules were tested against chloroquine-resistant W2 strain of Plasmodium falciparum (EC50 between 330.05 and 13.92 µM). Nitrofurantoin was the best antimalarial activity at low micromolar range (EC50 = 13.92 µM). However, a hit compound against malaria must have a biological activity value below 1 µM. A large number of molecules present problems with permeability in biological membranes and reaching an effective concentration in their target's microenvironment. Nitrofurantoin derivatives with inclusions of groups which confer increased lipid solubility (methyl groups, halogens and substituted and unsubstituted aromatic rings) have been proposed. These derivatives were pulled through the lipid bilayer in molecular dynamics simulations. Molecules 14, 18 and 21 presented lower free energy values than nitrofurantoin when crossing the lipid bilayer.

Liposomal Copermeation Assay Reveals Unexpected Membrane Interactions of Commonly Prescribed Drugs

The permeation of small molecules across biological membranes is a crucial process that lies at the heart of life. Permeation is involved not only in the maintenance of homeostasis at the cell level but also in the absorption and biodistribution of pharmacologically active substances throughout the human body. Membranes are formed by phospholipid bilayers that represent an energy barrier for permeating molecules. Crossing this energy barrier is assumed to be a singular event, and permeation has traditionally been described as a first-order kinetic process, proportional only to the concentration gradient of the permeating substance. For a given membrane composition, permeability was believed to be a unique property dependent only on the permeating molecule itself. We provide experimental evidence that this long-held view might not be entirely correct. Liposomes were used in copermeation experiments with a fluorescent probe, where simultaneous permeation of two substances occurred over a single phospholipid bilayer. Using an assay of six commonly prescribed drugs, we have found that the presence of a copermeant can either enhance or suppress the permeation rate of the probe molecule, often more than 2-fold in each direction. This can have significant consequences for the pharmacokinetics and bioavailability of commonly prescribed drugs when used in combination and provide new insight into so-far unexplained drug-drug interactions as well as changing the perspective on how new drug candidates are evaluated and tested.

Targeting ATP-binding site of WRN Helicase: Identification of novel inhibitors through pocket analysis and Molecular Dynamics-Enhanced virtual screening

WRN helicase is a critical protein involved in maintaining genomic stability, utilizing ATP hydrolysis to dissolve DNA secondary structures. It has been identified as a promising synthetic lethal target for microsatellite instable (MSI) cancers. However, few WRN helicase inhibitors have been discovered, and their potential binding sites remain unexplored. In this study, we analyzed potential binding sites for WRN inhibitors and focused on the ATP-binding site for screening new inhibitors. Through molecular dynamics-enhanced virtual screening, we identified two compounds, h6 and h15, which effectively inhibited WRN's helicase and ATPase activity in vitro. Importantly, these compounds selectively targeted WRN's ATPase activity, setting them apart from other non-homologous proteins with ATPase activity. In comparison to the homologous protein BLM, h6 exhibits some degree of selectivity towards WRN. We also investigated the binding mode of these compounds to WRN's ATP-binding sites. These findings offer a promising strategy for discovering new WRN inhibitors and present two novel scaffolds, which might be potential for the development of MSI cancer treatment.

Fluorogenic Chemical Probes for Wash-free Imaging of Cell Membrane Damage in Ferroptosis, Necrosis, and Axon Injury

Selectively labeling cells with damaged membranes is needed not only for identifying dead cells in culture, but also for imaging membrane barrier dysfunction in pathologies in vivo. Most membrane permeability stains are permanently colored or fluorescent dyes that need washing to remove their non-uptaken extracellular background and reach good image contrast. Others are DNA-binding environment-dependent fluorophores, which lack design modularity, have potential toxicity, and can only detect permeabilization of cell volumes containing a nucleus (i.e., cannot delineate damaged volumes in vivo nor image non-nucleated cell types or compartments). Here, we develop modular fluorogenic probes that reveal the whole cytosolic volume of damaged cells, with near-zero background fluorescence so that no washing is needed. We identify a specific disulfonated fluorogenic probe type that only enters cells with damaged membranes, then is enzymatically activated and marks them. The esterase probe MDG1 is a reliable tool to reveal live cells that have been permeabilized by biological, biochemical, or physical membrane damage, and it can be used in multicolor microscopy. We confirm the modularity of this approach by also adapting it for improved hydrolytic stability, as the redox probe MDG2. We conclude by showing the unique performance of MDG probes in revealing axonal membrane damage (which DNA fluorogens cannot achieve) and in discriminating damage on a cell-by-cell basis in embryos in vivo. The MDG design thus provides powerful modular tools for wash-free in vivo imaging of membrane damage, and indicates how designs may be adapted for selective delivery of drug cargoes to these damaged cells: offering an outlook from selective diagnosis toward therapy of membrane-compromised cells in disease.

Predicting the intrinsic membrane permeability of Caco-2/MDCK cells by the solubility-diffusion model

Membrane permeability is one of the main determinants for the absorption, distribution, metabolism and excretion of compounds and is therefore of crucial importance for successful drug development. Experiments with artificial phospholipid membranes have shown that the intrinsic membrane permeability (P0) of compounds is well-predicted by the solubility-diffusion model (SDM). However, using the solubility-diffusion model to predict the P0 of biological Caco-2 and MDCK cell membranes has proven unreliable so far. Recent publications revealed that many published P0 extracted from Caco-2 and MDCK experiments are incorrect. In this work, we therefore used a small self-generated set as well as a large revised set of experimental Caco-2 and MDCK data from literature to compare experimental and predicted P0. The P0 extracted from Caco-2 and MDCK experiments were systematically lower than the P0 predicted by the solubility-diffusion model. However, using the following correlation: log P0,Caco-2/MDCK = 0.84 log P0,SDM - 1.85, P0 of biological Caco-2 and MDCK cell membranes was well-predicted by the solubility-diffusion model.

Methoxychalcones as potential anticancer agents for colon cancer: Is membrane perturbing potency relevant?

Chalcones are naturally produced by many plants, and constitute precursors for the synthesis of flavons and flavanons. They were shown to possess antibacterial, antifungal, anti-cancer, and anti- inflammatory properties. The goal of the study was to assess the suitability of three synthetic methoxychalcones as potential anticancer agents. In a panel of colon cancer cell lines they were demonstrated to be cytotoxic, proapoptotic, causing cell cycle arrest, and increasing intracellular level of reactive oxygen species. Anticancer activity of the compounds was not diminished in the presence of stool extract containing microbial enzymes that could change the structure of chalcones. Moreover, methoxychalcones interacted strongly with model phosphatidylcholine membranes as detected by differential scanning calorimetry. Metohoxychalcones particularly affected the properties of lipid domains in giant unilamellar liposomes formed from raft-mimicking lipid composition. This may be of importance since many molecular targets for therapy of metastatic colon cancer are raft-associated receptors (e.g., receptor tyrosine kinases). The importance of membrane perturbing potency of methoxychalcones for their biological activity was additionally corroborated by the results obtained by molecular modelling.

[Development of Membrane Permeability Coefficient by Means of Novel Molecular Dynamics Methods]

The membrane permeability, and its evaluation, is crucial factor in the process of uptake of compounds from outside to inside the cell and in the inhibition of the activity of disease-causing target proteins. Although molecular dynamics (MD) simulations have been shown to be able to reproduce the conformational changes of compounds occurring during membrane permeation, it is still challenging to extract the membrane permeability at an affordable computational workload solely by conventional MD. Indeed, the time scale accessible by MD is far below the one characterizing the actual permeation process. Phenomena occurring in living organisms escaping the reach of standard MD are generally referred to as biological rare events, and the membrane permeation process is one of them. To overcome this time-scale problem, several enhanced sampling methods have been proposed over the years to improve conformational sampling. In this review, a hybrid sampling method that combines the parallel cascade selection MD (PaCS-MD) and the outlier flooding method (OFLOOD), introduced and developed by our group, is proposed as a tool to study the membrane permeation from structural sampling (rare-event sampling). The obtained trajectories are used to estimate the free energy profiles for the membrane permeation and to compute the membrane permeation coefficients. Moreover, we present an example of application of the free energy reaction network method as a versatile way for incorporating explicitly into reaction coordinates the degrees of freedom related to internal motion.

Recent Studies of Artificial Intelligence on In Silico Drug Absorption

Absorption is an important area of research in pharmacochemistry and drug development, because the drug has to be absorbed before any drug effects can occur. Furthermore, the ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profile of drugs can be directly and considerably altered by modulating factors affecting absorption. Many drugs in development fail because of poor absorption. The research and continuous efforts of researchers in recent years have brought many successes and promises in drug absorption property prediction, especially in silico, which helps to reduce the time and cost significantly for screening undesirable drug candidates. In this report, we explicitly provide an overview of recent in silico studies on predicting absorption properties, especially from 2019 to the present, using artificial intelligence. Additionally, we have collected and investigated public databases that support absorption prediction research. On those grounds, we also proposed the challenges and development directions of absorption prediction in the future. We hope this review can provide researchers with valuable guidelines on absorption prediction to facilitate the development of newer approaches in drug discovery.

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.

Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods

The therapeutic approach of targeted protein degradation (TPD) is gaining momentum due to its potentially superior effects compared with protein inhibition. Recent advancements in the biotech and pharmaceutical sectors have led to the development of compounds that are currently in human trials, with some showing promising clinical results. However, the use of computational tools in TPD is still limited, as it has distinct characteristics compared with traditional computational drug design methods. TPD involves creating a ternary structure (protein-degrader-ligase) responsible for the biological function, such as ubiquitination and subsequent proteasomal degradation, which depends on the spatial orientation of the protein of interest (POI) relative to E2-loaded ubiquitin. Modeling this structure necessitates a unique blend of tools initially developed for small molecules (e.g., docking) and biologics (e.g., protein-protein interaction modeling). Additionally, degrader molecules, particularly heterobifunctional degraders, are generally larger than conventional small molecule drugs, leading to challenges in determining drug-like properties like solubility and permeability. Furthermore, the catalytic nature of TPD makes occupancy-based modeling insufficient. TPD consists of multiple interconnected yet distinct steps, such as POI binding, E3 ligase binding, ternary structure interactions, ubiquitination, and degradation, along with traditional small molecule properties. A comprehensive set of tools is needed to address the dynamic nature of the induced proximity ternary complex and its implications for ubiquitination. In this Perspective, we discuss the current state of computational tools for TPD. We start by describing the series of steps involved in the degradation process and the experimental methods used to characterize them. Then, we delve into a detailed analysis of the computational tools employed in TPD. We also present an integrative approach that has proven successful for degrader design and its impact on project decisions. Finally, we examine the future prospects of computational methods in TPD and the areas with the greatest potential for impact.

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.

How Azide Ion/Hydrazoic Acid Passes Through Biological Membranes: An Experimental and Computational Study

Hydrazoic acid (HN₃) and its deprotonated form azide ion (N₃^-) (AHA) are toxic because they inhibit the cytochrome c oxidase complex IV (CoX IV) embedded in the inner mitochondrial membrane that forms part of the enzyme complexes involved in cellular respiration. Critical to its toxicity is the inhibition of CoX IV in the central nervous system and cardiovascular system. Hydrazoic acid is an ionizable species and its affinity for membranes, and the associated permeabilities, depend on the pH values of aqueous media on both sides of the membranes. In this article, we address the permeability of AHA through the biological membrane. In order to understand the affinity of the membrane for the neutral and ionized form of azide, we measured the octanol/water partition coefficients at pH values of 2.0 and 8.0, which are 2.01 and 0.00034, respectively. Using a Parallel Artificial Membrane Permeability Assay (PAMPA) experiment, we measured the effective permeability through the membrane, which is logP_e - 4.97 and - 5.26 for pH values of 7.4 and pH 8.0, respectively. Experimental permeability was used to validate theoretical permeability, which was estimated by numerically solving a Smoluchowski equation for AHA diffusion through the membrane. We demonstrated that the rate of permeation through the cell membrane of 8.46·10⁴ s^-1 is much higher than the rate of the chemical step of CoX IV inhibition by azide of 200 s^-1. The results of this study show that transport through the membrane does not represent the rate-limiting step and therefore does not control the rate of CoX IV inhibition in the mitochondria. However, the observed dynamics of azide poisoning is controlled by circulatory transport that takes place on a time scale of minutes.

Preparation and Surface Characterization of Chitosan-Based Coatings for PET Materials

Poly(ethylene terephthalate)-PET-is one of the most frequently used polymers in biomedical applications. Due to chemical inertness, PET surface modification is necessary to gain specific properties, making the polymer biocompatible. The aim of this paper is to characterize the multi-component films containing chitosan (Ch), phospholipid 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), immunosuppressant cyclosporine A (CsA) and/or antioxidant lauryl gallate (LG) which can be utilized as a very attractive material for developing the PET coatings. Chitosan was employed owing to its antibacterial activity and also its ability to promote cell adhesion and proliferation favorable for tissue engineering and regeneration purposes. Moreover, the Ch film can be additionally modified with other substances of biological importance (DOPC, CsA and LG). The layers of varying compositions were prepared using the Langmuir-Blodgett (LB) technique on the air plasma-activated PET support. Then their nanostructure, molecular distribution, surface chemistry and wettability were determined by atomic force microscopy (AFM), time-of-flight secondary ion mass spectrometry (TOF-SIMS), X-ray photoelectron spectroscopy (XPS), contact angle (CA) measurements and the surface free energy and its components' determination, respectively. The obtained results show clearly the dependence of the surface properties of the films on the molar ratio of components and allow for a better understanding of the coating organization and mechanisms of interactions at the molecular level both inside the films and between the films and the polar/apolar liquids imitating the environment of different properties. The organized layers of this type can be helpful in gaining control over the surface properties of the biomaterial, thus getting rid of the limitations in favor of increased biocompatibility. This is a good basis for further investigations on the correlation of the immune system response to the presence of biomaterial and its physicochemical properties.

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.

Antioxidant and Anti-inflammatory Activity of Sea Cucumber (Holothuria scabra) Active Compounds against KEAP1 and iNOS Protein

Oxidative stress and inflammation have a role in the development of various diseases. Oxidative stress and inflammation are associated with many proteins, including Kelch ECH associating protein 1 (KEAP1) and inducible nitric oxide synthase (iNOS) proteins. The active compounds contained in Holothuria scabra have antioxidant and anti-inflammatory properties. This study aimed to evaluate the antioxidant and anti-inflammatory activity of sea cucumber's active compounds by targeting KEAP1 and iNOS proteins. 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and nitric oxide (NO) scavenging activity of H. scabra extract were measured spectrophotometrically. The 3-dimensional (3D) structures of sea cucumber's active compounds and proteins were obtained from the PubChem and Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) databases. Molecular docking was performed using AutoDock Vina software. Molecular dynamics simulations were carried out using Yet Another Scientific Artificial Reality Application (YASARA) software with environmental parameters according to the cell's physiological conditions. The membrane permeability test was performed using the PerMM web server. The methanol extract of H. scabra had a weak antioxidant activity against DPPH and strong activity against NO radical. Scabraside and holothurinoside G had the most negative binding affinity values when interacting with the active site of KEAP1 and iNOS proteins. Molecular dynamics simulations also showed that both compounds were stable when interacting with KEAP1 and iNOS. However, scabraside and holothurinoside G were difficult to penetrate the cell plasma membrane, which is seen from the high energy transfer value in the lipid acyl chain region of phospholipids. Scabraside and holothurinoside G are predicted to act as antioxidants and anti-inflammations, but in their implementation to in vitro and in vivo study, it is necessary to have liposomes or nanoparticles, or other delivery methods to help these 2 compounds enter the cell.

Free-Energy Profiles for Membrane Permeation of Compounds Calculated Using Rare-Event Sampling Methods

The free-energy profile of a compound is an essential measurement in evaluating the membrane permeation process by means of theoretical methods. Computationally, molecular dynamics (MD) simulation allows the free-energy profile calculation. However, MD simulations frequently fail to sample membrane permeation because they are rare events induced in longer timescales than the accessible timescale of MD, leading to an insufficient conformational search to calculate an incorrect free-energy profile. To achieve a sufficient conformational search, several enhanced sampling methods have been developed and elucidated the membrane permeation process. In addition to these enhanced sampling methods, we proposed a simple yet powerful free-energy calculation of a compound for the membrane permeation process based on originally rare-event sampling methods developed by us. Our methods have a weak dependency on external biases and their optimizations to promote the membrane permeation process. Based on distributed computing, our methods only require the selection of initial structures and their conformational resampling, whereas the enhanced sampling methods may be required to adjust external biases. Furthermore, our methods efficiently search membrane permeation processes with simple scripts without modifying any MD program. As demonstrations, we calculated the free-energy profiles of seven linear compounds for their membrane permeation based on a hybrid conformational search using two rare-event sampling methods, that is, (1) parallel cascade selection MD (PaCS-MD) and (2) outlier flooding method (OFLOOD), combined with a Markov state model (MSM) construction. In the first step, PaCS-MD generated initial membrane permeation paths of a compound. In the second step, OFLOOD expanded the unsearched conformational area around the initial paths, allowing for a broad conformational search. Finally, the trajectories were employed to construct reliable MSMs, enabling correct free-energy profile calculations. Furthermore, we estimated the membrane permeability coefficients of all compounds by constructing the reliable MSMs for their membrane permeation. In conclusion, the calculated coefficients were qualitatively correlated with the experimental measurements (correlation coefficient (R²) = 0.8689), indicating that the hybrid conformational search successfully calculated the free-energy profiles and membrane permeability coefficients of the seven compounds.

Surface Properties of the Polyethylene Terephthalate (PET) Substrate Modified with the Phospholipid-Polypeptide-Antioxidant Films: Design of Functional Biocoatings

Surface properties of polyethylene terephthalate (PET) coated with the ternary monolayers of the phospholipid 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), the immunosuppressant cyclosporine A (CsA), and the antioxidant lauryl gallate (LG) were examined. The films were deposited, by means of the Langmuir-Blodgett (LB) technique, on activated by air low temperature plasma PET plates (PET_air). Their topography and surface chemistry were determined with the help of atomic force microscopy (AFM) and time-of-flight secondary ion mass spectrometry (TOF-SIMS), respectively, while wettability was evaluated by the contact angle measurements. Then, the surface free energy and its components were calculated from the Lifshitz-van der Waals/Acid-Base (LWAB) approach. The AFM imaging showed that the Langmuir monolayers were transferred effectively and yielded smoothing of the PET_air surface. Mass spectrometry confirmed compatibility of the quantitative and qualitative compositions of the monolayers before and after the transfer onto the substrate. Moreover, the molecular arrangement in the LB films and possible mechanisms of DOPC-CsA-LG interactions were determined. The wettability studies provided information on the type and magnitude of the interactions that can occur between the biocoatings and the liquids imitating different environments. It was found that the changes from open to closed conformation of CsA molecules are driven by the hydrophobic environment ensured by the surrounding DOPC and LG molecules. This process is of significance to drug delivery where the CsA molecules can be released directly from the biomaterial surface by passive diffusion. The obtained results showed that the chosen techniques are complementary for the characterization of the molecular organization of multicomponent LB films at the polymer substrate as well as for designing biocompatible coatings with precisely defined wettability.

In Vitro Characterization of Inhibitors for Lung A549 and Leukemia K562 Cell Lines from Fungal Transformation of Arecoline Supported by In Silico Docking to M3-mAChR and ADME Prediction

The search for anticancer drugs is of continuous interest. Arecoline is an alkaloid with anticancer activity. Herein, the metabolism of arecoline through fungal transformation was investigated for the discovery of potential anticancer drugs with higher activity and selectivity. Compounds 1–5 were isolated, and their structures were fully elucidated using various spectroscopic analyses, including 1D and 2D NMR, ESIMS, and HRESIMS. This is the first report for the isolation of compounds 1 and 2. An MTT assay was performed to determine the cytotoxic activity of arecoline and its metabolites in vitro using non-small-cell lung cancer A549 and leukemia K562 cell lines compared to staurosporine and doxorubicin as positive controls. For the non-small-cell lung A549 cell line, arecoline hydrobromide, staurosporine, and doxorubicin resulted in IC50 values of 11.73 ± 0.71 µM, 10.47 ± 0.64 µM, and 5.05 ± 0.13 µM, respectively, while compounds 1, 3, and 5 exhibited IC50 values of 3.08 ± 0.19 µM, 7.33 ± 0.45 µM, and 3.29 ± 0.20 µM, respectively. For the leukemia K562 cell line, the IC50 values of arecoline hydrobromide, staurosporine, and doxorubicin were 15.3 ± 1.08 µM, 5.07 ± 0.36 µM, and 6.94 ± 0.21 µM, respectively, while the IC50 values of compounds 1, 3 and 5 were 1.56 ± 0.11 µM, 3.33 ± 0.24 µM, and 2.15 ± 0.15 µM, respectively. The selectivity index value of these compounds was higher than 3. These results indicated that compounds 1, 3, and 5 are very strong cytotoxic agents with higher activity than the positive controls and good selectivity toward the tested cancer cell lines. Cell cycle arrest was then studied by flow cytometry to investigate the apoptotic mechanism. Docking simulation revealed that most compounds possessed good binding poses and favorable protein-ligand interactions with muscarinic acetylcholine receptor M3-mAChR protein. In silico study of pharmacokinetics using SwissADME predicted compounds 1–5 to be drug-like with a high probability of good oral bioavailability.

Impact of cholesterol and sphingomyelin on intrinsic membrane permeability

Transwell experiments with Caco-2 or MDCK cells are the gold standard for determining the intestinal permeability of chemicals. The intrinsic membrane permeability (P₀), that can be extracted from these experiments, might be comparable to P₀ measured in black lipid membrane (BLM) experiments and P₀ predicted by the solubility-diffusion model. Unfortunately, the overlap between experimental P_{0,Caco-2/MDCK} and P_0,BLM data is very small. So far, differences between both approaches have been attributed to the cholesterol and sphingomyelin content of cell membranes, but the database is too sparse to thoroughly test this theory. To create a diverse dataset, we measured P_0,BLM of ten chemicals in BLM experiments using DPhPC and DPhPC/cholesterol/sphingomyelin membranes. The results were compared to predicted BLM data and experimental Caco-2/MDCK data obtained from literature. While P_0,BLM of all chemicals was well predicted by the solubility-diffusion model, P_{0,Caco-2/MDCK} was only predictable for rather hydrophilic compounds with logarithmic hexadecane/water partition coefficients below -0.5. The effect of cholesterol and sphingomyelin on P_0,BLM was negligibly small.

Discovery of potent dual ligands for dopamine D4 and σ1 receptors

During our work on exploration of molecules with some piperidine-triazole scaffolds, we realized that our compounds display chemical similarity with some σ, as well as dopaminergic receptor ligands. Here we show that this series of molecules has indeed strong affinity both for σ1 and dopamine D4 receptors. Moreover, they appear selective towards σ2, dopamine paralogues D1, D2, D3 and D5 receptors and hERG channel. Extensive molecular dynamics with our lead compound AVRM-13 were carried out on σ1, supporting agonist activity of the ligand. Unexpectedly, several observations suggested the existence of a cation binding domain, a probable regulatory site for calcium.

Membrane thickness, lipid phase and sterol type are determining factors in the permeability of membranes to small solutes

Cell membranes provide a selective semi-permeable barrier to the passive transport of molecules. This property differs greatly between organisms. While the cytoplasmic membrane of bacterial cells is highly permeable for weak acids and glycerol, yeasts can maintain large concentration gradients. Here we show that such differences can arise from the physical state of the plasma membrane. By combining stopped-flow kinetic measurements with molecular dynamics simulations, we performed a systematic analysis of the permeability of a variety of small molecules through synthetic membranes of different lipid composition to obtain detailed molecular insight into the permeation mechanisms. While membrane thickness is an important parameter for the permeability through fluid membranes, the largest differences occur when the membranes transit from the liquid-disordered to liquid-ordered and/or to gel state, which is in agreement with previous work on passive diffusion of water. By comparing our results with in vivo measurements from yeast, we conclude that the yeast membrane exists in a highly ordered and rigid state, which is comparable to synthetic saturated DPPC-sterol membranes.

Membrane permeability of small molecules depends on the composition of the lipid bilayer. Here, authors compare permeability measured on membranes in different physical states and conclude that the yeast membrane exists in a highly ordered phase.

A Simulation Model for the Non-Electrogenic Uniport Carrier-Assisted Transport of Ions across Lipid Membranes

Impressive work has been completed in recent decades on the transmembrane anion transport capability of small synthetic transporters from many different structural classes. However, very few predicting models have been proposed for the fast screening of compound libraries before spending time and resources on the laboratory bench for their synthesis. In this work, a new approach is presented which aims at describing the transport process by taking all the steps into explicit consideration, and includes all possible experiment-derived parameters. The algorithm is able to simulate the macroscopic experiments performed with lipid vesicles to assess the ion-transport ability of the synthetic transporters following a non-electrogenic uniport mechanism. While keeping calculation time affordable, the final goal is the curve-fitting of real experimental data—so, to obtain both an analysis and a predictive tool. The role and the relative weight of the different parameters is discussed and the agreement with the literature is shown by using the simulations of a virtual benchmark case. The fitting of real experimental curves is also shown for two transporters of different structural type.

From Fragment to Lead: De Novo Design and Development toward a Selective FGFR2 Inhibitor

Fibroblast growth factor receptors (FGFRs) are implicated in a range of cancers with several pan-kinase and selective-FGFR inhibitors currently being evaluated in clinical trials. Pan-FGFR inhibitors often cause toxic side effects and few examples of subtype-selective inhibitors exist. Herein, we describe a structure-guided approach toward the development of a selective FGFR2 inhibitor. De novo design was carried out on an existing fragment series to yield compounds predicted to improve potency against the FGFRs. Subsequent iterative rounds of synthesis and biological evaluation led to an inhibitor with nanomolar potency that exhibited moderate selectivity for FGFR2 over FGFR1/3. Subtle changes to the lead inhibitor resulted in a complete loss of selectivity for FGFR2. X-ray crystallographic studies revealed inhibitor-specific morphological differences in the P-loop which were posited to be fundamental to the selectivity of these compounds. Additional docking studies have predicted an FGFR2-selective H-bond which could be utilized to design more selective FGFR2 inhibitors.

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.

Isobavachalcone as an Active Membrane Perturbing Agent and Inhibitor of ABCB1 Multidrug Transporter

Isobavachalcone (IBC) is an active substance from the medicinal plant Psoralea corylifolia. This prenylated chalcone was reported to possess antioxidative, anti-inflammatory, antibacterial, and anticancer activities. Multidrug resistance (MDR) associated with the over-expression of the transporters of vast substrate specificity such as ABCB1 (P-glycoprotein) belongs to the main causes of cancer chemotherapy failure. The cytotoxic, MDR reversing, and ABCB1-inhibiting potency of isobavachalcone was studied in two cellular models: human colorectal adenocarcinoma HT29 cell line and its resistant counterpart HT29/Dx in which doxorubicin resistance was induced by prolonged drug treatment, and the variant of MDCK cells transfected with the human gene encoding ABCB1. Because MDR modulators are frequently membrane-active substances, the interaction of isobavachalcone with model phosphatidylcholine bilayers was studied by means of differential scanning calorimetry. Molecular modeling was employed to characterize the process of membrane permeation by isobavachalcone. IBC interacted with ABCB1 transporter, being a substrate and/or competitive inhibitor of ABCB1. Moreover, IBC intercalated into model membranes, significantly affecting the parameters of their main phospholipid phase transition. It was concluded that isobavachalcone interfered both with the lipid phase of cellular membrane and with ABCB1 transporter, and for this reason, its activity in MDR cancer cells was presumptively beneficial.

16-Picolyl-androsterone derivative exhibits potent 17β-HSD3 inhibitory activity, improved metabolic stability and cytotoxic effect on various cancer cells: Synthesis, homology modeling and docking studies

A new androsterone derivative bearing a 16β-picolyl group (compound 5; FCO-586-119) was synthetized in four steps from the lead compound 1 (RM-532-105). We measured its inhibitory activity on 17β-HSD3 using microsomal fraction of rat testes as well as transfected LNCaP[17β-HSD3] cells. We then assessed its metabolic stability as well as its cytotoxic effect against a panel of cancer cell lines. The addition of a picolyl moiety at C-16 of RM-532-105 steroid core improves the 17β-HSD3 inhibitory activity in the microsomal fraction of rat testes, but not in whole LNCaP[17β-HSD3] cells. Interestingly, this structural modification enhances 3-fold the metabolic stability in conjunction with a significant cytotoxic effect against pancreatic, ovarian, breast, lung, and prostate cancer cells. Because the inhibitory activity data against 17β-HSD3 suggested that both steroid derivatives are non-competitive inhibitors, we performed docking and molecular dynamics simulations using a homology model of this membrane-associated enzyme. The results of these simulations revealed that both RM-532-105 (1) and FCO-586-119 (5) can compete for the cofactor-binding site displaying better binding energy than NADP+.

Analysis of Molecular Interactions between Components in Phospholipid-Immunosuppressant-Antioxidant Mixed Langmuir Films

The study of Langmuir monolayers incorporating biomimetic and bioactive substances plays an important role today in assessing the properties and quality of the molecular films for potential biomedical applications. Here, miscibility of binary and ternary monolayers of phospholipid (dioleoyl phosphatidylcholine, DOPC), immunosuppressant (cyclosporine A, CsA), and antioxidant (lauryl gallate, LG) of varying molar fractions was analyzed by means of the Langmuir technique coupled with a surface potential (ΔV) module at the air-water interface. The surface pressure-area per molecule (π-A) isotherms provided information on the physical state of the films at a given surface pressure, the monolayer packing and ordering, and the type and strength of intermolecular interactions. Surface potential-area (ΔV-A) isotherms revealed the molecular orientation changes at the interface upon compression. In addition, the apparent dipole moment of the monolayer-forming molecules was determined from the surface potential isotherms. The obtained results indicated that the film compression provoked subsequent changes of CsA conformation and/or orientation, conferring better affinity for the hydrocarbon environment. The mutual interactions between the components were analyzed here in terms of the excess and total Gibbs energy of mixing, whose values depended on the stoichiometry of the mixed films. The strongest attraction, thus the highest thermodynamic stability, was found for a DOPC-CsA-LG mixture with a 1:1:2 molar ratio. Based on these results, a molecular model for the organization of the molecules within the Langmuir film was proposed. Through this model, we elucidated the significant role of LG in improving the miscibility of CsA in the model DOPC membrane and thus in increasing the stability of self-assembled monolayers by noncovalent interactions, such as H-bonds and Lifshitz-van der Waals forces. The above 1:1:2 combination of three components is revealed as the most promising film composition for the modification of implant device surfaces to improve their biocompatibility. Further insight into mechanisms concerning drug-membrane interactions at the molecular level is provided, which results in great importance for biocoating design and development as well as for drug release at target sites.

Cnicin as an Anti-SARS-CoV-2: An Integrated In Silico and In Vitro Approach for the Rapid Identification of Potential COVID-19 Therapeutics

Since the emergence of the SARS-CoV-2 pandemic in 2019, it has remained a significant global threat, especially with the newly evolved variants. Despite the presence of different COVID-19 vaccines, the discovery of proper antiviral therapeutics is an urgent necessity. Nature is considered as a historical trove for drug discovery, especially in global crises. During our efforts to discover potential anti-SARS CoV-2 natural therapeutics, screening our in-house natural products and plant crude extracts library led to the identification of C. benedictus extract as a promising candidate. To find out the main chemical constituents responsible for the extract's antiviral activity, we utilized recently reported SARS CoV-2 structural information in comprehensive in silico investigations (e.g., ensemble docking and physics-based molecular modeling). As a result, we constructed protein-protein and protein-compound interaction networks that suggest cnicin as the most promising anti-SARS CoV-2 hit that might inhibit viral multi-targets. The subsequent in vitro validation confirmed that cnicin could impede the viral replication of SARS CoV-2 in a dose-dependent manner, with an IC50 value of 1.18 µg/mL. Furthermore, drug-like property calculations strongly recommended cnicin for further in vivo and clinical experiments. The present investigation highlighted natural products as crucial and readily available sources for developing antiviral therapeutics. Additionally, it revealed the key contributions of bioinformatics and computer-aided modeling tools in accelerating the discovery rate of potential therapeutics, particularly in emergency times like the current COVID-19 pandemic.

The Dihydroorotate Dehydrogenase Inhibitor Brequinar Is Synergistic with ENT1/2 Inhibitors

The dihydroorotate dehydrogenase (DHODH) inhibitor brequinar failed all clinical trials for solid tumors. To investigate mechanisms to increase brequinar's efficacy, we employed a combination strategy to simultaneously inhibit the nucleotide salvage pathways. Brequinar is synergistic with the equilibrative nucleoside transporter (ENT) inhibitor dipyridamole, but not the concentrative nucleoside transporter inhibitor phlorizin. This synergy carries over to ENT1/2 inhibition, but not ENT4. Our previously described brequinar analogue 41 was also synergistic with dipyridamole as were the FDA-approved DHODH inhibitors leflunomide and teriflunomide but the latter required much higher concentrations than brequinar. Therefore, a combination of brequinar and ENT inhibitors presents a potential anti-cancer strategy in select tumors.

New 3β-hydroxysteroid-indolamine conjugates: Design, synthesis and inhibition of C6 glioma cell proliferation

Four novel indole steroids based on dehydroepiandrosterone (IS-1), estrone (IS-2) and pregnenolone (IS-3) were obtained and studied for their ability to inhibit C6 glioma proliferation. A reduction in cell proliferation by 52 ± 13% was observed for IS-1 at 10 μM, whereas IS-3 and abiraterone acetate at 10 μM caused a 36 ± 8% decrease. Surprisingly, the cellular effects reported for abiraterone, namely, cytochrome P450 CYP17A1 inhibition and endoplasmic reticulum stress were not detected for IS-1. However, both abiraterone and IS-1 significantly increased glutathione levels. Docking studies predicted good affinity of IS-1 to liver X receptors and regulatory protein Keap1, which are proposed to be involved in the compounds' antiproliferative activity.

Effect of drying methods on the gastrointestinal fate and bioactivity of phytochemicals from cocoa pod husk: In vitro and in silico approaches

Cocoa pod husk (CPH) contains many nutraceutical phytochemicals whose gastrointestinal fate and bioactivity can be affected by drying methods. Microwave (MW), forced-air drying (AF), and AF plus extrusion (AF-E) dried CPH samples were chemically characterized, and their phenolic and theobromine (THB) contents were evaluated under oral-gastric-intestinal (in vitro) and colonic fermentation (ex vivo). Absorption, distribution, metabolism, excretion, and toxicity (ADEMT) properties of CPH's small molecules were evaluated in silico. The chemical composition of CPH [mostly carbohydrates/insoluble dietary fiber], polyphenol [total polyphenols > condensed tannin (CT) > monomeric flavonoids] differed minimally among samples, except for THB content (AF/AF-E > MW) and antioxidant capacity (MW > AF/AF-E). Time- trend gastrointestinal (X³ behavior) and colonic bioaccessibility were AF/AF-E > MW, but phenolic acids, procyanidins, and THB fluctuated in a sample-specific fashion. In silico modeling showed that bioactives of CPH easily crossed the intestinal epithelium illustrating their bioaccessibility and, permeability. These bioactives can act as receptor ligands in a structure-dependent manner, suggesting their use as a functional ingredient.

Nitrogen-containing naringenin derivatives for reversing multidrug resistance in cancer

Naringenin (1), isolated from Euphorbia pedroi, was previously derivatized yielding compounds 2-13. In this study, aiming at expanding the pool of analogues of the flavanone core towards better multidrug resistance (MDR) reversal agents, alkylation reactions and chemical modification of the carbonyl moiety was performed (15-39). Compounds structures were assigned mainly by 1D and 2D NMR experiments. Compounds 1-39 were assessed as MDR reversers, in human ABCB1-transfected mouse T-lymphoma cells, overexpressing P-glycoprotein (P-gp). The results revealed that O-methylation at C-7, together with the introduction of nitrogen atoms and aromatic moieties at C-4 or C-4', significantly improved the activity, being compounds 27 and 37 the strongest P-gp modulators and much more active than verapamil. In combination assays, synergistic interactions of selected compounds with doxorubicin substantiated the results. While molecular docking suggested that flavanone derivatives act as competitive modulators, molecular dynamics showed that dimethylation promotes binding to a modulator-binding site. Moreover, flavanones may also interact with a vicinal ATP-binding site in both nucleotide-binding domains, hypothesizing an allosteric mode of action.

Membrane/Water Partitioning and Permeabilities of Perfluoroalkyl Acids and Four of their Alternatives and the Effects on Toxicokinetic Behavior

The search for alternatives to bioaccumulative perfluoroalkyl acids (PFAAs) is ongoing. New, still highly fluorinated alternatives are produced in hopes of reducing bioaccumulation. To better estimate this bioaccumulative behavior, we performed dialysis experiments and determined membrane/water partition coefficients, K_mem/w, of six perfluoroalkyl carboxylic acids (PFCAs), three perfluoroalkanesulfonic acids, and four alternatives. We also investigated how passive permeation might influence the uptake kinetics into cells, measuring the passive anionic membrane permeability P_ion through planar lipid bilayers for six PFAAs and three alternatives. Experimental K_mem/w and P_ion were both predicted well by the COSMO-RS theory (log RMSE 0.61 and 0.46, respectively). K_mem/w values were consistent with the literature data, and alternatives showed similar sorption behavior as PFAAs. Experimental P_ion values were high enough to explain observed cellular uptake by passive diffusion with no need to postulate the existence of active uptake processes. However, predicted pK_a and neutral permeabilities suggest that also the permeation of the neutral species should be significant in case of PFCAs. This can have direct consequences on the steady-state distribution of PFAAs across cell membranes and thus toxicity. Consequently, we propose a model to predict pH-dependent baseline toxicity based on K_mem/w, which considers the permeation of both neutral and anionic species.

QSPR model for Caco-2 cell permeability prediction using a combination of HQPSO and dual-RBF neural network

The aim of this study is to establish a promising QSPR model for the Caco-2 permeability prediction.

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/ .