Bruce Prentiss Murch

Amphiphilic drug-like molecules accumulate in a membrane below the head group region.

The partitioning behavior of drug-like molecules into biomembranes has a crucial impact on the design and efficacy of therapeutic drugs. Thermodynamic properties connected with the interaction of molecules with membranes can be evaluated by calculating free-energy profiles normal to the membrane surface. We calculated the free-energy profiles of 25 drug-like molecules in a 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) membrane and free energies of solvation in water and heptane using two methods, molecular dynamics (MD) simulations with the Berger lipid force field and COSMOmic, based on a continuum conductor-like screening model for realistic solvation (COSMO-RS). The biased MD simulations (in total ∼22 μs long) were relatively computationally expensive, whereas the COSMOmic approach offered a significantly less expensive alternative. Both methods provided similar results and showed that the studied amphiphilic drug-like molecules accumulate in the membrane, with the majority localized below the head group region. The MD simulations were more lipophilic and gave free-energy profiles that were systematically deeper than those calculated by COSMOmic. To investigate the physical nature of the increased lipophilicity, we analyzed a water/heptane system and identified that it is most likely caused by overestimation of the attractive term of the Lennard-Jones potential in lipid tails. We concluded that COSMOmic can be successfully used for high-throughput computations of global thermodynamic properties, for example, partition coefficients and energy barrier heights, in phosphocholine membranes. In contrast, MD is better for investigating local properties like molecular positioning and orientation in the membrane because they more accurately reflect the complex structure of lipid bilayers. MD is also useful for studies of highly complex systems, for example, drug-membrane-protein interactions.

Rationalization of reduced penetration of drugs through ceramide gel phase membrane.

Since computing resources have advanced enough to allow routine molecular simulation studies of drug molecules interacting with biologically relevant membranes, a considerable amount of work has been carried out with fluid phospholipid systems. However, there is very little work in the literature on drug interactions with gel phase lipids. This poses a significant limitation for understanding permeation through the stratum corneum where the primary pathway is expected to be through a highly ordered lipid matrix. To address this point, we analyzed the interactions of p-aminobenzoic acid (PABA) and its ethyl (benzocaine) and butyl (butamben) esters with two membrane bilayers, which differ in their fluidity at ambient conditions. We considered a dioleoylphosphatidylcholine (DOPC) bilayer in a fluid state and a ceramide 2 (CER2, ceramide NS) bilayer in a gel phase. We carried out unbiased (100 ns long) and biased z-constraint molecular dynamics simulations and calculated the free energy profiles of all molecules along the bilayer normal. The free energy profiles converged significantly slower for the gel phase. While the compounds have comparable affinities for both membranes, they exhibit penetration barriers almost 3 times higher in the gel phase CER2 bilayer. This elevated barrier and slower diffusion in the CER2 bilayer, which are caused by the high ordering of CER2 lipid chains, explain the low permeability of the gel phase membranes. We also compared the free energy profiles from MD simulations with those obtained from COSMOmic. This method provided the same trends in behavior for the guest molecules in both bilayers; however, the penetration barriers calculated by COSMOmic did not differ between membranes. In conclusion, we show how membrane fluid properties affect the interaction of drug-like molecules with membranes.

Accurate modeling of ionic surfactants at high concentration.

Molecular dynamics (MD) simulation is a useful tool for simulating formulations of surfactant mixtures from first-principles, which can be used to predict surfactant morphology and other industrially relevant thermodynamic properties. However, the surfactant structure is sensitive to the parameters used in MD simulations, and in the absence of extensive validation against experimental data, it is often not obvious a priori which range of parameter sets to choose. In this work, we compare the performance of ion parameters implemented in nonpolarizable classical MD simulations, and its effect on simulations of an idealized solution of sodium dodecyl sulfate (SDS). We find that previous artifacts reported in simulations of larger SDS constructs are a direct consequence of using parameters that poorly model ionic interactions at high concentration. Using osmotic pressure and/or other thermodynamic properties measured at finite concentration, such as Kirkwood-Buff integrals, is shown to be the most cost-effective means to validate and parametrize existing force fields. Our findings highlight the importance of optimizing intermolecular parameters for simulations of systems with a high local concentration, which may be applicable in other contexts, such as in molecular crowding, hotspot mapping, protein folding, and modeling pH effects.

Predicting proton titration in cationic micelle and bilayer environments.

Knowledge of the protonation behavior of pH-sensitive molecules in micelles and bilayers has significant implications in consumer product development and biomedical applications. However, the calculation of pKas in such environments proves challenging using traditional structure-based calculations. Here we apply all-atom constant pH molecular dynamics with explicit ions and titratable water to calculate the pKa of a fatty acid molecule in a micelle of dodecyl trimethylammonium chloride and liquid as well as gel-phase bilayers of diethyl ester dimethylammonium chloride. Interestingly, the pKa of the fatty acid in the gel bilayer is 5.4, 0.4 units lower than that in the analogous liquid bilayer or micelle, despite the fact that the protonated carboxylic group is significantly more desolvated in the gel bilayer. This work illustrates the capability of all-atom constant pH molecular dynamics in capturing the delicate balance in the free energies of desolvation and Coulombic interactions. It also shows the importance of the explicit treatment of ions in sampling the protonation states. The ability to model dynamics of pH-responsive substrates in a bilayer environment is useful for improving fabric care products as well as our understanding of the side effects of anti-inflammatory drugs.

The Procter and Gamble Company: Current State and Future Needs in Materials Modeling

New material development and commercial application is often quite complex due to the material properties and multiple transformations materials undergo in the supply chain, manufacturing process, and distribution of the finished product. In the fast-moving consumer goods industry of personal and household care products, these complexities are particularly acute due to the focus on and use of “commodity” materials that, at times, have significant variability in material properties. These materials are often formulated into complex liquids or assembled products, which undergo multiple transformations during making and can further undergo additional changes during distribution and use by the consumer (some desired, some not). At each stage of development, manufacturing, and distribution, materials models can be tremendously helpful in material and process selection and optimization. This chapter provides an overview of the current state-of-the-art in materials modeling as applied to the soft materials typically used in household and personal care products, with particular focus on modeling tools that span the length and time scales most relevant for modeling. We review the tools and methods in materials modeling and provide several examples where these tools have been used to guide the development of new materials. We conclude with commentary on additional advancements needed to drive practical application of these modeling tools more broadly for material development.