Effect of dipole moment on amphiphile solubility and partition into liquid ordered and liquid disordered phases in lipid bilayers

Permeation of a Homologous Series of NBD-Labeled Fatty Amines through Lipid Bilayers: A Molecular Dynamics Study

Permeation through biomembranes is ubiquitous for drugs to reach their active sites. Asymmetry of the cell plasma membrane (PM) has been described as having an important role in this process. Here we describe the interaction of a homologous series of 7-nitrobenz-2-oxa-1,3-diazol-4-yl (NBD)-labeled amphiphiles (NBD-Cn, n = 4 to 16) with lipid bilayers of different compositions (1-palmitoyl, 2-oleoyl-sn-glycero-3-phosphocholine (POPC):cholesterol (1:1) and palmitoylated sphingomyelin (SpM):cholesterol (6:4)), including an asymmetric bilayer. Both unrestrained and umbrella sampling (US) simulations (at varying distances to the bilayer center) were carried out. The free energy profile of NBD-Cn at different depths in the membrane was obtained from the US simulations. The behavior of the amphiphiles during the permeation process was described regarding their orientation, chain elongation, and H-bonding to lipid and water molecules. Permeability coefficients were also calculated for the different amphiphiles of the series, using the inhomogeneous solubility-diffusion model (ISDM). Quantitative agreement with values obtained from kinetic modeling of the permeation process could not be obtained. However, for the longer, and more hydrophobic amphiphiles, the variation trend along the homologous series was qualitatively better matched by the ISDM when the equilibrium location of each amphiphile was taken as reference (ΔG = 0), compared to the usual choice of bulk water.

Interaction of 5-Fluorouracil on the Surfaces of Pristine and Functionalized Ca12O12 Nanocages: An Intuition from DFT

The utilization of nanostructured materials for several biomedical applications has tremendously increased over the last few decades owing to their nanosizes, porosity, large surface area, sensitivity, and efficiency as drug delivery systems. Thus, the incorporation of functionalized and pristine nanostructures for cancer therapy offers substantial prospects to curb the persistent problems of ineffective drug administration and delivery to target sites. The potential of pristine (Ca₁₂O₁₂) and formyl (-CHO)- and amino (-NH₂)-functionalized (Ca₁₂O₁₂-CHO and Ca₁₂O₁₂-NH₂) derivatives as efficient nanocarriers for 5-fluorouracil (5FU) was studied at the B3LYP-GD3(BJ)/6-311++G(d,p) theoretical level in two electronic media (gas and solvent). To effectively account for all adsorption interactions of the drug on the investigated surfaces, electronic studies as well as topological analysis based on the quantum theory of atoms in molecules (QTAIM) and noncovalent interactions were exhaustively utilized. Interestingly, the obtained results divulged that the 5FU drug interacted favorably with both Ca₁₂O₁₂ and its functionalized derivatives. The adsorption energies of pristine and functionalized nanostructures were calculated to be -133.4, -96.9, and -175.6 kcal/mol, respectively, for Ca₁₂O₁₂, Ca₁₂O₁₂-CHO, and Ca₁₂O₁₂-NH2. Also, both topological analysis and NBO stabilization analysis revealed the presence of interactions among O₃-H₃₂, O₂₇-C₂₄, O₁₀-C₂₇, and N₂₄-H₃₂ atoms of the drug and the surface. However, 5FU@Ca₁₂O₁₂-CHO molecules portrayed the least adsorption energy due to considerable destabilization of the molecular complex as revealed by the computed deformation energy. Therefore, 5FU@Ca₁₂O₁₂ and 5FU@Ca₁₂O₁₂-NH₂ acted as better nanovehicles for 5FU.

Analysis of the Equilibrium Distribution of Ligands in Heterogeneous Media–Approaches and Pitfalls

The equilibrium distribution of small molecules (ligands) between binding agents in heterogeneous media is an important property that determines their activity. Heterogeneous systems containing proteins and lipid membranes are particularly relevant due to their prevalence in biological systems, and their importance to ligand distribution, which, in turn, is crucial to ligand’s availability and biological activity. In this work, we review several approaches and formalisms for the analysis of the equilibrium distribution of ligands in the presence of proteins, lipid membranes, or both. Special attention is given to common pitfalls in the analysis, with the establishment of the validity limits for the distinct approaches. Due to its widespread use, special attention is given to the characterization of ligand binding through the analysis of Stern–Volmer plots of protein fluorescence quenching. Systems of increasing complexity are considered, from proteins with single to multiple binding sites, from ligands interacting with proteins only to biomembranes containing lipid bilayers and membrane proteins. A new formalism is proposed, in which ligand binding is treated as a partition process, while considering the saturation of protein binding sites. This formalism is particularly useful for the characterization of interaction with membrane proteins.

Δ-Quantum machine-learning for medicinal chemistry

Many molecular design tasks benefit from fast and accurate calculations of quantum-mechanical (QM) properties. However, the computational cost of QM methods applied to drug-like molecules currently renders large-scale applications of quantum chemistry challenging. Aiming to mitigate this problem, we developed DelFTa, an open-source toolbox for the prediction of electronic properties of drug-like molecules at the density functional (DFT) level of theory, using Δ-machine-learning. Δ-Learning corrects the prediction error (Δ) of a fast but inaccurate property calculation. DelFTa employs state-of-the-art three-dimensional message-passing neural networks trained on a large dataset of QM properties. It provides access to a wide array of quantum observables on the molecular, atomic and bond levels by predicting approximations to DFT values from a low-cost semiempirical baseline. Δ-Learning outperformed its direct-learning counterpart for most of the considered QM endpoints. The results suggest that predictions for non-covalent intra- and intermolecular interactions can be extrapolated to larger biomolecular systems. The software is fully open-sourced and features documented command-line and Python APIs.

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.

C-Glucosylation as a tool for the prevention of PAINS-induced membrane dipole potential alterations

The concept of Pan-Assay Interference Compounds (PAINS) is regarded as a threat to the recognition of the broad bioactivity of natural products. Based on the established relationship between altered membrane dipole potential and transmembrane protein conformation and function, we investigate here polyphenols' ability to induce changes in cell membrane dipole potential. Ultimately, we are interested in finding a tool to prevent polyphenol PAINS-type behavior and produce compounds less prone to untargeted and promiscuous interactions with the cell membrane. Di-8-ANEPPS fluorescence ratiometric measurements suggest that planar lipophilic polyphenols-phloretin, genistein and resveratrol-act by decreasing membrane dipole potential, especially in cholesterol-rich domains such as lipid rafts, which play a role in important cellular processes. These results provide a mechanism for their labelling as PAINS through their ability to disrupt cell membrane homeostasis. Aiming to explore the role of C-glucosylation in PAINS membrane-interfering behavior, we disclose herein the first synthesis of 4-glucosylresveratrol, starting from 5-hydroxymethylbenzene-1,3-diol, via C-glucosylation, oxidation and Horner-Wadsworth-Emmons olefination, and resynthesize phloretin and genistein C-glucosides. We show that C-glucosylation generates compounds which are no longer able to modify membrane dipole potential. Therefore, it can be devised as a strategy to generate bioactive natural product derivatives that no longer act as membrane dipole potential modifiers. Our results offer a new technology towards rescuing bioactive polyphenols from their PAINS danger label through C-C ligation of sugars.