Biology subjects

Thomasen, F. E.

Publications and source records attributed to Thomasen, F. E..

8 recordsLinked to original sources

bioRxiv2026

Full-Length Molecular Models of Brain-Derived α-Synuclein Fibrils Reveal a Fuzzy-Coat-Mediated Mechanism for Selective Peptide Binding

Parkinsons disease (PD) is characterized by the aggregation of -synuclein (aSyn) into amyloid fibrils that seed further aggregation and contribute to pathological spreading. Peptides that bind aggregated aSyn are promising therapeutic leads, but their validation is slow, difficult to standardize, and often relies on structural models limited to the ordered cross-{beta} core. Here, we built models of brain-derived full-length aSyn fibrils by extending the Lewy-fold cryo-EM structure with disordered N- and C-terminal segments and sampling the resulting ensembles with the CALVADOS coarse-grained force field. The resulting fibrils display a dynamic fuzzy coat in which the termini, especially the acidic C-terminal tails, form recurrent transient contacts with the core, including the aggregation-prone {beta}5 and {beta}9 motifs. We then used these full-length fibrils in a standardized in silico assay for peptide binding. Simulations of the validated peptide binders PSM3 and LL-37 reproduced their relative binding behavior and converged on a common mechanism in which electrostatic capture by the anionic fuzzy coat precedes stabilization on recurrent P2 and P3 hotspots within the structured core. Control simulations with monomeric aSyn or core-only fibrils showed that persistent association is lost in the absence of the full-length architecture, providing a mechanism for selectivity toward aggregated species. Finally, screening 123 peptides from aSynPEP-DB using a relative contact-based binding score yielded a ranked set of candidate binders and identified net positive charge as the dominant determinant of sustained association, with hydrophobicity acting as a secondary modulator. Together, these results establish full-length, brain-derived fibril ensembles as a practical framework for understanding ligand recognition at pathological amyloid surfaces and for prioritizing therapeutic peptide binders targeting aggregated aSyn. SignificanceParkinsons disease is driven by the assembly of -synuclein into amyloid fibrils, yet most structural models of these aggregates omit the disordered termini that form the fibrillar "fuzzy coat" in vivo. Here we use coarse-grained simulations to reconstruct full-length, brain-derived -synuclein fibrils and show that this fuzzy coat transiently contacts the Lewy-fold core, reshaping access to cross-{beta} surface motifs. Using these ensembles in a computational assay, we recapitulate the relative binding behavior of validated peptide inhibitors and reveal a two-step mechanism in which cationic and amphipathic peptides are first captured by the anionic fuzzy coat and then engage recurrent core hotspots. This framework explains selective recognition of aggregated -synuclein and provides a practical route to prioritize therapeutic peptide binders.

bioinformatics↗

bioRxiv2025

Computational characterization of the xanthan gum glycosyltransferase GumK

The activity of GT-B glycosyltransferases depends on their conformational flexibility and high substrate specificity, but the molecular basis of these features is still not well defined. The GT70 family contains a single well-characterized enzyme, GumK, a glucuronosyltransferase from Xanthomonas campestris required for xanthan gum biosynthesis. Here, we applied multiscale molecular simulations and sequence analysis to probe GumK dynamics and substrate specificity. We show that GumK undergoes twisting and bending motions constrained by interdomain contacts and modulated by membrane anchoring. Acceptor-substrate binding within an amphiphilic clamp promotes opening, whereas donor-substrate binding stabilizes closure, defining a substrate-dependent catalytic cycle. Specificity for UDP-glucuronate is mediated by a conserved electrostatic environment centered on Lys307 and a hydrophobic triad that orients the sugar moiety. On the acceptor side, the binding site selectively accommodates polyisoprenyl carriers up to three isoprene units in length and wraps around the substrate, constraining the trisaccharide moiety in a catalytically competent conformation. Comparative analysis highlights GumK-specific motifs that distinguish it from homologous GTs. This work provides mechanistic insight into the GT70 family and the dynamic behavior of GT-B enzymes, establishing principles for the rational engineering of GumK to modify the monosaccharide composition of xanthan gum. Author summaryGlycosyltransferases are enzymes that build many of the sugars and polysaccharides essential for life. One of them, called GumK, is responsible for a key step in producing xanthan gum -- a natural polymer widely used as a thickener in food and industrial materials. Despite its importance, how GumK works at the molecular level has remained unclear. In our study, we used multiscale computer simulation strategies to explore the dynamics of this enzyme and how it interacts with the cell membrane and its sugar substrates. We found that GumK acts like a flexible clamp that opens and closes as it binds two different sugar molecules through specific residues that may control the enzymes selectivity. We also discovered how the surrounding membrane helps the enzyme remain in the correct orientation to perform its function. By identifying the molecular details that determine GumKs selectivity and flexibility, our work provides a foundation for modifying this enzyme to produce xanthan gum with new properties. More broadly, our findings help explain how a large family of related enzymes controls sugar transfer in living organisms, with potential applications in biotechnology and materials science.

biophysics↗

bioRxiv2025

AF2χ: Predicting protein side-chain rotamer distributions with AlphaFold2

The flexibility of protein side chains is an essential contributor of conformational entropy and affects processes such as folding, stability and molecular interactions. Structure determination experiments and prediction tools such as AlphaFold generally fail to capture or represent the conformational heterogeneity of proteins in solution. Experiments can be used to study side-chain flexibility, but cannot be applied at scale, and most prediction methods focus on reconstructing the minimum free energy state rather than an ensemble representing side-chain configurations. Here, we use AlphaFold2 and its internal side-chain representations to develop AF2{chi} that predicts side-chain {chi}-angle distributions and generates structural ensembles. We extensively benchmark AF2{chi} predictions using experimental NMR 3J-couplings and s2 order parameters, as well as dihedral angle distributions derived from collections of experimental structures, demonstrating the accuracy of AF2{chi} in generating accurate side-chain ensembles. We also compare the accuracy of AF2{chi} with molecular dynamics simulations and recent machine learning models aimed to generate conformational ensembles and show that AF2{chi} provides state-of-the-art accuracy orders of magnitude faster than molecular simulations. With its speed and accuracy, AF2{chi} offers a strong complementary option to simulations and rotamer library approaches, making it particularly valuable for applications such as protein design, ligand docking and interpretation of biophysical experiments.

biophysics↗

bioRxiv2023

Accurate model and ensemble refinement using cryo-electron microscopy maps and Bayesian inference

Converting cryo-electron microscopy (cryo-EM) data into high-quality structural models is a challenging problem of outstanding importance. Current refinement methods often generate unbalanced models in which physico-chemical quality is sacrificed for excellent fit to the data. Furthermore, these techniques struggle to represent the conformational heterogeneity averaged out in low-resolution regions of density maps. Here we introduce EMMIVox, a Bayesian inference approach to determine single-structure models as well as structural ensembles from cryo-EM maps. EMMIVox automatically balances experimental information with accurate physico-chemical models of the system and the surrounding environment, including waters, lipids, and ions. Explicit treatment of data correlation and noise as well as inference of accurate B-factors enable determination of structural models and ensembles with both excellent fit to the data and high stereochemical quality, thus outperforming state-of-the-art refinement techniques. EMMIVox represents a flexible approach to determine high-quality structural models that will contribute to advancing our understanding of the molecular mechanisms underlying biological functions.

bioinformatics↗

bioRxiv2023

Recalibration of protein interactions in Martini 3

Multidomain proteins with flexible linkers and disordered regions play important roles in many cellular processes, but characterizing their conformational ensembles is diffcult. We have previously shown that the coarse-grained model, Martini 3, produces too compact ensembles in solution, that may in part be remedied by strengthening protein-water interactions. Here, we show that decreasing the strength of protein-protein interactions leads to improved agreement with experimental data on a wide set of systems. We show that the symmetry between rescaling protein-water and protein-protein interactions breaks down when studying interactions with or within membranes; rescaling protein-protein interactions better preserves the binding specificity of proteins with lipid membranes, whereas rescaling protein-water interactions preserves oligomerization of transmembrane helices. We conclude that decreasing the strength of protein-protein interactions improves the accuracy of Martini 3 for IDPs and multidomain proteins, both in solution and in the presence of a lipid membrane.

biophysics↗

bioRxiv2022

Conformational and oligomeric states of SPOP from small-angle X-ray scattering and molecular dynamics simulations

Speckle-type POZ protein (SPOP) is a substrate adaptor in the ubiquitin proteasome system, and plays important roles in cell-cycle control, development, and cancer. SPOP forms linear higher-order oligomers following an isodesmic self-association model. Oligomerization is essential for SPOPs multivalent interactions with substrates, which facilitate phase separation and localization to biomolecular condensates. Structural characterization of SPOP in its oligomeric state and in solution is, however, challenging due to the inherent conformational and compositional heterogeneity of the oligomeric species. Here, we develop an approach to simultaneously and self-consistently characterize the conformational ensemble and the distribution of oligomeric states of SPOP by combining small-angle X-ray scattering (SAXS) and molecular dynamics simulations. We build initial conformational ensembles of SPOP oligomers using coarse-grained molecular dynamics simulations, and use a Bayesian/maximum entropy approach to refine the ensembles, along with the distribution of oligomeric states, against a concentration series of SAXS experiments. Our results suggest that SPOP oligomers behave as rigid, helical structures in solution, and that a flexible linker region allows SPOPs substrate binding domains to extend away from the core of the oligomers. Additionally, our results are in good agreement with previous characterization of the isodesmic self-association of SPOP. In the future, the approach presented here can be extended to other systems to simultaneously characterize structural heterogeneity and self-assembly.

biophysics↗

bioRxiv2021

Improving the global dimensions of intrinsically disordered proteins in Martini 3

Coarse-grained molecular dynamics simulations are a useful tool to determine conformational ensembles of proteins. Here, we show that the coarse-grained force field Martini 3 underestimates the global dimensions of intrinsically disordered proteins (IDPs) and multidomain proteins when compared with small angle X-ray scattering (SAXS) data, and that increasing the strength of protein-water interactions favours more expanded conformations. We find that increasing the strength of interactions between protein and water by ca. 10% results in improved agreement with the SAXS data for IDPs and multi-domain proteins. We also show that this correction results in a more accurate description of self-association of IDPs and folded proteins and better agreement with paramagnetic relaxation enhancement data for most IDPs. While simulations with this revised force field still show deviations to experiments for some systems our results suggest that it is overall a substantial improvement for coarse-grained simulations of soluble proteins.

biophysics↗

bioRxiv2020

Interplay of folded domains and the disordered low-complexity domain in mediating hnRNPA1 phase separation

Liquid-liquid phase separation underlies the membrane-less compartmentalization of cells. Intrinsically disordered low-complexity domains (LCDs) often mediate phase separation, but how their phase behavior is modulated by folded domains is incompletely understood. Here, we interrogate the interplay between folded and disordered domains of the RNA-binding protein hnRNPA1. The LCD of hnRNPA1 is sufficient for mediating phase separation in vitro. However, we show that the folded RRM domains and a folded solubility-tag modify the phase behavior, even in the absence of RNA. Notably, the presence of the folded domains reverses the salt dependence of the driving force for phase separation relative to the LCD alone. Small-angle X-ray scattering experiments and coarse-grained MD simulations show that the LCD interacts transiently with the RRMs and/or the solubility-tag in a salt-sensitive manner, providing a mechanistic explanation for the observed salt-dependent phase separation. These data point to two effects from the folded domains: (1) electrostatically mediated interactions that compact hnRNPA1 and contribute to phase separation, and (2) increased solubility at higher ionic strengths mediated by the folded domains. The interplay between disordered and folded domains can modify the dependence of phase behavior on solution conditions and can obscure signatures of physicochemical interactions underlying phase separation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=192 SRC="FIGDIR/small/096966v2_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@119029borg.highwire.dtl.DTLVardef@fa274borg.highwire.dtl.DTLVardef@129deaaorg.highwire.dtl.DTLVardef@1d98f66_HPS_FORMAT_FIGEXP M_FIG hnRNPA1 phase separation is highly salt sensitive. Phase separation of the low-complexity domain (LCD) of hnRNPA1 increases with NaCl. In contrast, phase separation of full-length hnRNPA1 is saltsensitive. At low NaCl concentrations, electrostatic RRM-LCD interactions occur and can contribute positively to phase separation, but they are screened at high NaCl concentrations. The folded domains solubilize hnRNPA1 under these conditions and prevent phase separation. C_FIG

biophysics↗