Andreas Haahr Larsen

Helix 8 in G protein-coupled receptors (GPCRs) has recently been linked to receptor internalization (Schmidt et al., 2025, Sci. Adv. 11, eadv1499), but the molecular basis of this relationship remains unclear. Here, we examined a proposed mechanism in which helix 8 functions as a surface-active amphipathic element that promotes membrane binding, senses membrane curvature, and thereby facilitates GPCR trafficking. We analyzed six amphipathic peptides, including helix 8 segments from five GPCRs spanning a broad range of internalization rates, using molecular dynamics simulations and circular dichroism spectroscopy. Secondary structure in a membrane environment showed the strongest relationship with internalization, indicating that helix-forming propensity is a key determinant of trafficking behavior. Membrane binding showed a weaker association with internalization that became more apparent when secondary structure was considered. In contrast, curvature sensing, as modeled here, did not correlate positively with internalization, although all constructs favored positive curvature and curvature-related hydrophobic phase width matched the internalization trend. Together, the results suggest that, while membrane binding and curvature-related properties likely contribute to the process, the ability of helix 8 to form amphipathic helices is the principal factor underlying differential GPCR internalization. These findings support a broader model in which surface-active amphipathic motifs tune membrane protein trafficking by coupling dynamic structural propensities to membrane interactions.

Amphiphilic copolymers have emerged as powerful, detergent‑free tools for solubilizing biological membranes, enabling the extraction and stabilization of membrane proteins within native‑like lipid environments. We report a comprehensive, multi‑technique elucidation of how polymer:lipid stoichiometry governs the formation, size, and stability of styrene-maleic acid lipid particles (SMALPs). Using commercial SMA2000, a styrene-maleic acid copolymer made using free radical polymerisation and 1,2-ditetradecanoyl-sn-glycero-3-phosphocholine (DMPC) as a model phospholipid, we prepared SMALPs across a wide range of polymer‑to‑lipid weight ratios and employed an integrated suite of orthogonal characterization methods, including size exclusion chromatography (SEC), dynamic light scattering (DLS), flow-induced dispersion analysis (FIDA), mass photometry, ensemble and time‑resolved Förster resonance energy transfer (FRET), and small-angle X-ray scattering (SAXS), to establish the structural consequences of varying polymer content. Our data reveal that efficient lipid solubilization into nanodiscs requires a minimum amount of polymer. Above ~1% (w/v) SMA2000: 1% DMPC, well-defined nanodiscs of ~10 nm diameter are formed that, on average, exhibit a consistent stoichiometry of ~130 lipids encircled by ~11 polymer chains. Through a new molecularly‑constrained SAXS model, we show that these nanodiscs possess a stable bilayer height across variations in polymer to lipid ratio and a narrow polymer belt, and that their structural parameters remain invariant once excess polymer is used. In contrast, insufficient polymer (<1% w/v) generates bimodal populations including substantially larger discs. Notably, nanodiscs formed at optimal polymer:lipid ratios remain structurally stable for at least two months. Together, these results provide a rigorous quantification of SMALP composition and preferred size, enhancing our understanding of polymer-lipid nanodisc formation and offering critical design rules for detergent‑free membrane protein extraction.

Transmembrane proteins mediate essential cellular processes including signaling, transport, and ion flux. Besides their well-characterized structured domains, most contain intrinsically disordered regions, whose biological roles remain poorly understood. Evidence suggests that the functions of intrinsically disordered regions are context-dependent, a trait particularly relevant when anchored to cellular membranes. In this study, we probed peptide arrays with fluorescent liposomes to generate a high-resolution, proteome-wide map of membrane-interaction sites within intrinsically disordered regions of human transmembrane proteins. Screening 4,000 proteins, we identified membrane-interaction sites in ~60% of cases. Among these, ~63% represent amphipathic helices, while ~17% resemble cationic cell-penetrating peptides. We demonstrate that membrane-interaction motifs can influence subcellular localization and may contribute to both physiological and pathological processes. Our findings establish membrane association as a key functional aspect of intrinsically disordered regions and provide a valuable resource for discovering non-canonical regulatory mechanisms in transmembrane proteins. The resource is available at MemRIDRdb.

Neuropeptide-containing dense core vesicles (DCVs) generated in neuronal somata are circulated in axons to supply distal release sites, depending on kinesin-1, kinesin-3, and dynein, but how the motors are recruited remains unclear. Here we use proximity proteomics in the living Drosophila nervous system to identify the protein complex responsible for recruitment of kinesin-1 and dynein on DCVs. We find that the dynein and kinesin-1 adaptor Sunday driver (Syd/dJIP3/4) interact with the DCV-located GTPase Rab2 and also bind the Arl8 effector RUFY. Disrupting Rab2, Syd, RUFY, the Arl8 activator BORC, or dynein impedes retrograde DCV flux and induces axonal accumulation of immobile DCVs. Our data suggest that dynein is recruited and activated by a Syd/RUFY complex anchored to DCVs by Rab2 and Arl8. Rab2 loss but not disruption of Syd, RUFY, or dynein causes missorting of DCV membrane proteins into vesicle aggregates in motor neuron somata, suggesting that Rab2 employs separate effectors in DCV biogenesis and motility.

Cellular signaling relies on the activity of transmembrane receptors and their presentation on the cellular surface. Their continuous insertion in the plasma membrane is balanced by constitutive and activity-dependent internalization, which is orchestrated by adaptor proteins recognizing semispecific motifs within the receptors’ intracellular regions. Here, we describe a complementary trafficking mechanism for G protein–coupled receptors (GPCRs) that is evolutionary conserved and refined. This mechanism relies on the insertion of their amphipathic helix 8 into the inner leaflet of lipid membranes, orthogonal to the transmembrane helices. These amphipathic helices dictate subcellular localization of the receptors and autonomously drive their endocytosis by cooperative assembly and association with areas of high membrane curvature. The strength of helix 8 membrane insertion propensity quantitatively predicts the rate of constitutive internalization of GPCRs. This discovery advances our understanding of membrane protein trafficking and highlights a principle of receptor-lipid interactions that may have broad implications for cellular signaling and therapeutic targeting.

Small-angle X-ray and neutron scattering (SAXS and SANS) are powerful techniques in materials science and soft matter. This study addressed how multiple SAXS or SANS datasets are best weighted when performing simultaneous fitting. Three weighting schemes were tested: (1) equal weighting of all datapoints, (2) equal weighting of each dataset through normalization with the number of datapoints and (3) weighting proportional to the information content. The weighting schemes were assessed by model refinement against synthetic data under numerous conditions. The first weighting scheme led to the most accurate parameter estimation, especially when one dataset substantially outnumbered the other(s). Furthermore, it was demonstrated that inclusion of Gaussian priors significantly improves the accuracy of the refined parameters, as compared with common practice, where each parameter is constrained uniformly within an allowed interval.

Small-angle X-ray and neutron scattering (SAXS and SANS) are versatile techniques for studying the structure of various materials and particles, enabling investigations of structures from a few to hundreds of nanometres. However, interpreting SAXS or SANS data can be challenging, hence the need for effective training. Here, we present the website SAStutorials.org, which offers tutorials on small-angle scattering (SAS) data analysis. The website serves as a learning platform that supports active learning both in the classroom and through self-study. The tutorials cover basic concepts, advanced modelling and theoretical aspects of SAS. Each tutorial follows a structure based on the principle of SOLO taxonomy, guiding learners from minimal or no knowledge in a given area to the ability to tackle real-world problems. SAStutorials.org has been developed as a community tool, providing tutorials that encompass a broad range of data analysis types, leveraging various programs and investigating different materials. Moreover, the website and all its data are open source, encouraging contributions from the community.

Stimulated by informal conversations at the XVII International Small Angle Scattering (SAS) conference (Traverse City, 2017), an international team of experts undertook a round-robin exercise to produce a large dataset from proteins under standard solution conditions. These data were used to generate consensus SAS profiles for xylose isomerase, urate oxidase, xylanase, lysozyme and ribonuclease A. Here, we apply a new protocol using maximum likelihood with a larger number of the contributed datasets to generate improved consensus profiles. We investigate the fits of these profiles to predicted profiles from atomic coordinates that incorporate different models to account for the contribution to the scattering of water molecules of hydration surrounding proteins in solution. Programs using an implicit, shell-type hydration layer generally optimize fits to experimental data with the aid of two parameters that adjust the volume of the bulk solvent excluded by the protein and the contrast of the hydration layer. For these models, we found the error-weighted residual differences between the model and the experiment generally reflected the subsidiary maxima and minima in the consensus profiles that are determined by the size of the protein plus the hydration layer. By comparison, all-atom solute and solvent molecular dynamics (MD) simulations are without the benefit of adjustable parameters and, nonetheless, they yielded at least equally good fits with residual differences that are less reflective of the structure in the consensus profile. Further, where MD simulations accounted for the precise solvent composition of the experiment, specifically the inclusion of ions, the modelled radius of gyration values were significantly closer to the experiment. The power of adjustable parameters to mask real differences between a model and the structure present in solution is demonstrated by the results for the conformationally dynamic ribonuclease A and calculations with pseudo-experimental data. This study shows that, while methods invoking an implicit hydration layer have the unequivocal advantage of speed, care is needed to understand the influence of the adjustable parameters. All-atom solute and solvent MD simulations are slower but are less susceptible to false positives, and can account for thermal fluctuations in atomic positions, and more accurately represent the water molecules of hydration that contribute to the scattering profile.