Biology subjects

von Bülow, S.

Publications and source records attributed to von Bülow, S..

10 recordsLinked to original sources

bioRxiv2025

AF-CALVADOS: AlphaFold-guided simulations of multi-domain proteins at the proteome level

Deep-learning methods have transformed our ability to predict the three-dimensional structures of folded proteins from sequence, and coarse-grained simulations have made it possible to study intrinsically disordered proteins at the proteome scale. More than half of human proteins, however, contain mixtures of disordered regions and one or more folded domains, and the biological function of these multi-domain proteins depends on the interplay between the folded and disordered regions. Here, we developed AF-CALVADOS, a coarse-grained simulation model that is informed by AlphaFold to model the dynamics of intrinsically disordered proteins and multi-domain proteins containing mixtures of folded and disordered regions. AF-CALVADOS leverages information from AlphaFold 2 to model folded regions that we then integrate with the coarse-grained CALVADOS model. Our automated framework makes it possible to perform simulations of any soluble folded or disordered protein without manually defining the folded regions, enabling scaling to the proteome level. We validate AF-CALVADOS using experimental SAXS data for more than 400 proteins and find that it performs well across proteins with varying amounts of ordered and disordered regions. We demonstrate the scalability of AF-CALVADOS by performing simulations of 12,483 intracellular human proteins and make the data freely available; we envisage that large-scale simulation data generated by AF-CALVADOS can be used to benchmark or train machine learning models for flexible, multi-domain proteins. The conformational ensembles can also be used to study sequence-dynamics-function relationships at scale, and can shed light on the interplay between folded and disordered regions. We exemplify this by analysing the disordered regions in 1,487 human transcription factors.

biophysics↗

bioRxiv2024

A coarse-grained model of disordered RNA for simulations of biomolecular condensates

Protein-RNA condensates are involved in a range of cellular activities. Coarse-grained molecular models of intrinsically disordered proteins have been developed to shed light on and predict single-chain properties and phase separation. An RNA model compatible with such models for disordered proteins would enable the study of complex biomolecular mixtures involving RNA. Here, we present a sequence-independent coarse-grained, two-bead-per-nucleotide model of disordered, flexible RNA based on a hydropathy scale. We parameterize the model, which we term CALVADOS-RNA, using a combination of bottom-up and top-down approaches to reproduce local RNA geometry and intramolecular interactions based on atomistic simulations and in vitro experiments. The model semi-quantitatively captures several aspects of RNA-RNA and RNA-protein interactions. We examined RNA-RNA interactions by comparing calculated and experimental virial coefficients, and non-specific RNA-protein interaction by studying reentrant phase behavior of protein-RNA mixtures. We demonstrate the utility of the model by simulating the formation of mixed condensates consisting of the disordered region of MED1 and RNA chains, and the selective partitioning of disordered regions from transcription factors into these, and compare the results to experiments. Despite the simplicity of our model we show that it captures several key aspects of protein-RNA interactions and may therefore be used as a baseline model to study several aspects of the biophysics and biology of protein-RNA condensates.

biophysics↗

bioRxiv2024

Prediction of phase separation propensities of disordered proteins from sequence

Phase separation is thought to be one possible mechanism governing the selective cellular enrichment of biomolecular constituents for processes such as transcriptional activation, mRNA regulation, and immune signaling. Phase separation is mediated by multivalent interactions of biological macromolecules including intrinsically disordered proteins and regions (IDRs). Despite considerable advances in experiments, theory and simulations, the prediction of the thermodynamics of IDR phase behaviour remains challenging. We combined coarse-grained molecular dynamics simulations and active learning to develop a fast and accurate machine learning model to predict the free energy and saturation concentration for phase separation directly from sequence. We validate the model using both experimental and computational data. We apply our model to all 27,663 IDRs of chain length up to 800 residues in the human proteome and find that 1,420 of these (5%) are predicted to undergo homotypic phase separation with transfer free energies < -2kBT. We use our model to understand the relationship between single-chain compaction and phase separation, and find that changes from charge-to hydrophobicity-mediated interactions can break the symmetry between intra-and inter-molecular interactions. We also analyse the structural preferences at condensate interfaces and find substantial heterogeneity that is determined by the same sequence properties as phase separation. Our work refines the established rules governing the relationships between sequence features and phase separation propensities, and our prediction models will be useful for interpreting and designing cellular experiments on the role of phase separation, and for the design of IDRs with specific phase separation propensities.

biophysics↗

bioRxiv2024

A coarse-grained model for disordered and multi-domain proteins

Many proteins contain more than one folded domain, and such modular multi-domain proteins help expand the functional repertoire of proteins. Because of their larger size and often substantial dynamics, it may be difficult to characterize the conformational ensembles of multi-domain proteins by simulations. Here, we present a coarse-grained model for multi-domain proteins that is both fast and provides an accurate description of the global conformational properties in solution. We show that the accuracy of a one-bead-per-residue coarse-grained model depends on how the interaction sites in the folded domains are represented. Specifically, we find excessive domain-domain interactions if the interaction sites are located at the position of the C atoms. We also show that if the interaction sites are located at the centre of mass of the residue, we obtain good agreement between simulations and experiments across a wide range of proteins. We then optimize our previously described CALVADOS model using this centre-of-mass representation, and validate the resulting model using independent data. Finally, we use our revised model to simulate phase separation of both disordered and multi-domain proteins, and to examine how the stability of folded domains may differ between the dilute and dense phases. Our results provide a starting point for understanding interactions between folded and disordered regions in proteins, and how these regions affect the propensity of proteins to self-associate and undergo phase separation.

biophysics↗

bioRxiv2021

GlycoSHIELD: a versatile pipeline to assess glycan impact on protein structures

More than 75% of surface and secreted proteins are modified by covalent addition of complex sugars through N- and O-glycosylation. Unlike proteins, glycans do not typically adopt specific secondary structures and remain very mobile, influencing protein dynamics and interactions with other molecules. Glycan conformational freedom impairs complete structural elucidation of glycoproteins. Computer simulations may be used to model glycan structure and dynamics. However, such simulations typically require thousands of computing hours on specialized supercomputers, thus limiting routine use. Here, we describe a reductionist method that can be implemented on personal computers to graft ensembles of realistic glycan conformers onto static protein structures in a matter of minutes. Using this open-source pipeline, we reconstructed the full glycan cover of SARS-CoV-2 Spike protein (S-protein) and a human GABAA receptor. Focusing on S-protein, we show that GlycoSHIELD recapitulates key features of extended simulations of the glycosylated protein, including epitope masking, and provides new mechanistic insights on N-glycan impact on protein structural dynamics.

bioinformatics↗

bioRxiv2021

Structural basis of polyamine transport by human ATP13A2 (PARK9)

Polyamines are small, organic polycations that are ubiquitous and essential to all forms of life. Currently, how polyamines are transported across membranes is not understood. Recent studies have suggested that ATP13A2 and its close homologs, collectively known as P5B-ATPases, are polyamine transporters at endo-/lysosomes. Loss-of-function mutations of ATP13A2 in humans cause hereditary early-onset Parkinsons disease. To understand the polyamine transport mechanism of ATP13A2, we determined high-resolution cryo-EM structures of human ATP13A2 in five distinct conformational intermediates, which together represent a near-complete transport cycle of ATP13A2. The structural basis of the polyamine specificity was revealed by an endogenous polyamine molecule bound to a narrow, elongated cavity within the transmembrane domain. The structures show an atypical transport path for a water-soluble substrate, where polyamines may exit within the cytosolic leaflet of the membrane. Our study provides important mechanistic insights into polyamine transport and a framework to understand functions and mechanisms of P5B-ATPases. HighlightsCryo-EM structures of human ATP13A2 in five distinct conformations at 2.5-3.7 [A] resolutions. Unique features of ATP13A2 in comparison to other P-type ATPases. Structure of the substrate-binding pocket of ATP13A2 and the molecular basis of polyamine binding. Conformational changes along the transport cycle and proposed model for polyamine transport.

biochemistry↗

bioRxiv2020

Simulation of FUS protein condensates with an adapted coarse-grained model

Disordered proteins and nucleic acids can condense into droplets that resemble the membraneless organelles observed in living cells. MD simulations offer a unique tool to characterize the molecular interactions governing the formation of these biomolecular condensates, their physico-chemical properties, and the factors controlling their composition and size. However, biopolymer condensation depends sensitively on the balance between different energetic and entropic contributions. Here, we develop a general strategy to fine-tune the potential energy function for molecular dynamics simulations of biopolymer phase separation. We rebalance protein-protein interactions against solvation and entropic contributions to match the excess free energy of transferring proteins between dilute solution and condensate. We illustrate this formalism by simulating liquid droplet formation of the FUS low complexity domain (LCD) with a rebalanced MARTINI model. By scaling the strength of the nonbonded interactions in the coarse-grained MARTINI potential energy function, we map out a phase diagram in the plane of protein concentration and interaction strength. Above a critical scaling factor of c {approx} 0.6, FUS LCD condensation is observed, where = 1 and 0 correspond to full and repulsive interactions in the MARTINI model, respectively. For a scaling factor = 0.65, we recover the experimental densities of the dilute and dense phases, and thus the excess protein transfer free energy into the droplet and the saturation concentration where FUS LCD condenses. In the region of phase separation, we simulate FUS LCD droplets of four different sizes in stable equilibrium with the dilute phase and slabs of condensed FUS LCD for tens of microseconds, and over one millisecond in aggregate. We determine surface tensions in the range of 0.01 to 0.4mN/m from the fluctuations of the droplet shape and from the capillary-wave-like broadening of the interface between the two phases. From the dynamics of the protein end-to-end distance, we estimate shear viscosities from 0.001 to 0.02Pas for the FUS LCD droplets with scaling factors in the range of 0.625 to 0.75, where we observe liquid droplets. Significant hydration of the interior of the droplets keeps the proteins mobile and the droplets fluid.

biophysics↗

bioRxiv2020

Map of SARS-CoV-2 spike epitopes not shielded by glycans.

The severity of the COVID-19 pandemic, caused by the SARS-CoV-2 coronavirus, calls for the urgent development of a vaccine. The primary immunological target is the SARS-CoV-2 spike (S) protein. S is exposed on the viral surface to mediate viral entry into the host cell. To identify possible antibody binding sites not shielded by glycans, we performed multi-microsecond molecular dynamics simulations of a 4.1 million atom system containing a patch of viral membrane with four full-length, fully glycosylated and palmitoylated S proteins. By mapping steric accessibility, structural rigidity, sequence conservation and generic antibody binding signatures, we recover known epitopes on S and reveal promising epitope candidates for vaccine development. We find that the extensive and inherently flexible glycan coat shields a surface area larger than expected from static structures, highlighting the importance of structural dynamics in epitope mapping.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biophysics↗

bioRxiv2020

In situ structural analysis of SARS-CoV-2 spike reveals flexibility mediated by three hinges

The spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is required for cell entry and is the major focus for vaccine development. We combine cryo electron tomography, subtomogram averaging and molecular dynamics simulations to structurally analyze S in situ. Compared to recombinant S, the viral S is more heavily glycosylated and occurs predominantly in a closed pre-fusion conformation. We show that the stalk domain of S contains three hinges that give the globular domain unexpected orientational freedom. We propose that the hinges allow S to scan the host cell surface, shielded from antibodies by an extensive glycan coat. The structure of native S contributes to our understanding of SARS-CoV-2 infection and the development of safe vaccines. The large scale tomography data set of SARS-CoV-2 used for this study is therefore sufficient to resolve structural features to below 5 [A]ngstrom, and is publicly available at EMPIAR-10453.

molecular biology↗

bioRxiv2020

Kinetics of Atg2-mediated lipid transfer from the ER can account for phagophore expansion

The protein Atg2 has been proposed to form a membrane tether that mediates lipid transfer from the ER to the phagophore in autophagy. However, recent kinetic measurements on the human homolog ATG2A indicated a transport rate of only about one lipid per minute, which would be far too slow to deliver the millions of lipids required to form a phagophore on a physiological time scale. Here, we revisit the analysis of the fluorescence quenching experiments. We develop a detailed kinetic model of the lipid transfer between two membranes bridged by a tether that forms a conduit for lipids. The model provides an excellent fit to the fluorescence experiments, with a lipid transfer rate of about 100 per second and protein. At this rate, Atg2-mediated transfer can supply a significant fraction of the lipids required in autophagosome biogenesis. Our kinetic model is generally applicable to lipid-transfer experiments, in particular to proteins forming organelle contact sites in cells.

biophysics↗