Biology subjects

Risselada, H. J.

Publications and source records attributed to Risselada, H. J..

13 recordsLinked to original sources

bioRxiv2026

A narrow thermodynamic design window governs selective membrane permeabilization and antiviral activity of amphipathic peptides

Designing molecules that selectively target therapeutically relevant membranes, such as viral envelopes, while sparing host cells is challenging: these membranes closely resemble host bilayers, so selectivity must exploit subtle lipid composition and curvature differences and demands precise tuning of affinity and hydrophobicity, yet curated sequence-specificity data are scarce. Here we show that selective membrane permeabilization and membrane-selective activity of amphipathic peptides are governed by a narrow thermodynamic design window defined by membrane curvature affinity and molecular hydrophobicity. Using a physics-driven generative workflow combining evolutionary molecular dynamics and a transformer predictor (PMIpred), we systematically explored and thermodynamically mapped peptide sequence space de novo without reliance on natural templates or experimental training data. Across four design generations we synthesized and experimentally characterized 43 peptides. Mapping functional activity onto a low-dimensional free-energy landscape reveals a confined thermodynamic "sweet spot" separating weak membrane binding from excessive hydrophobic association and cytotoxicity. Peptides operating within this regime efficiently permeabilize model membranes while maintaining low cellular toxicity. Antiviral activity against Zika virus and HIV-1 emerges in the same region but depends sensitively on membrane lipid composition. Quantitative thermodynamic design rules emerge for membrane-active peptides, illustrating how low-dimensional free-energy landscapes can guide the engineering of selective interactions at soft-matter interfaces.

biophysics↗

bioRxiv2026

The missing link between biomolecular condensates and amyloid fibrils

The traditional view of protein self-assembly posits a binary choice between phase separation into fluid condensates and nucleation into crystalline amyloid fibers. However, this framework is incomplete. Experiments show that liquid condensates are non-equilibrium systems that mature into solid-like structures mediated by amphiphilic prion-like domains (PLDs). Being spatially organized yet dynamic, lyotropic phases represent an intermediate regime between these states. Using physics-based de novo protein design (Evo-MD), we identify a vast amphiphilic motif space encoding fluid lyotropic phases (e.g., micelles and bicelles). TEM, CD, and AlphaFold predictions confirm that these motifs also assemble into amyloid-based hydrogels as thermodynamic endpoints. Notably, the molecular grammar of lyotropic motifs overlaps strongly with that of PLDs and LARKS. Thus, while PLDs likely evolved to stabilize condensates through transient interactions near criticality, our results show that these same amphiphilic forces inherently encode lyotropic structuring and subsequent amyloid formation - linking functional condensation with pathological aggregation.

biophysics↗

bioRxiv2025

Lipidomic Profile Reconstruction of TherapeuticMembrane Targets Using Physics-BasedOptimization with Limited Activity Data

Membrane-targeting peptide motifs recognize characteristic features of biological membrane targets through specific interactions with their lipid composition. To elucidate the complex relationship between binding sequences and lipid composition, we propose an alternative computational framework to leverage limited sequence activity data by combining genetic algorithms with coarse-grained molecular dynamics simulations. We demonstrate through evolutionary optimization of plasma membrane lipid compositions how four true positive and four false positive antimicrobial peptide sequences encode sufficient information to resolve model membranes with a discriminative affinity of peptides that matches the accuracy of state-of-the-art antimicrobial classification. This finding reveals how subtle differences in lipid composition precisely control the selective binding of membrane-associated proteins, thereby regulating their trafficking, aggregation, and function within living cells. Our methodology reconstructs lipidomic profiles from limited sequence data, uniquely revealing targeting patterns for therapeutic peptides and the selectivity mechanisms of membrane-associated proteins.

biophysics↗

bioRxiv2025

Membrane curvature regulates Ups1 dependent phosphatidic acid transfer across lipid bilayers

Mitochondria are essential organelles in eukaryotic cells, enclosed by two membranes with distinct compositions and functions. In addition to the endoplasmic reticulum, mitochondria are major sites of cellular lipid production. Cardiolipin, for example, is exclusively synthesized in the mitochondrial inner membrane. This requires the precursor lipid phosphatidic acid to be imported from the endoplasmic reticulum to the mitochondrial outer membrane. Subsequently phosphatidic acid is transferred to the inner membrane by the lipid transfer protein Ups1/PRELID1. The regulation of this process, the role of membrane physico-chemical properties, and the mechanisms by which energy barriers are overcome during lipid extraction and insertion remain poorly understood. Here, we demonstrate that Ups1 exhibits a strong preference for binding to positively curved membrane regions. Our findings reveal that phosphatidic acid extraction is energetically favored at these membrane domains, leading to enhanced lipid transfer between membranes with high positive curvature and we show that events at the donor membrane are rate limiting for the transfer cycle. Our data suggest that Ups1 membrane binding is modulated by pH, lipid composition, and membrane morphology, pointing to a complex, multipartite regulatory network underlying intra-mitochondrial lipid transfer.

biochemistry↗

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

Lipid Oxidation Controls Peptide Self-Assembly near Membranes

The self-assembly of peptides into supramolecular fibril structures has been linked to neurodegenerative diseases such as Alzheimers disease but has also been observed in functional roles. Peptides are physiologically exposed to crowded environments of biomacromolecules, and particularly membrane lipids, within a cellular milieu. Previous research has shown that membranes can both accelerate and inhibit peptide self-assembly. Here, we studied the impact of biomimetic membranes that mimic cellular oxidative stress and compared this to mammalian and bacterial membranes. Using molecular dynamics simulations and experiments, we propose a model that explains how changes in peptide-membrane binding, electrostatics, and peptide secondary structure stabilization determine the nature of peptide self-assembly. We explored the influence of zwitterionic (POPC), anionic (POPG) and oxidized (PazePC) phospholipids, as well as cholesterol, and mixtures thereof, on the self-assembly kinetics of the amyloid {beta} (1-40) peptide (A{beta}40), linked to Alzheimers disease, and the amyloid-forming antimicrobial peptide uperin 3.5 (U3.5). We show that the presence of an oxidized lipid had similar effects on peptide self-assembly as the bacterial mimetic membrane. While A{beta}40 fibril formation was accelerated, U3.5 aggregation was inhibited by the same lipids at the same peptide-to-lipid ratio. We attribute these findings and peptide-specific effects to differences in peptide-membrane adsorption with U3.5 being more strongly bound to the membrane surface and stabilized in an -helical conformation compared to A{beta}40. Different peptide-to-lipid ratios resulted in different effects. Molecular dynamics simulations provided detailed mechanistic insights into the peptide-lipid interactions and secondary structure stability. We found that electrostatic interactions are a primary driving force for peptide-membrane interaction, enabling us to propose a model for predictions how cellular changes might impact peptide self-assembly in vivo, and potentially impact related diseases.

biophysics↗

bioRxiv2022

Membrane interactions of mitochondrial lipid transfer proteins

The mitochondrial inner membrane is an integral part of the cellular lipid biosynthesis network. Intramitochondrial lipid transfer shuttles specific lipid species between the two mitochondrial membranes. This pathway is facilitated by designated protein complexes in the intermembrane space. A hetero-dimeric complex of Ups1 and Mdm35 has been identified in yeast to transfer phosphatidic acid from the outer to the inner membrane. Here, we define pH and lipid charge dependency of Ups1 membrane interaction. We show that Ups1 interacts with membranes in a membrane curvature dependent manner. Ups1 predominantly binds to membrane domains of positive curvature. Desorption of phosphatidic acid from positively curved membranes is energetically favorable over flat or negatively curved membranes. Hence, our results demonstrate that Ups1 specifically binds to membrane regions where extraction and insertion of lipids is enhanced.

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↗

bioRxiv2021

Size Matters: A Mechanistic Model of Nanoparticle Curvature Effects on Amyloid Fibril Formation

The aggregation of peptides into amyloid fibrils is linked to ageing-related diseases, such as Alzheimers disease and type 2 diabetes. Interfaces, particularly those with large nanostructured surface areas, can affect the kinetics of peptide aggregation, ranging from a complete inhibition to strong acceleration. While a number of physiochemical parameters determine interface effects, we here focus on the role of nanoparticle curvature for the aggregation of the amyloidogenic peptides A{beta}40, NNFGAIL, GNNQQNY and VQIYVK. Nanoparticles (NPs) provided a surface for peptide monomers to adsorb, enabling the nucleation into oligomers and fibril formation. High surface curvature, however, destabilized prefibrillar structures, providing an explanation for inhibitory effects on fibril growth. Thioflavin T (ThT) fluorescence assays as well as dynamic light scattering (DLS), atomic force microscopy (AFM) and electron microscopy experiments revealed NP size-dependent effects on amyloid fibril formation, with differences between the peptides. While 5 nm gold NPs (AuNP-5) retarded or inhibited the aggregation of most peptides, larger 20 nm gold NPs (AuNP-20) tended to accelerate peptide aggregation. Molecular dynamics (MD) studies demonstrated that NPs ability to catalyze or inhibit oligomer formation was influenced by the oligomer stability at curved interfaces which was lower at more highly curved surfaces. Differences in the NP effects for the peptides resulted from the peptide properties (size, aggregation propensity) and concomitant surface binding affinities. The results can be applied to the design of future nanostructured materials for defined applications.

biochemistry↗

bioRxiv2021

TatA and TatB generate a hydrophobic mismatch that is important for function and assembly of the Tat translocon in Escherichia coli

The Tat system has the unique purpose to translocate folded proteins across energy-transducing membranes. It occurs in bacteria and archaea, as well as in eukaryotic organelles of bacterial origin. In the bacterial model system Escherichia coli, the three components TatA, TatB, and TatC assemble to functional translocons. TatA and TatB both possess an N-terminal transmembrane helix (TMH) that is followed by an amphipathic helix (APH). The TMHs of TatA and TatB generate a hydrophobic mismatch with only 12 consecutive hydrophobic residues that span the membrane. We shortened or extended this stretch of hydrophobic residues in either TatA, TatB, or both, and analyzed effects on transport functionality and translocon assembly. The wild type length functioned best but was not an absolute requirement, as some variation was clearly tolerated. Defects of shortenings or extensions were enhanced by simultaneous mutations in TatA and TatB, indicating partial compensations of mutations in TatA by wild type TatB or vice versa. Length variation in TatB destabilized TatBC-containing complexes, revealing that the 12-residues-length is important for Tat component interactions and translocon assembly. To also address potential effects on TatA associations, we characterized these by metal tagging transmission electron microscopy and carried out molecular dynamics simulations. In these simulations, interacting short TMHs of larger TatA assemblies were thinning the membrane together with laterally aligned tilted APHs that generated a deep V-shaped groove. The conserved length of 12 hydrophobic residues may thus not only be important for translocon interactions, but also for a membrane destabilization during Tat transport. If this is the case, the specific short length could be a compromise between functionality and proton leakage minimization.

biochemistry↗