Biology subjects

van Hilten, N.

Publications and source records attributed to van Hilten, N..

8 recordsLinked to original sources

bioRxiv2026

Hydrophobic mismatch induces lipid sorting based on tail unsaturation

Biological membranes contain a diverse set of membrane proteins surrounded by many different lipids, and the lateral organization and function of these molecules are closely intertwined. Here, we use coarse-grained molecular dynamics (MD) simulations to explore how hydrophobic mismatch between the length of transmembrane (TM) proteins and the thickness of the surrounding lipid membrane impacts the spatial distribution of the lipids. We constructed idealized cylindrically symmetric proteins, inspired by the "Mattress Model" developed in the 1980s, and simulated these model proteins in different lipid compositions. We found that unsaturated lipids were attracted to short TM proteins that thinned the membrane, while fully saturated lipids were attracted to long TM proteins that induced membrane extension. A simple mechanical description of the membrane deformation energy coupled to a lipid mixing model accurately predicted the enrichment/depletion, which was up to 33% in some cases. Our simulations also highlight that lipid sorting behavior is sensitive to protein tilt and protein surface roughness. By teasing out the fundamental physical principles in these simple models, our results provide a foundational understanding of how proteins and lipids form complex and transient assemblies, which we believe will be important for interpreting lipid-protein interactions for a host of membrane proteins that regulate cellular membranes and cell function. SIGNIFICANCETransmembrane (TM) proteins in the eukaryotic plasma membrane are solvated by hundreds of lipid species with different head group chemistries and tail configurations. This work explores how the number of double C-C bonds in the lipid acyl chains (unsaturations) affects the enrichment and depletion of lipid species around TM proteins that exhibit hydrophobic mismatch: i.e., they are either too long or too short for the membrane. We use molecular simulation and elastic modeling to show that short TM proteins attract unsaturated lipids, while long TM proteins attract saturated ones. This finding unlocks a currently understudied aspect of protein-lipid interactions that has important implications for our fundamental understanding of membrane proteins.

biophysics↗

bioRxiv2025

A cell-based scrambling assay reveals phospholipid headgroup preference of TMEM16F on the plasma membrane

The asymmetric resting distribution of the three major phospholipid classes on the mammalian plasma membrane, with phosphatidylserine and phosphatidylethanolamine mostly on the inner leaflet, and phosphatidylcholine mostly on the outer leaflet, is maintained by ATP-dependent flippases and floppases that exhibit headgroup selectivity. Upon signaling cues, this asymmetry can be dissipated by various phospholipid scramblases, allowing cells to respond to stimuli and adapt to different physiological contexts. The prevailing view in the field is that phospholipid scramblases on the plasma membrane act without headgroup preference. Here we report contrary experimental evidence based on a phospholipid scrambling assay that quantifies the fluorescence polarization of nitrobenzoxadiazole-labeled phospholipids for kinetic monitoring of phospholipid scrambling on the plasma membrane of living cells. Our experiments reveal that the plasma membrane-residing calcium-activated phospholipid scramblase TMEM16F preferentially acts on phosphatidylserine and phosphatidylcholine over phosphatidylethanolamine. Significance StatementPhospholipid scramblases on the mammalian plasma membrane are thought to act promiscuously without preference for headgroup. Thoroughly addressing this question, however, requires the development of new methodologies. We devised a cell-based phospholipid scrambling assay that utilizes the fluorescence polarization of nitrobenzoxadiazole (NBD)-labeled phospholipids, allowing the monitoring of their scrambling in a native environment. We discovered that the plasma membrane-residing calcium-activated phospholipid scramblase TMEM16F preferentially acts on phosphatidylserine and phosphatidylcholine over phosphatidylethanolamine. Major Classification: Biological Sciences; Minor Classification: Cell biology, Biophysics and Computational Biology

cell biology↗

bioRxiv2024

Robust lipid scrambling by TMEM16 proteins requires an open groove and thin membrane

Biological membranes are complex and dynamic structures with different populations of lipids in their inner and outer leaflets. The Ca2+-activated TMEM16 family of membrane proteins plays an important role in collapsing this asymmetric lipid distribution by spontaneously, and bidirectionally, scrambling phospholipids between the two leaflets, which can initiate signaling and alter the physical properties of the membrane. While evidence shows that lipid scrambling can occur via an open hydrophilic pathway ("groove") that spans the membrane, it remains unclear if all family members facilitate lipid movement in this manner. Here we present a comprehensive computational study of lipid scrambling by all TMEM16 members with experimentally solved structures. We performed coarse-grained molecular dynamics (MD) simulations of 27 structures from five different family members solved under activating and non-activating conditions, and we captured over 700 scrambling events in aggregate. This enabled us to directly compare scrambling rates, mechanisms, and protein-lipid interactions for fungal and mammalian TMEM16s, in both open (Ca2+-bound) and closed (Ca2+-free) conformations with statistical rigor. We show that all TMEM16 structures thin the membrane and that the majority of scrambling (>90%) occurs at the groove only when TM4 and TM6 have sufficiently separated. Surprisingly, we also observed 60 scrambling events that occurred outside the canonical groove, over 90% of which took place at the dimer-dimer interface in mammalian TMEM16s. This new site suggests an alternative mechanism for lipid scrambling in the absence of an open groove. Impact StatementThe majority of TMEM16 lipid scrambling occurs in the open groove associated with Ca2+-activation, but limited scrambling also occurs in the dimer interface independent of Ca2+.

biophysics↗

bioRxiv2023

Cofilin-Driven Nuclear Deformation Drives Dendritic Cell Migration through the Extracellular Matrix

To mount an adaptive immune response, dendritic cells must process antigens, migrate to lymph nodes and form synapses with T cells. Critical to 3D migration and mechano-sensing is the nucleus, which is the size-limiting barrier for navigation through gaps in the extracellular matrix. Here, we show that inflammatory activation of dendritic cells leads to the nucleus becoming spherically deformed, adopting a raison-like shape and enables dendritic cells to overcome the typical 2 - 3-micron pore limit for 3D-migration. We show that the nuclear shape-change is partially attained through reduced cell adhesion, whereas improved migration through extracellular matrix is achieved through reprogramming of the actin cytoskeleton. Specifically we show that cofilin-1 is phosphorylated at serine 41 drives the assembly of a Cofilin-ActoMyosin (CAM)-ring proximal to the nucleus and enhancing migration through 3D collagen gels. In summary, these data describe novel signaling events through which dendritic cells simultaneously deform their nucleus and enhance their migratory capacity; molecular events that may be re-capitulated in other contexts such as wound healing and cancer.

cell biology↗

bioRxiv2023

PMIpred: A physics-informed web server for quantitative Protein-Membrane Interaction prediction

MotivationMany membrane peripheral proteins have evolved to transiently interact with the surface of (curved) lipid bilayers. Currently, methods to quantitatively predict sensing and binding free energies for protein sequences or structures are lacking, and such tools could greatly benefit the discovery of membrane-interacting motifs, as well as their de novo design. ResultsHere, we trained a transformer neural network model on molecular dynamics data for >50,000 peptides that is able to accurately predict the (relative) membrane-binding free energy for any given amino acid sequence. Using this information, our physics-informed model is able to classify a peptides membrane-associative activity as either non-binding, curvature sensing, or membrane binding. Moreover, this method can be applied to detect membraneinteraction regions in a wide variety of proteins, with comparable predictive performance as state-of-the-art data-driven tools like DREAMM, PPM3, and MODA, but with a wider applicability regarding protein diversity, and the added feature to distinguish curvature sensing from general membrane binding. AvailabilityWe made these tools available as a web server, coined Protein-Membrane Interaction predictor (PMIpred), which can be accessed at https://pmipred.fkt.physik.tu-dortmund.de.

biophysics↗

bioRxiv2022

Physics-based inverse design of lipid packing defect sensing peptides; distinguishing sensors from binders

Proteins can specifically bind to curved membranes through curvature-induced hydrophobic lipid packing defects. The chemical diversity among such curvature sensors challenges our understanding of how they differ from general membrane binders, that bind without curvature selectivity. Here, we combine an evolutionary algorithm with coarse-grained molecular dynamics simulations (Evo-MD) to resolve the peptide sequences that optimally recognize the curvature of lipid membranes. We subsequently demonstrate how a synergy between Evo-MD and a neural network (NN) can enhance the identification and discovery of curvature sensing peptides and proteins. To this aim, we benchmark a physics-trained NN model against experimental data and show that we can correctly identify known sensors and binders. We illustrate that sensing and binding are in fact phenomena that lie on the same thermodynamic continuum, with only subtle but explainable differences in membrane binding free energy, consistent with the serendipitous discovery of sensors. TeaserAI-based design helps explain curvature-selective membrane binding behavior.

biophysics↗

bioRxiv2022

Efficient quantification of lipid packing defect sensing by amphipathic peptides; comparing Martini 2 & 3 with CHARMM36

In biological systems, proteins can be attracted to curved or stretched regions of lipid bilayers by sensing hydrophobic defects in the lipid packing on the membrane surface. Here, we present an efficient end-state free energy calculation method to quantify such sensing in molecular dynamics simulations. We illustrate that lipid packing defect sensing can be defined as the difference in mechanical work required to stretch a membrane with and without a peptide bound to the surface. We also demonstrate that a peptides ability to concurrently induce excess leaflet area (tension) and elastic softening - a property we call the characteristic area of sensing (CHAOS) - and lipid packing sensing behavior are in fact two sides of the same coin. In essence, defect sensing displays a peptides propensity to generate tension. The here-proposed mechanical pathway is equally accurate yet, computationally, about 40 times less costly than the commonly used alchemical pathway (thermodynamic integration), allowing for more feasible free energy calculations in atomistic simulations. This enabled us to directly compare the Martini 2 and 3 coarse-grained and the CHARMM36 atomistic force-fields in terms of relative binding free energies for six representative peptides including the curvature sensor ALPS and two antiviral amphipathic helices (AH). We observed that Martini 3 qualitatively reproduces experimental trends, whilst producing substantially lower (relative) binding free energies and shallower membrane insertion depths compared to atomistic simulations. In contrast, Martini 2 tends to overestimate (relative) binding free energies. Finally, we offer a glimpse into how our end-state based free energy method can enable the inverse design of optimal lipid packing defect sensing peptides when used in conjunction with our recently developed Evolutionary Molecular Dynamics (Evo-MD) method. We argue that these optimized defect sensors - aside from their biomedical and biophysical relevance - can provide valuable targets for the development of lipid force-fields. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/482978v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@1872c25org.highwire.dtl.DTLVardef@1635f0eorg.highwire.dtl.DTLVardef@f5ad91org.highwire.dtl.DTLVardef@156209f_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2021

Inverse design of cholesterol attracting transmembrane helices reveals a paradoxical role of hydrophobic length

The occurrence of linear cholesterol-recognition motifs in alpha-helical transmembrane domains has long been debated. Here, we demonstrate the ability of a genetic algorithm guided by coarse-grained molecular dynamics simulations--a method coined evolutionary molecular dynamics (Evo-MD)--to directly resolve the sequence which maximally attracts cholesterol for single-pass alpha-helical transmembrane domains (TMDs). We illustrate that the evolutionary landscape of cholesterol attraction in membrane proteins is characterized by a sharp, well-defined global optimum. Surprisingly, this optimal solution features an unusual short, slender hydrophobic block surrounded by three successive lysines. Owing to the membrane thickening effect of cholesterol, cholesterol-enriched ordered phases favor TMDs characterized by a long rather than a too short hydrophobic length (a negative hydrophobic mismatch). However, this short hydrophobic pattern evidently offers a pronounced net advantage for the attraction of free cholesterol in both coarse-grained and atomistic simulations. We illustrate that optimal cholesterol attraction is in fact based on the superposition of two distinct structural features: (i) slenderness and (ii) hydrophobic mismatch. In addition, we explore the evolutionary occurrence and feasibility of the two features by analyzing existing databases of membrane proteins and through the direct expression of analogous short hydrophobic sequences in live cell assays. The puzzling sequence variability of proposed linear cholesterol-recognition motifs is indicative of a sub-optimal membrane-mediated attraction of cholesterol which markedly differs from ligand binding based on shape compatibility. Significance StatementOur work demonstrates how a synergy between evolutionary algorithms and high-throughput coarse-grained molecular dynamics can yield fundamentally new insights into the evolutionary fingerprints of protein-mediated lipid sorting. We illustrate that the evolutionary landscape of cholesterol attraction in isolated transmembrane domains is characterized by a well-defined global optimum. In contrast, sub-optimal attraction of cholesterol is associated with a diverse solution space and features a high sequence variability despite acting on the same unique molecule. The contrasting physicochemical nature of the resolved attraction optimum suggests that cholesterol attraction via linear motifs does not pose a dominant pressure on the evolution of transmembrane proteins.

biophysics↗