Pathway for insertion of amphiphilic nanoparticles into defect-free lipid bilayers from atomistic molecular dynamics simulations

Gold nanoparticles (NPs) have been increasingly used in biological applications that involve potential contact with cellular membranes. As a result, it is essential to gain a physical understanding of NP-membrane interactions to guide the design of next-generation bioactive nanoparticles. In previous work, we showed that charged, amphiphilic NPs can fuse with lipid bilayers after contact between protruding solvent-exposed lipid tails and the NP monolayer. Fusion was only observed at the high-curvature edges of large bilayer defects, but not in low-curvature regions where protrusions are rarely observed. Here, we use atomistic molecular dynamics simulations to show that the same NPs can also fuse with low-curvature bilayers in the absence of defects if NP-protrusion contact occurs, generalizing the results of our previous work. Insertion proceeds without applying biasing forces to the NP, driven by the hydrophobic effect, and involves the transient generation of bilayer curvature. We further find that NPs with long hydrophobic ligands can insert a single ligand into the bilayer core in a manner similar to the binding of peripheral proteins. Such anchoring may precede insertion, revealing potential methods for engineering NP monolayers to enhance NP-bilayer fusion in systems with a low likelihood of lipid tail protrusions. These results reveal new pathways for NP-bilayer fusion and provide fundamental insight into behavior at the nano-bio interface.National Science Foundation (U.S.). Materials Research Science and Engineering Centers (Program) (Award DMR-0819762)National Science Foundation (U.S.) (CAREER Award DMR-1054671

Regulation of multispanning membrane protein topology via post-translational annealing

The canonical mechanism for multispanning membrane protein topogenesis suggests that protein topology is established during cotranslational membrane integration. However, this mechanism is inconsistent with the behavior of EmrE, a dual-topology protein for which the mutation of positively charged loop residues, even close to the C-terminus, leads to dramatic shifts in its topology. We use coarse-grained simulations to investigate the Sec-facilitated membrane integration of EmrE and its mutants on realistic biological timescales. This work reveals a mechanism for regulating membrane-protein topogenesis, in which initially misintegrated configurations of the proteins undergo post-translational annealing to reach fully integrated multispanning topologies. The energetic barriers associated with this post-translational annealing process enforce kinetic pathways that dictate the topology of the fully integrated proteins. The proposed mechanism agrees well with the experimentally observed features of EmrE topogenesis and provides a range of experimentally testable predictions regarding the effect of translocon mutations on membrane protein topogenesis

Solvent-exposed lipid tail protrusions depend on lipid membrane composition and curvature

The stochastic protrusion of hydrophobic lipid tails into solution, a subclass of hydrophobic membrane defects, has recently been shown to be a critical step in a number of biological processes like membrane fusion. Understanding the factors that govern the appearance of lipid tail protrusions is critical for identifying membrane features that affect the rate of fusion or other processes that depend on contact with solvent-exposed lipid tails. In this work, we utilize atomistic molecular dynamics simulations to characterize the likelihood of tail protrusions in phosphotidylcholine lipid bilayers of varying composition, curvature, and hydration. We distinguish two protrusion modes corresponding to atoms near the end of the lipid tail or near the glycerol group. Through potential of mean force calculations, we demonstrate that the thermodynamic cost for inducing a protrusion depends on tail saturation but is insensitive to other bilayer structural properties or hydration above a threshold value. Similarly, highly curved vesicles or micelles increase both the overall frequency of lipid tail protrusions as well as the preference for splay protrusions, both of which play an important role in driving membrane fusion. In multi-component bilayers, however, the incidence of protrusion events does not clearly depend on the mismatch between tail length or tail saturation of the constituent lipids. Together, these results provide significant physical insight into how system components might affect the appearance of protrusions in biological membranes, and help explain the roles of composition or curvature-modifying proteins in membrane fusion.National Science Foundation (U.S.). MRSEC Program (award number DMR-0819762)National Science Foundation (U.S.). Faculty Early Career Development Program (Award No. DMR-1054671)United States. Department of Energy. Computational Science Graduate Fellowship Program (grant number DE-FG02-97ER25308)National Science Foundation (U.S.) (grant number OCI-1053575

Uncertainty Quantification for Molecular Property Predictions with Graph Neural Architecture Search

Graph Neural Networks (GNNs) have emerged as a prominent class of data-driven methods for molecular property prediction. However, a key limitation of typical GNN models is their inability to quantify uncertainties in the predictions. This capability is crucial for ensuring the trustworthy use and deployment of models in downstream tasks. To that end, we introduce AutoGNNUQ, an automated uncertainty quantification (UQ) approach for molecular property prediction. AutoGNNUQ leverages architecture search to generate an ensemble of high-performing GNNs, enabling the estimation of predictive uncertainties. Our approach employs variance decomposition to separate data (aleatoric) and model (epistemic) uncertainties, providing valuable insights for reducing them. In our computational experiments, we demonstrate that AutoGNNUQ outperforms existing UQ methods in terms of both prediction accuracy and UQ performance on multiple benchmark datasets. Additionally, we utilize t-SNE visualization to explore correlations between molecular features and uncertainty, offering insight for dataset improvement. AutoGNNUQ has broad applicability in domains such as drug discovery and materials science, where accurate uncertainty quantification is crucial for decision-making

Structurally detailed coarse-grained model for Sec-facilitated co-translational protein translocation and membrane integration

We present a coarse-grained simulation model that is capable of simulating the minute-timescale dynamics of protein translocation and membrane integration via the Sec translocon, while retaining sufficient chemical and structural detail to capture many of the sequence-specific interactions that drive these processes. The model includes accurate geometric representations of the ribosome and Sec translocon, obtained directly from experimental structures, and interactions parameterized from nearly 200 μs of residue-based coarse-grained molecular dynamics simulations. A protocol for mapping amino-acid sequences to coarse-grained beads enables the direct simulation of trajectories for the co-translational insertion of arbitrary polypeptide sequences into the Sec translocon. The model reproduces experimentally observed features of membrane protein integration, including the efficiency with which polypeptide domains integrate into the membrane, the variation in integration efficiency upon single amino-acid mutations, and the orientation of transmembrane domains. The central advantage of the model is that it connects sequence-level protein features to biological observables and timescales, enabling direct simulation for the mechanistic analysis of co-translational integration and for the engineering of membrane proteins with enhanced membrane integration efficiency

Effect of Particle Diameter and Surface Composition on the Spontaneous Fusion of Monolayer-Protected Gold Nanoparticles with Lipid Bilayers

Anionic, monolayer-protected gold nanoparticles (AuNPs) have been shown to nondisruptively penetrate cellular membranes. Here, we show that a critical first step in the penetration process is potentially the fusion of such AuNPs with lipid bilayers. Free energy calculations, experiments on unilamellar and multilamellar vesicles, and cell studies all support this hypothesis. Furthermore, we show that fusion is only favorable for AuNPs with core diameters below a critical size that depends on the monolayer composition.National Science Foundation (U.S.). Graduate Research Fellowship ProgramNational Science Foundation (U.S.). Materials Research Science and Engineering Centers (Program) (Award DMR-0819762)National Cancer Institute (U.S.) (Award U54CA143874)United States. Army Research Office (Contract W911NF-13-D-0001)United States. Army Research Office (Contract W911NF-07-D-0004, T.O. 8

Communication: Lateral phase separation of mixed polymer brushes physisorbed on planar substrates

Here, we present a new method to model lateral phase separation in mixed polymer brushes physisorbed to a planar surface with mobile grafting points. The model is based on a local mean field theory that combines a Flory-Huggins approximation for interaction enthalpies with an Alexander-de Gennes brush entropy contribution. Using Monte Carlo sampling, the application of these two interactions to a lattice model yields a range of phase behavior consistent with previous theoretical and experimental work. This model will be useful for predicting mixed polymer brush morphologies on planar surfaces and in principle can be extended to other geometries (e.g., spheres) and polymer systems.National Science Foundation (U.S.) (Graduate Research Fellowship Program)National Science Foundation (U.S.). Materials Research Science and Engineering Centers (Program) (DMR–0819762

data

Simulation input parameters, output configurations, and system preparation scripts needed to reproduce simulations performed in the main text. In addition, the processed data and instructions on the data was generated for each figure is included

Energy landscape for the insertion of amphiphilic nanoparticles into lipid membranes: A computational study.

Amphiphilic, monolayer-protected gold nanoparticles (NPs) have been shown to enter cells via a non-endocytic, non-disruptive pathway that could be valuable for biomedical applications. The same NPs were also found to insert into a series of model cell membranes as a precursor to cellular uptake, but the insertion mechanism remains unclear. Previous simulations have demonstrated that an amphiphilic NP can insert into a single leaflet of a planar lipid bilayer, but in this configuration all charged end groups are localized to one side of the bilayer and it is unknown if further insertion is thermodynamically favorable. Here, we use atomistic molecular dynamics simulations to show that an amphiphilic NP can reach the bilayer midplane non-disruptively if charged ligands iteratively "flip" across the bilayer. Ligand flipping is a favorable process that relaxes bilayer curvature, decreases the nonpolar solvent-accessible surface area of the NP monolayer, and increases attractive ligand-lipid electrostatic interactions. Analysis of end group hydration further indicates that iterative ligand flipping can occur on experimentally relevant timescales. Supported by these results, we present a complete energy landscape for the non-disruptive insertion of amphiphilic NPs into lipid bilayers. These findings will help guide the design of NPs to enhance bilayer insertion and non-endocytic cellular uptake, and also provide physical insight into a possible pathway for the translocation of charged biomacromolecules