Biology subjects

Strodel, B.

Publications and source records attributed to Strodel, B..

18 recordsLinked to original sources

bioRxiv2026

Lipopolysaccharide chain length and coat assembly keep guanylate-binding proteins upright on bacterial membranes

Guanylate-binding proteins (GBPs) defend host cells by assembling on intracellular pathogen membranes. For human GBP1, this requires a switch from a compact, closed conformation to an extended, open one, whereas for murine orthologues the open state is not known. How the open state behaves at a membrane has remained inaccessible to experiment. Using all-atom and coarse-grained molecular dynamics simulations covering over 0.5 ms, we followed human GBP1 and murine GBP2 as monomers, dimers, and higher-order assemblies on phosphatidylcholine membranes, Shigella flexneri lipopolysaccharide (LPS), and phosphoinositide-containing bilayers. Closed GBPs dock through their prenyl anchor with minimal lipid selectivity. Open GBPs, by contrast, are intrinsically unstable: monomers fold back into membrane-bound resting states, and dimers tip over unless supported, either by long LPS O-antigen chains or by neighboring molecules within a coat. The open state thus appears to be maintained not by the nucleotide alone but by the protein's molecular environment.

biophysics↗

bioRxiv2026

Structural Basis for the Rational Design of UAMC-1110-Based FAP Radiopharmaceuticals

Radioligands targeting fibroblast activation protein alpha (FAP) are promising tools for cancer diagnosis and therapy. However, the molecular binding mode of clinically established UAMC-1110-derived ligands such as FAPI-46 remains insufficiently characterized. To simplify synthesis while preserving key binding properties, we designed two novel derivatives - FAP-DD-101 (short aminoalkyl linker) and FAP-DD-102 (extended aminohexanoic acid spacer) - and evaluated them alongside FAPI-46 using molecular docking and all-atom molecular dynamics (MD) simulations. Across all derivatives, we identified a highly stable, energetically favorable charge-anchored binding mode, in which the 2-cyano-4,4-difluoropyrrolidine head anchors in a negatively charged subregion formed by Glu202, Glu203, and Glu204, mimicking the binding architecture observed in the FAP-linagliptin complex. MD trajectories confirmed that FAPI-46 and FAP-DD-101 maintain exceptional stability in this pose, with several non-anchored FAPI-46 trajectories spontaneously evolving toward engagement with this electrostatic subregion. For FAP-DD-102, linker elongation slightly reduced pose robustness, yet initial charge-anchored states still yielded superior average binding energies and vector stability compared to non-anchored poses. Overall, these findings elucidate the key structural determinants of FAP recognition, establishing a rational framework for designing synthetically accessible FAPI radiotracers with retained binding stability.

biophysics↗

bioRxiv2026

Exopolysaccharide export complex PelBC of Pseudomonas aeruginosa attenuates the dynamics of the surrounding outer membrane

The opportunistic pathogen Pseudomonas aeruginosa ensures its survival by forming mechanically and chemically resistant biofilms, with cationic exopolysaccharide Pel as an abundant constituent of the structural matrix. Despite its biomedical relevance, the mechanisms of Pel synthesis and secretion via the trans-envelope protein machinery are not understood. Here, we examine the structure of the outer membrane export complex PelBC embedded in synthetic nanodiscs and polymer-extracted particles. Both environments preserve the unique architecture of the complex, where the beta-barrel PelB is capped with the dodecameric ring of PelC lipoproteins. Cryogenic electron microscopy shows that the polymer-extracted PelB beta-barrel is tightly associated with phospholipids and lipid A molecules, and the membrane-facing PelC ring may stabilize lipids of the periplasmic leaflet in defined positions. All-atom molecular dynamics simulation of PelBC in the asymmetric outer membrane of P. aeruginosa corroborate the structural findings and visualize how the essential C-terminal helix of PelC forms multiple electrostatic contacts with the periplasmic leaflet of the outer membrane. Those interactions reduce the lateral mobility of the lipids, stabilize the position of the ring at the interface and may guide folding and assembly of the polysaccharide export machinery.

microbiology↗

bioRxiv2026

Glycosaminoglycans Promote Amyloid-β Aggregation via Multivalent, pH-Dependent Interactions

Glycosaminoglycans (GAGs) are polyanionic polysaccharides that co-localize with amyloid-{beta} (A{beta}) deposits in Alzheimers disease, yet their mechanistic contribution to A{beta} aggregation remains unclear. Here, we show that GAGs function as pH-responsive electrostatic scaffolds that selectively accelerate A{beta}(1-42) aggregation under mildly acidic, endosomal conditions but not at neutral extracellular pH. Combining experimental and computational approaches, we identify protonated N-terminal histidines as key determinants of GAG binding. Weak interactions between GAGs and the charged Nterminal region of A{beta} promote conformational rearrangements that bring peptides into proximity and expose adjacent hydrophobic aggregation-prone segments, thereby facilitating peptide clustering. Kinetic analyses reveal that aggregation is enhanced in a way consistent with an apparent increase in effective peptide concentration, accelerating nucleation without altering the dominant aggregation pathway. Systematic variation of GAG chain length and sulfation level further demonstrates that aggregation enhancement requires a threshold degree of multivalency, consistent with a clustering-driven mechanism. Together, these findings establish a framework in which pH-dependent electrostatic interactions with GAGs act as molecular triggers of amyloid nucleation, providing insight into how cellular microenvironments regulate the earliest stages of Alzheimers disease pathology.

biophysics↗

bioRxiv2024

Influence of Wobbling Tryptophan and Mutations on PET Degradation Explored by QM/MM Free Energy Calculations

Plastic-degrading enzymes, particularly poly(ethylene terephthalate) (PET) hydrolases, have garnered significant attention in recent years as potential eco-friendly solutions for recycling plastic waste. However, understanding of their PET-degrading activity and influencing factors remains incomplete, impeding the development of uniform approaches for enhancing PET hydrolases for industrial applications. A key aspect of PET hydrolase engineering is optimizing the PET-hydrolysis reaction by lowering the associated free energy barrier. However, inconsistent findings have complicated these efforts. Therefore, our goal is to elucidate various aspects of enzymatic PET degradation by means of quantum mechanics / molecular mechanics (QM/MM) reaction simulations and analysis, focusing on the initial reaction step, acylation, in two thermophilic PET hydrolases: LCC and PES-H1, along with their highly active variants, LCCICCG and PES-H1FY. Our findings highlight the impact of semi-empirical QM methods on proton transfer energies, affecting the distinction between a two-step reaction involving a metastable tetrahedral intermediate and a one-step reaction. Moreover, we uncovered a concerted conformational change involving the orientation of the PET benzene ring, altering its interaction with the side-chain of the wobbling tryptophan from T-stacking to parallel {pi}-{pi} interactions, a phenomenon overlooked in prior research. Our study thus enhances the understanding of the acylation mechanism of PET hydrolases, in particular by characterizing it for the first time for the promising PES-H1FY using QM/MM simulations. It also provides insights into selecting a suitable QM method and a reaction coordinate, valuable for future studies on PET degradation processes. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/591886v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@c0aa9aorg.highwire.dtl.DTLVardef@1008acdorg.highwire.dtl.DTLVardef@98b0d6org.highwire.dtl.DTLVardef@81d8e3_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

From Bulk to Binding: Decoding the Entry of PET into Hydrolase Binding Pockets

Plastic-degrading enzymes hold promise for biocatalytic recycling of poly(ethylene terephthalate) (PET), a key synthetic polymer. Despite their potential, the current activity of PET hydrolases is not sufficient for industrial use. To unlock their full potential, a deep mechanistic understanding followed by protein engineering is required. Using cuttingedge molecular dynamics simulations and free energy analysis methods, we uncover the entire pathway from the initial binding of two PET hydrolases - the thermophilic leaf-branch compost cutinase (LCC) and polyester hydrolase 1 (PES-H1) - to an amorphous PET material to a PET chain entering the active site and adopting a hydrolyzable geometry. Our results reveal the initial PET binding and elucidate its non-specific nature driven by electrostatic and hydrophobic forces. Upon PET entry into the active site, we uncover that this process can occur via one of three key pathways and detect barriers to it arising from both PET-PET and PET-enzyme interactions, with specific residues identified by in silico and in vitro mutagenesis. These insights not only advance our understanding of PET degradation mechanisms and pave the way for targeted enzyme enhancement strategies, but also offer an innovative approach applicable to enzyme studies across disciplines.

bioengineering↗

bioRxiv2024

TransMEP: Transfer learning on large protein language models to predict mutation effects of proteins from a small known dataset

Machine learning-guided optimization has become a driving force for recent improvements in protein engineering. In addition, new protein language models are learning the grammar of evolutionarily occurring sequences at large scales. This work combines both approaches to make predictions about mutational effects that support protein engineering. To this end, an easy-to-use software tool called TransMEP is developed using transfer learning by feature extraction with Gaussian process regression. A large collection of datasets is used to evaluate its quality, which scales with the size of the training set, and to show its improvements over previous fine-tuning approaches. Wet-lab studies are simulated to evaluate the use of mutation effect prediction models for protein engineering. This showed that TransMEP finds the best performing mutants with a limited study budget by considering the trade-off between exploration and exploitation. Graphical TOC Entry O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/575432v1_ufig1.gif" ALT="Figure 1"> View larger version (12K): org.highwire.dtl.DTLVardef@11ccc78org.highwire.dtl.DTLVardef@1b3e51corg.highwire.dtl.DTLVardef@1869c65org.highwire.dtl.DTLVardef@85d6c0_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Amyloid Morphology is Encoded in H-bonds and Electrostatics Interactions Ruling Protein Phase Separation

Ion-protein interactions regulate biological processes and are the basis of key strategies of modulating protein phase diagrams and stability in drug development. Here, we report the mechanisms by which H-bonds and electrostatic interactions in ion-protein systems determine phase separation and amyloid formation. Using microscopy, small-angle X-ray scattering, circular dichroism and atomistic molecular dynamics (MD) simulations, we found that anions specifically interacting with insulin induced phase separation by neutralising the protein charge and forming H-bond bridges between insulin molecules. The same interaction was responsible for an enhanced insulin conformational stability and resistance to oligomerisation. Under aggregation conditions, the anion-protein interaction translated into the activation of a coalescence process, leading to amyloid-like microparticles. This reaction is alternative to conformationally-driven pathways, giving rise to elongated amyloid-like fibrils and occurs in the absence of preferential ion-protein binding. Our findings depict a unifying scenario in which common interactions dictated both phase separation at low temperatures and the occurrence of pronounced heterogeneity in the amyloid morphology at high temperatures, similar to what has previously been reported for protein crystal growth.

biophysics↗

bioRxiv2023

Allosteric communication induced by GTP binding sets off a closed-to-open transition in a bacterial dynamin-like protein

Dynamin superfamily proteins are mechanochemical GTPases that operate in highly oligomeric and highly cooperative superstructures to deform lipid membranes. It is known from the structures of a bacterial dynamin-like protein (BDLP) that binding of GTP and association of BDLP with lipids causes a transition from closed to open hinge 1 that affects oligomerization. We trace this radical, large-scale conformational change at the atomic level with unbiased, replica exchange, and umbrella sampling molecular dynamics simulations. We decipher how GTP loading from the GTPase domain to the distal stalk end is mediated by an allosteric network of salt bridges that act in response to GTP binding and subsequent conformational changes in GTPase domain motifs. Two previously undiscovered motifs have been identified whose movements free the paddle from the GTPase domain, allowing large-scale domain rearrangements. In addition, a novel wide-open state of BDLP reminiscent of human dynamin 1 is discovered. Our results explain several aspects of the BDLP cycle and have broad implications for other members of the dynamin family.

biophysics↗

bioRxiv2022

Integrative modeling of guanylate binding protein dimers

Guanylate binding proteins (GBPs) are interferon-{gamma}-activated large GTPases, effective against intracellular pathogens like Toxoplasma gondii. Their host-protective functions require oligomerization, however, the oligomer structures have not been completely resolved yet. Here, we provide dimer models for hGBP1 and the murine GBPs 2 and 7 (mGBP2 and mGBP7) based on integrative modeling that involves the crystal structure of the G domain dimer of hGBP1, cross-linking mass spectrometry (XL-MS), small angle X-ray scattering (SAXS), protein-protein docking, and molecular dynamics (MD) simulations of hGBP1, mGBP2 and mGBP7. We first compare the sequences and protein dynamics of the monomeric hGBP1, mGBP2, and mGBP7, finding that the M/E domain of all three proteins is highly mobile featuring a hinge movement, yet this motion is less pronounced in mGBP7 while its GTPase (G) domain is more flexible. These differences can be explained by the variations in the sequences between mGBP7 and hGBP1/mGBP2 and extend to their dimers. While hGBP1 and its close orthologue mGBP2 dimerize via their G domains, mGBP7 shows a variety of possible dimer structures, among them parallel and crossed-stalk conformations. The G domain is only partly involved in mGBP7 dimerization, which provides a rational why mGBP7, unlike hGBP1 and mGBP2, can dimerize in the absence of GTP. The different GBP dimer structures, which still exhibit hinge movements to certain degrees, are expected to encode diverging functions, such as a destabilization of pathogenic membranes or fusion of the parasitophorous vacuole membrane with the autophagic machinery.

biochemistry↗

bioRxiv2022

Domain motions, dimerization, and membrane interactions of the murine guanylate binding protein 2

Guanylate-binding proteins (GBPs) are a group of GTPases that are induced by interferon-{gamma} and are crucial components of cell-autonomous immunity against intracellular pathogens. Here, we examine murine GBP2 (mGBP2), which we have previously shown to be an essential effector protein for the control of Toxoplasma gondii replication, with its recruitment through the membrane of the parasitophorous vacuole and its involvement in the destruction of this membrane likely playing a role. The overall aim of our work is to provide a molecular-level understanding of the mutual influences of mGBP2 and the parasitophorous vacuole membrane. To this end, we performed lipid-binding assays which revealed that mGBP2 has a particular affinity for cardiolipin. This observation was confirmed by fluorescence microscopy using giant unilamellar vesicles of different lipid compositions. To obtain an understanding of the protein dynamics and how this is affected by GTP binding, mGBP2 dimerization, and membrane binding, assuming that each of these steps are relevant for the function of the protein, we carried out standard as well as replica exchange molecular dynamics simulations with an accumulated simulation time of more than 30 s. The main findings from these simulations are that mGBP2 features a large-scale hinge motion in its M/E domain, which is present in each of the studied protein states. When bound to a cardiolipin-containing membrane, this hinge motion is particularly pronounced, leading to an up and down motion of the M/E domain on the membrane, which did not occur on a membrane without cardiolipin. Our prognosis is that this up and down motion has the potential to destroy the membrane following the formation of supramolecular mGBP2 complexes on the membrane surface.

biophysics↗

bioRxiv2021

Structural dissection of the first events following membrane binding of the islet amyloid polypeptide

Amyloid forming proteins are involved in many pathologies and often belong to the class of intrinsically disordered proteins. One of these proteins is the islet amyloid polypeptide (IAPP), which is the main constituent of the amyloid fibrils found in the pancreas of type 2 diabetes patients. The molecular mechanism of IAPP-induced cell death is not yet understood, however it is known that cell membrane plays a dual role, being a catalyst of IAPP aggregation and the target of IAPP toxicity. Using FTIR spectroscopy, transmission electron microscopy, and molecular dynamics simulations we investigate the very first molecular steps following IAPP binding to a lipid membrane. In particular, we assess the combined effects of the charge state of amino-acid residue 18 and the IAPP-membrane interactions on the structures of monomeric and aggregated IAPP. Both our experiments and simulations reveal distinct IAPP-membrane interaction modes for the various IAPP variants. Membrane binding causes IAPP to fold into an amphipathic helix, which in the case of H18K- and H18R-IAPP can easily insert into the membrane. For all IAPP variants but H18E-IAPP, the membrane-bound -helical structure is an intermediate on the way to IAPP amyloid aggregation, while H18E-IAPP remains in a stable helical conformation. The fibrillar aggregates of wild-type IAPP and H18K-IAPP are dominated by an antiparallel {beta}-sheet conformation, while H18R- and H18A-IAPP exhibit both antiparallel and parallel {beta}-sheets as well as amorphous aggregates. In summary, our results emphasize the importance of residue 18 for the structure and membrane interaction of IAPP. This residue is thus a good target for destabilizing amyloid fibrils of IAPP and inhibit its toxic actions by possible therapeutic molecules.

biophysics↗

bioRxiv2021

Amyloid-β peptide dimers undergo a random coil to β-sheet transition in the aqueous phase but not at the neuronal membrane

AO_SCPLOWBSTRACTC_SCPLOWThe aggregation of amyloid {beta}-peptides into neurotoxic oligomers is a key feature in the development of Alzheimers disease. Mounting evidence suggests that the neuronal cell membrane is the main site of oligomer-mediated neuronal toxicity. To gain a detailed understanding of the mutual effects of amyloid-{beta} oligomers and the neuronal membrane, we carried out a total of 12 {micro}s all-atom molecular dynamics (MD) simulations of the dimerization of the full-length A{beta}42 peptide in the presence of a lipid bilayer mimicking the in vivo composition of neuronal membranes. The conformational changes of A{beta}42 resulting from its dimerization and interactions with the neuronal membrane are compared to those occurring upon its dimerization in the aqueous phase, which is also tested by 12 {micro}s of MD simulations. We find that the interactions with the neuronal membrane decrease the order of the A{beta}42 dimer by attenuating its propensity to form a {beta}-sheet structure. The main lipid interaction partners of A{beta}42 are the surface-exposed sugar groups of the gangliosides GM1. A{beta}42 dimerization in solution, on the other hand, is characterized by a random coil to {beta}-sheet transition that seems to be on-pathway to amyloid aggregation. As the neurotoxic activity of amyloid oligomers increases with oligomer order, the results suggest that GM1 is neuroprotective against A{beta}-mediated toxicity by inhibiting the formation of ordered amyloid oligomers.

biophysics↗

bioRxiv2020

Different force fields give rise to different amyloid aggregation pathways in molecular dynamics simulations

The progress towards understanding the molecular basis of Alzheimerss disease is strongly connected to elucidating the early aggregation events of the amyloid-{beta} (A{beta}) peptide. Molecular dynamics (MD) simulations provide a viable technique to study the aggregation of A{beta} into oligomers with high spatial and temporal resolution. However, the results of an MD simulation can only be as good as the underlying force field. A recent study by our group showed that none of the force fields tested can distinguish between aggregation-prone and non-aggregating peptide sequences, producing the same and in most cases too fast aggregation kinetics for all peptides. Since then, new force fields specially designed for intrinsically disordered proteins such as A{beta} were developed. Here, we assess the applicability of these new force fields to studying peptide aggregation using the A{beta}16-22 peptide and mutations of it as test case. We investigate their performance in modeling the monomeric state, the aggregation into oligomers, and the stability of the aggregation end product, i.e., the fibrillar state. A main finding is that changing the force field has a stronger effect on the simulated aggregation pathway than changing the peptide sequence. Also the new force fields are not able to reproduce the experimental aggregation propensity order of the peptides. Dissecting the various energy contributions shows that AMBER99SB-disp overestimates the interactions between the peptides and water, thereby inhibiting peptide aggregation. More promising results are obtained with CHARMM36m and especially its version with increased protein-water interactions. It is thus recommended to use this force field for peptide aggregation simulations and base future reparameterizations on it.

biophysics↗

bioRxiv2020

Thermodynamics and kinetics of the amyloid-β peptide revealed by Markov state models based on MD data in agreement with experiment

The amlyoid-{beta} peptide (A{beta}) is closely linked to the development of Alzheimers disease. Molecular dynamics (MD) simulations have become an indispensable tool for studying the behavior of this peptide at the (sub)molecular level, thereby providing insight into the molecular basis of Alzheimers disease. General key aspects of MD simulations are the force field used for modeling the peptide or protein and its environment, which is important for accurate modeling of the system of interest, and the length of the simulations, which determines whether or not equilibrium is reached. In this study we address these points by analyzing 30-{micro}s MD simulations acquired for A{beta}40 using seven different force fields. We assess the convergence of these simulations based on the convergence of various structural properties and of NMR and fluorescence spectroscopic observables. Moreover, we calculate Markov state models for each of the seven MD simulations, which provide an unprecedented view of the thermodynamics and kinetics of the amyloid-{beta} peptide. This further allows us to provide answers for pertinent questions, like: Which force fields are suitable for modeling A{beta}? (a99SB-UCB and a99SB-ILDN/TIP4P-D); What does A{beta} peptide really look like? (mostly extended and disordered) and; How long does it take MD simulations of A{beta} to attain equilibrium? (20-30 {micro}s). We believe the analyses presented in this study will provide a useful reference guide for important questions relating to the structure and dynamics of A{beta}in particular, and by extension other similar disordered peptides.

biophysics↗

bioRxiv2020

Molecular dynamics simulations of protein aggregation: protocols for simulation setup and analysis with Markov state models and transition networks

Protein disorder and aggregation play significant roles in the pathogenesis of numerous neuro-degenerative diseases, such as Alzheimers and Parkinsons disease. The end products of the aggregation process in these diseases are {beta}-sheet rich amyloid fibrils. Though in most cases small, soluble oligomers formed during amyloid aggregation are the toxic species. A full understanding of the physicochemical forces behind the protein aggregation process is required if one aims to reveal the molecular basis of the various amyloid diseases. Among a multitude of biophysical and biochemical techniques that are employed for studying protein aggregation, molecular dynamics (MD) simulations at the atomic level provide the highest temporal and spatial resolution of this process, capturing key steps during the formation of amyloid oligomers. Here we provide a step-by-step guide for setting up, running, and analyzing MD simulations of aggregating peptides using GROMACS. For the analysis we provide the scripts that were developed in our lab, which allow to determine the oligomer size and inter-peptide contacts that drive the aggregation process. Moreover, we explain and provide the tools to derive Markov state models and transition networks from MD data of peptide aggregation.

biophysics↗

bioRxiv2019

Large-scale, dynamin-like motions of the human guanylate binding protein 1 revealed by multi-resolution simulations

Guanylate binding proteins (GBPs) belong to the dynamin-related superfamily and exhibit various functions in the fight against infections. The functions of the human guanylate binding protein 1 (hGBP1) are tightly coupled to GTP hydrolysis and dimerization. Despite known crystal structures of the hGBP1 monomer and GTPase domain dimer, little is known about the dynamics of hGBP1. To gain a mechanistic understanding of hGBP1, we performed sub-millisecond multi-resolution molecular dynamics simulations of both the hGBP1 monomer and dimer. We found that hGBP1 is a highly flexible protein that undergoes a hinge motion similar to the movements observed for other dynamin-like proteins. Another large-scale motion was observed for the C-terminal helix 13, providing a molecular view for the 13-13 distances previously reported for the hGBP1 dimer. Most of the loops of the GTPase domain were found to be flexible, disclosing why GTP binding is needed for hGBP1 dimerization to occur.\n\nAuthor summaryGunaylate binding proteins are key fighters against microbial and viral pathogens. In the human body there are seven types of such proteins, among which is the guanylate binding protein 1 (hGBP1). This protein is able to perform its function only once it is activated by binding and converting guanosinetriphosphat (GTP) to guanosinediphosphat and guanosinemonophosphat via hydrolysis. In concert with the conversion of GTP the dimerization of hGBP1 occurs, which can further interact with the lipid membrane of the pathogen and disrupt it. While the crystal structure of the protein is known, the activation and dimerization steps are not well understood at molecular level as studying them experimentally is difficult. An alternative approach is given by molecular simulations, allowing us to elucidate the protein dynamics closely connected to these steps. From our simulations applied to both the hGBP1 monomer and dimer we identified large-scale motions taking place in hGBP1 that had not been reported before. We discuss the relevance of these motions in terms of their biological function, such as possible membrane damage caused by one of the motions or locking the protein in the dimer state.

biophysics↗

bioRxiv2017

A structural and kinetic link between membrane association and amyloid fibril formation of α-Synuclein

The protein -Synuclein (S) is linked to Parkinsons disease through its abnormal aggregation, which is thought to involve an interplay between cytosolic and membrane-bound forms of S. Therefore, better insights into the molecular determinants of membrane association and their implications for protein aggregation may help deciphering the pathogenesis of Parkinsons disease. Following previous studies using micelles and vesicles, we present a comprehensive study of S interaction with phospholipid bilayer nanodiscs. Using a combination of NMR - spectroscopic and complementary biophysical as well as computational methods we structurally and kinetically characterize S interaction with defined stable planar membranes in a quantitative and site-resolved way. We probe the role of S acetylation as well as membrane charge, plasticity and available surface area in modulating S membrane binding modes and directly link these findings to their consequences for S amyloid fibril formation.

biophysics↗