Considerations of Recent All-Atom Lipid Force Field Development

Simulating Bacterial Membrane Models at the Atomistic Level: A Force Field Comparison

Molecular dynamics (MD) simulations are currently an indispensable tool to understand both the dynamic and nanoscale organization of cell membrane models. A large number of quantitative parameters can be extracted from these simulations, but their reliability is determined by the quality of the employed force field and the simulation parameters. Much of the work on parametrizing and optimizing force fields for biomembrane modeling has been focused on homogeneous bilayers with a single phospholipid type. However, these may not perform effectively or could even be unsuitable for lipid mixtures commonly employed in membrane models. This work aims to fill this gap by comparing MD simulation results of several bacterial membrane models using different force fields and simulation parameters, namely, CHARMM36, Slipids, and GROMOS-CKP. Furthermore, the hydrogen isotope exchange (HIE) method, combined with GROMOS-CKP (GROMOS-H2Q), was also tested to check for the impact of this acceleration strategy on the performance of the force field. A common set of simulation parameters was employed for all of the force fields in addition to those corresponding to the original parametrization of each of them. Furthermore, new experimental order parameter values determined from NMR of several lipid mixtures are also reported to compare them with those determined from MD simulations. Our results reveal that most of the calculated physical properties of bacterial membrane models from MD simulations are substantially force field and lipid composition dependent. Some lipid mixtures exhibit nearly ideal behaviors, while the interaction of different lipid types in other mixtures is highly synergistic. None of the employed force fields seem to be clearly superior to the other three, each having its own strengths and weaknesses. Slipids are notably effective at replicating the order parameters for all acyl chains, including those in lipid mixtures, but they offer the least accurate results for headgroup parameters. Conversely, CHARMM provides almost perfect estimates for the order parameters of the headgroups but tends to overestimate those of the lipid tails. The GROMOS parametrizations deliver reasonable order parameters for entire lipid molecules, including multicomponent bilayers, although they do not reach the accuracy of Slipids for tails or CHARMM for headgroups. Importantly, GROMOS-H2Q stands out for its computational efficiency, being at least 3 times faster than GROMOS, which is already faster than both CHARMM and Slipids. In turn, GROMOS-H2Q yields much higher compressibilities compared to all other parametrizations.

Exploring the Properties of Curved Lipid Membranes: Comparative Analysis of Atomistic and Coarse-Grained Force Fields

Curvature emerges as a fundamental membrane characteristic crucial for diverse biological processes, including vesicle formation, cell signaling, and membrane trafficking. Increasingly valuable insights into atomistic details governing curvature-dependent membrane properties are provided by computer simulations. Nevertheless, the underlying force field models are conventionally calibrated and tested in relation to experimentally derived parameters of planar bilayers, thereby leaving uncertainties concerning their consistency in reproducing curved lipid systems. In this study we compare the depiction of buckled phosphatidylcholine (POPC) and POPC-cholesterol membranes by four popular force field models. Aside from agreement with respect to general trends in curvature dependence of a number of parameters, we observe a few qualitative differences. Among the most prominent ones is the difference between atomistic and coarse grained force fields in their representation of relative compressibility of the polar headgroup region and hydrophobic lipid core. Through a number of downstream effects, this discrepancy can influence the way in which curvature modulates the behavior of membrane bound proteins depending on the adopted simulation model.

Passive permeability controls synthesis for the allelochemical sorgoleone in sorghum root exudate

Competition for soil nutrients and water with other plants foster competition within the biosphere for access to these limited resources. The roots for the common grain sorghum produce multiple small molecules that are released via root exudates into the soil to compete with other plants. Sorgoleone is one such compound, which suppresses weed growth near sorghum by acting as a quinone analog and interferes with photosynthesis. Since sorghum also grows photosynthetically, and may be susceptible to sorgoleone action if present in tissues above ground, it is essential to exude sorgoleone efficiently. However, since the P450 enzymes that synthesize sorgoleone are intracellular, the release mechanism for sorgoleone remain unclear. In this study, we conducted an in silico assessment for sorgoleone and its precursors to passively permeate biological membranes. To facilitate accurate simulation, CHARMM parameters were newly optimized for sorgoleone and its precursors. These parameters were used to conduct 1 μs of unbiased molecular dynamics simulations to compare the permeability of sorgoleone with its precursors molecules. We find that interleaflet transfer is maximized for sorgoleone, suggesting that the precursor molecules may remain in the same leaflet for access by biosynthetic P450 enzymes. Since no sorgoleone was extracted during unbiased simulations, we compute a permeability coefficient using the inhomogeneous solubility diffusion model. The requisite free energy and diffusivity profiles for sorgoleone through a sorghum membrane model were determined through Replica Exchange Umbrella Sampling (REUS) simulations. The REUS calculations highlight that any soluble sorgoleone would quickly insert into a lipid bilayer, and would readily transit. When sorgoleone forms aggregates in root exudate as indicated by our equilibrium simulations, aggregate formation would lower the effective concentration in aqueous solution, creating a concentration gradient that would facilitate passive transport. This suggests that sorgoleone synthesis occurs within sorghum root cells and that sorgoleone is exuded by permeating through the cell membrane without the need for a transport protein once the extracellular sorgoleone aggregate is formed.

Ionizable Amino Lipids Distribution and Effects on DSPC/Cholesterol Membranes: Implications for Lipid Nanoparticle Structure

Lipid nanoparticles (LNPs) containing ionizable aminolipids are among the leading platforms for the successful delivery of nucleic-acid-based therapeutics, including messenger RNA (mRNA). The two recently FDA-approved COVID-19 vaccines developed by Moderna and Pfizer/BioNTech belong to this category. Ionizable aminolipids, cholesterol, and DSPC lipids are among the key components of such formulations, crucially modulating physicochemical properties of these formulations and, consequently, the potency of these therapeutics. Despite the importance of these components, the distribution of these molecules in LNPs containing mRNA is not clear. In this study, we used all-atom molecular dynamics (MD) simulations to investigate the distribution and effects of the Lipid-5 (apparent pKa of the lipid nanoparticle = 6.56), a rationally designed and previously reported ionizable aminolipid by Moderna, on lipid bilayers [Mol. Ther. 2018, 26, 1509-1519]. The simulations were conducted with half of the aminolipids charged and half neutral approximately to the expected ionization in the microenvironment of the LNP surface. In all five simulated systems in this work, the cholesterol content was kept constant, whereas the DSPC and Lipid-5 concentrations were changed systematically. We found that at higher concentrations of the ionizable aminolipids, the neutral aminolipids form a disordered aggregate in the membrane interior that preferentially includes cholesterol. The rules underlying the lipid redistribution could be used to rationally choose lipids to optimize the LNP function.

Accurate Simulations of Lipid Monolayers Require a Water Model with Correct Surface Tension

Lipid monolayers provide our lungs and eyes their functionality and serve as proxy systems in biomembrane research. Therefore, lipid monolayers have been studied intensively including using molecular dynamics simulations, which are able to probe their lateral structure and interactions with, e.g., pharmaceuticals or nanoparticles. However, such simulations have struggled in describing the forces at the air-water interface. Particularly, the surface tension of water and long-range van der Waals interactions have been considered critical, but their importance in monolayer simulations has been evaluated only separately. Here, we combine the recent C36/LJ-PME lipid force field that includes long-range van der Waals forces with water models that reproduce experimental surface tensions to elucidate the importance of these contributions in monolayer simulations. Our results suggest that a water model with correct surface tension is necessary to reproduce experimental surface pressure-area isotherms and monolayer phase behavior. The latter includes the liquid expanded and liquid condensed phases, their coexistence, and the opening of pores at the correct area per lipid upon expansion. Despite these improvements of the C36/LJ-PME with certain water models, the standard cutoff-based CHARMM36 lipid model with the 4-point OPC water model still provides the best agreement with experiments. Our results emphasize the importance of using high-quality water models in applications and parameter development in molecular dynamics simulations of biomolecules.

Dynorphin A induces membrane permeabilization by formation of proteolipidic pores. Insights from electrophysiology and computational simulations

Dynorphins are endogenous neuropeptides that function as ligands for the κ-opioid receptor. In addition to opioid activity, dynorphins can induce several pathological effects such as neurological dysfunctions and cell death. Previous studies have suggested that Dynorphin A (DynA) mediates some pathogenic actions through formation of transient pores in lipid domains of the plasma membrane. Here, we use planar bilayer electrophysiology to show that DynA induces pore formation in negatively charged membranes. We find a large variability in pore conformations showing equilibrium conductance fluctuations, what disregards electroporation as the dominant mechanism of pore formation. Ion selectivity measurements showing cationic selectivity indicate that positive protein charges of DynA are stabilized by phosphatidyl serine negative charges in the formation of combined structures. We complement our study with computational simulations that assess the stability of diverse peptide arrangements in the hydrophobic core of the bilayer. We show that DynA is capable of assembling in charged membranes to form water-filled pores that conduct ions.

All-Atom Modeling of Complex Cellular Membranes

Cell membranes are composed of a variety of lipids and proteins where they interact with each other to fulfill their roles. The first step in modeling these interactions in molecular simulations is to have reliable mimetics of the membrane's lipid environment. This Feature Article presents our recent efforts to model complex cellular membranes using all-atom force fields. A short review of the CHARMM36 (C36) lipid force field and its recent update to incorporate the long-range dispersion is presented. Key examples of model membranes mimicking various species and organelles are given. These include single-celled organisms such as bacteria (E. coli., chlamydia, and P. aeruginosa) and yeast (plasma membrane, endoplasmic reticulum, and trans-Golgi network) and more advanced ones such as plants (soybean and Arabidopsis thaliana) and mammals (ocular lens, stratum corneum, and peripheral nerve myelin). Leaflet asymmetry in composition has also been applied to some of these models. With the increased lipid diversity in the C36 lipid FF, these complex models can better reflect the structural, mechanical, and dynamic properties of realistic membranes and open an opportunity to study biological processes involving other molecules.

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.