Entropy and Polarity Control the Partition and Transportation of Drug-like Molecules in Biological Membrane

Revisiting the Application of Machine Learning Approaches in Predicting Aqueous Solubility

The solubility of chemical substances in water is a critical parameter in pharmaceutical development, environmental chemistry, agrochemistry, and other fields; however, accurately predicting it remains a challenge. This study aims to evaluate and compare the effectiveness of some of the most popular machine learning modeling methods and molecular featurization techniques in predicting aqueous solubility. Although these methods were not implemented in a competitive environment, some of their performance surpassed previous benchmarks, offering gradual but significant improvements. Our results show that methods based on graph convolution and graph attention mechanisms demonstrated exceptional predictive abilities with high-quality data sets, albeit with a sensitivity to data noise and errors. In contrast, models leveraging molecular descriptors not only provided better interpretability but also showed more resilience when dealing with inherent noise and errors in data. Our analysis of over 4000 molecular descriptors used in various models identified that approximately 800 of these descriptors make a significant contribution to solubility prediction. These insights offer guidance and direction for future developments in solubility prediction.

Symmetrical Bispyridinium Compounds Act as Open Channel Blockers of Cation-Selective Ion Channels

Current treatments against organophosphate poisoning (OPP) do not directly address effects mediated by the overstimulation of nicotinic acetylcholine receptors (nAChR). Non-oxime bispyridinium compounds (BPC) promote acetylcholine esterase-independent recovery of organophosphate-induced paralysis. Here, we test the hypothesis that they act by positive modulatory action on nAChRs. Using two-electrode voltage clamp analysis in combination with mutagenesis and molecular docking analysis, the potency and molecular mode of action of a series of nine BPCs was investigated on human α7 and muscle-type nAChRs expressed in Xenopus laevis oocytes. The investigated BPCs inhibited α7 and/or muscle-type nAChRs with IC50 values in the high nanomolar to high micromolar range. Further analysis of the most potent analogues revealed a noncompetitive, voltage-dependent inhibition. Co-application with the α7-selective positive allosteric modulator PNU120596 and generation of α7/5HT3 receptor chimeras excluded direct interaction with the PNU120596 binding site and binding to the extracellular domain of the α7 nAChR, suggesting that they act as open channel blockers (OCBs). Molecular docking supported by mutagenesis localized the BPC binding area in the outer channel vestibule between the extracellular and transmembrane domains. Analysis of BPC action on other cation-selective channels suggests a rather nonspecific inhibition of pentameric cation channels. BPCs have been shown to ameliorate organophosphate-induced paralysis in vitro and in vivo. Our data support molecular action as OCBs at α7 and muscle-type nAChRs and suggest that their positive physiological effects are more complex than anticipated and require further investigation.

Biochemical exploration of β-lactamase inhibitors

The alarming rise of microbial resistance to antibiotics has severely limited the efficacy of current treatment options. The prevalence of β-lactamase enzymes is a significant contributor to the emergence of antibiotic resistance. There are four classes of β-lactamases: A, B, C, and D. Class B is the metallo-β-lactamase, while the rest are serine β-lactamases. The clinical use of β-lactamase inhibitors began as an attempt to combat β-lactamase-mediated resistance. Although β-lactamase inhibitors alone are ineffective against bacteria, research has shown that combining inhibitors with antibiotics is a safe and effective treatment that not only prevents β-lactamase formation but also broadens the range of activity. These inhibitors may cause either temporary or permanent inhibition. The development of new β-lactamase inhibitors will be a primary focus of future research. This study discusses recent advances in our knowledge of the biochemistry behind β-lactam breakdown, with special emphasis on the mechanism of inhibitors for β-lactam complexes with β-lactamase. The study also focuses on the pharmacokinetic and pharmacodynamic properties of all inhibitors and then applies them in clinical settings. Our analysis and discussion of the challenges that exist in designing inhibitors might help pharmaceutical researchers address root issues and develop more effective inhibitors.

Treating Polarization Effects in Charged and Polar Bio-Molecules Through Variable Electrostatic Parameters

Polarization plays important roles in charged and hydrogen bonding containing systems. Much effort ranging from the construction of physics-based models to quantum mechanism (QM)-based and machine learning (ML)-assisted models have been devoted to incorporating the polarization effect into the conventional force fields at different levels, such as atomic and coarse grained (CG). The application of polarizable force fields or polarization models was limited by two aspects, namely, computational cost and transferability. Different from physics-based models, no predetermining parameters were required in the QM-based approaches. Taking advantage of both the accuracy of QM calculations and efficiency of molecular mechanism (MM) and ML, polarization effects could be treated more efficiently while maintaining the QM accuracy. The computational cost could be reduced with variable electrostatic parameters, such as the charge, dipole, and electronic dielectric constant with the help of linear scaling fragmentation-based QM calculations and ML models. Polarization and entropy effects on the prediction of partition coefficient of druglike molecules are demonstrated by using both explicit or implicit all-atom molecular dynamics simulations and machine learning-assisted models. Directions and challenges for future development are also envisioned.

Reliable Prediction of Caco-2 Permeability by Supervised Recursive Machine Learning Approaches

The heterogeneity of the Caco-2 cell line and differences in experimental protocols for permeability assessment using this cell-based method have resulted in the high variability of Caco-2 permeability measurements. These problems have limited the generation of large datasets to develop accurate and applicable regression models. This study presents a QSPR approach developed on the KNIME analytical platform and based on a structurally diverse dataset of over 4900 molecules. Interpretable models were obtained using random forest supervised recursive algorithms for data cleaning and feature selection. The development of a conditional consensus model based on regional and global regression random forest produced models with RMSE values between 0.43–0.51 for all validation sets. The potential applicability of the model as a surrogate for the in vitro Caco-2 assay was demonstrated through blind prediction of 32 drugs recommended by the International Council for the Harmonization of Technical Requirements for Pharmaceuticals (ICH) for validation of in vitro permeability methods. The model was validated for the preliminary estimation of the BCS/BDDCS class. The KNIME workflow developed to automate new drug prediction is freely available. The results suggest that this automated prediction platform is a reliable tool for identifying the most promising compounds with high intestinal permeability during the early stages of drug discovery.

The effects of molecular weight and orientation on the membrane permeation and partitioning of polycyclic aromatic hydrocarbons: a computational study

Membrane permeation and the partitioning of polycyclic aromatic hydrocarbons (PAHs) are crucial aspects affecting their carcinogenicity and mutagenicity. However, a clear understanding of these processes is still rare due to the difficulty of determining the details experimentally. Here, the interactions between PAHs and lipid bilayers were studied by molecular simulations, mainly to check the influence of molecular weight and orientation. The liposome-water partition coefficient (K_LW), transmembrane time (τ), and permeability coefficient (P) of the PAHs were calculated by integrating free energy profiles from umbrella sampling. For selected PAHs, the membrane adsorption is a spontaneous process. The preferred location is near the CC bond and the orientation is related to the molecular structure. The P values of all the PAHs are basically the same order of magnitude, which means that the molecular weight contributes little to the process. As for K_LW and τ, they show obvious increases with different molecular weights. Unconstrained simulations showed that a flat orientation on the membrane surface would prevent PAHs from being transported through the membrane. Highly hydrophobic driving forces are not always good for the absorption of PAHs, especially the formation of aggregates. In addition, the orientations and energetic barriers of PAHs near the midplane of the lipid bilayer explain the different transitions of high- and low-weight PAHs. This work provides molecular level details relating to the interactions of PAHs with lipid membranes, with significance for understanding the health effects of PAHs.

Stress impact of liposomes loaded with ciprofloxacin on the expression level of MepA and NorB efflux pumps of methicillin-resistant Staphylococcus aureus

One mechanism of ciprofloxacin resistance is attributed to chromosomal DNA-encoded efflux pumps such as the MepA and NorB proteins. The goal of this research is to find a way to bypass Staphylococcus aureus' efflux pumps. Because of its high membrane permeability and low association with NorB and MepA efflux proteins, a liposome-encapsulating antibiotic is one of the promising, cost-effective drug carriers and coating mechanisms for overcoming active transport of methicillin-resistant S. aureus (MRSA) multidrug-resistant efflux protein . The calculated "Log Perm RRCK" membrane permeability values of 1,2-distearoyl-sn-glycerol-3-phosphocholine (DSPC) ciprofloxacin liposome-encapsulated (CFL) showed a lower negative value of - 4,652 cm/s and greater membrane permeability than ciprofloxacin free (CPF). The results of RT-qPCR showed that cationic liposomes containing ciprofloxacin in liposome-encapsulated form (CFL) improved CPF antibacterial activity and affinity for negatively charged bacterial cell surface membrane in comparison to free drug and liposome, as it overcame several resistance mechanisms and reduced the expression of efflux pumps. Ciprofloxacin liposome-encapsulated (CFL) is therefore more effective than ciprofloxacin alone. Liposomes can be combined with a variety of drugs that interact with bacterial cell efflux pumps to maintain high sustained levels of antibiotics in bacterial cells.

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.

Effects of Cholesterol on the Partitioning of a Drug Molecule in Lipid Bilayers

Drug molecules either bind to membrane-bound targets or permeate through cell membranes to reach intracellular targets, and hence, their membrane partition and permeation are of great importance. Here, we studied the effects of cholesterol on the partition of amantadine, an antiflu drug molecule, into 1,2-dimyristoyl-sn-glycero-3-phosphocholine bilayers using molecular dynamics simulations. The membrane partition of amantadine is sensitive to the cholesterol mole fraction (x_chol). In the absence of cholesterol, amantadine is stably bound in membranes, but at x_chol = 32%, it can escape to the aqueous phase, in agreement with recent experiments. The reduced membrane partition of amantadine at a high cholesterol content is mainly due to the perturbation of the bilayer structure and dynamics. Surrounding lipids stabilize amantadine by having their tails wrapped around the drug molecule, and this ability is compromised when cholesterol is present to increase the order in lipid tails. The atomic details on interactions with lipids and perturbations by cholesterol revealed here provide insight into membrane partition and delivery of drug molecules to their targets.

Mastering the Gram-negative bacterial barrier - Chemical approaches to increase bacterial bioavailability of antibiotics

To win the battle against resistant, pathogenic bacteria, novel classes of anti-infectives and targets are urgently needed. Bacterial uptake, distribution, metabolic and efflux pathways of antibiotics in Gram-negative bacteria determine what we here refer to as bacterial bioavailability. Understanding these mechanisms from a chemical perspective is essential for anti-infective activity and hence, drug discovery as well as drug delivery. A systematic and critical discussion of in bacterio, in vitro and in silico assays reveals that a sufficiently accurate holistic approach is still missing. We expect new findings based on Gram-negative bacterial bioavailability to guide future anti-infective research.

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.

Shear viscosity prediction of alcohols, hydrocarbons, halogenated, carbonyl, nitrogen-containing, and sulfur compounds using the variable force fields

Viscosity of organic liquids is an important physical property in applications of printing, pharmaceuticals, oil extracting, engineering, and chemical processes. Experimental measurement is a direct but time-consuming process. Accurately predicting the viscosity with a broad range of chemical diversity is still a great challenge. In this work, a protocol named Variable Force Field (VaFF) was implemented to efficiently vary the force field parameters, especially λ_vdW, for the van der Waals term for the shear viscosity prediction of 75 organic liquid molecules with viscosity ranging from -9 to 0 in their nature logarithm and containing diverse chemical functional groups, such as alcoholic hydroxyl, carbonyl, and halogenated groups. Feature learning was applied for the viscosity prediction, and the selected features indicated that the hydrogen bonding interactions and the number of atoms and rings play important roles in the property of viscosity. The shear viscosity prediction of alcohols is very difficult owing to the existence of relative strong intermolecular hydrogen bonding interaction as reflected by density functional theory binding energies. From radial and spatial distribution functions of methanol, we found that the van der Waals related parameters λ_vdW are more crucial to the viscosity prediction than the rotation related parameters, λ_tor. With the variable λ_vdW-based all-atom optimized potentials for liquid simulations force field, a great improvement was observed in the viscosity prediction for alcohols. The simplicity and uniformity of VaFF make it an efficient tool for the prediction of viscosity and other related properties in the rational design of materials with the specific properties.

Gating and regulation of the calcium release-activated calcium channel: Recent progress from experiments and molecular modeling

Calcium release-activated calcium (CRAC) channels are highly calcium ion (Ca²⁺)-selective channels in the plasma membrane. The transient drop of endoplasmic reticulum Ca²⁺ level activates its calcium sensor stromal interaction molecule (STIM) and then triggers the gating of the CRAC channel pore unit Orai. This process involves a variety of activities of the immune system. Therefore, understanding how the activation and regulation of the CRAC channel can be accomplished is essential. Here we briefly summarize the recent progress on Orai gating and its regulation by 2-aminoethoxydiphenylborate (2-APB) obtained from structural biology studies, biochemical and electrophysiological measurements, as well as molecular modeling. Indeed, integration between experiments and computations has further deepened our understanding of the channel gating and regulation.

An Iterative Fragment Scheme for the ACKS2 Electronic Polarization Model: Application to Molecular Dimers and Chains

The treatment of electrostatic interactions is a key ingredient in the force field-based simulation of condensed phase systems. Most approaches used fixed, site-specific point charges. Yet, it is now clear that many applications of force fields (FFs) demand more sophisticated treatments, prompting the implementation of charge equilibration methods in polarizable FFs to allow the redistribution of charge within the system. One approach allowing both, charge redistribution and site-specific polarization, while at the same time solving methodological shortcomings of earlier methods, is the first-principles-derived atom-condensed Kohn-Sham density functional theory method approximated to the second order (ACKS2). In this work, we present two fragment approaches to ACKS2, termed f-ACKS2 and a self-consistent version, scf-ACKS2, that treat condensed phase systems as a collection of electronically polarizable molecular fragments. The fragmentation approach to ACKS2 not only leads to a more transferable and less system-specific collection of electronic response parameters but also opens up the method to large condensed phase systems. We validate the accuracies of f-ACKS2 and scf-ACKS2 by comparing polarization energies and induced dipole moments for a number of charged hydrocarbon dimers against DFT reference calculations. Finally, we also apply both fragmented ACKS2 variants to calculate the polarization energy for electron-hole pair separation along a chain of anthracene molecules and find excellent agreement with reference DFT calculations.

Dynamic Protonation Dramatically Affects the Membrane Permeability of Drug-like Molecules

Permeability (P_m) across biological membranes is of fundamental importance and a key factor in drug absorption, distribution, and development. Although the majority of drugs will be charged at some point during oral delivery, our understanding of membrane permeation by charged species is limited. The canonical model assumes that only neutral molecules partition into and passively permeate across membranes, but there is mounting evidence that these processes are also facile for certain charged species. However, it is unknown whether such ionizable permeants dynamically neutralize at the membrane surface or permeate in their charged form. To probe protonation-coupled permeation in atomic detail, we herein apply continuous constant-pH molecular dynamics along with free energy sampling to study the permeation of a weak base propranolol (PPL), and evaluate the impact of including dynamic protonation on P_m. The simulations reveal that PPL dynamically neutralizes at the lipid-tail interface, which dramatically influences the permeation free energy landscape and explains why the conventional model overestimates the assigned intrinsic permeability. We demonstrate how fixed-charge-state simulations can account for this effect, and propose a revised model that better describes pH-coupled partitioning and permeation. Our results demonstrate how dynamic changes in protonation state may play a critical role in the permeation of ionizable molecules, including pharmaceuticals and drug-like molecules, thus requiring a revision of the standard picture.

Molecular Dynamics Simulations of Membrane Permeability

This Review illustrates the evaluation of permeability of lipid membranes from molecular dynamics (MD) simulation primarily using water and oxygen as examples. Membrane entrance, translocation, and exit of these simple permeants (one hydrophilic and one hydrophobic) can be simulated by conventional MD, and permeabilities can be evaluated directly by Fick's First Law, transition rates, and a global Bayesian analysis of the inhomogeneous solubility-diffusion model. The assorted results, many of which are applicable to simulations of nonbiological membranes, highlight the limitations of the homogeneous solubility diffusion model; support the utility of inhomogeneous solubility diffusion and compartmental models; underscore the need for comparison with experiment for both simple solvent systems (such as water/hexadecane) and well-characterized membranes; and demonstrate the need for microsecond simulations for even simple permeants like water and oxygen. Undulations, subdiffusion, fractional viscosity dependence, periodic boundary conditions, and recent developments in the field are also discussed. Last, while enhanced sampling methods and increasingly sophisticated treatments of diffusion add substantially to the repertoire of simulation-based approaches, they do not address directly the critical need for force fields with polarizability and multipoles, and constant pH methods.

Polarizable Force Fields for Biomolecular Simulations: Recent Advances and Applications

Realistic modeling of biomolecular systems requires an accurate treatment of electrostatics, including electronic polarization. Due to recent advances in physical models, simulation algorithms, and computing hardware, biomolecular simulations with advanced force fields at biologically relevant timescales are becoming increasingly promising. These advancements have not only led to new biophysical insights but also afforded opportunities to advance our understanding of fundamental intermolecular forces. This article describes the recent advances and applications, as well as future directions, of polarizable force fields in biomolecular simulations.