Biology subjects

Grubmueller, H.

Publications and source records attributed to Grubmueller, H..

11 recordsLinked to original sources

bioRxiv2026

Dynamic microtubule-end structure governs multivalent kinetochore coupling by the Dam1c ring

Accurate chromosome segregation relies on kinetochores maintaining load-bearing attachments to dynamic microtubule ends, a coupling in which the Dam1 complex ring is central. How the microtubule-end structure and ring-microtubule interactions collectively determine attachment stability and drive force transduction remains unresolved. Here, we use multiscale modeling to show that the ring forms a "fuzzy" complex mediated by a dynamic network of intrinsically disordered regions, enabling both high-affinity binding and free diffusion along the microtubule lattice. Crucially, we find that this prototypic disordered-disordered protein complex provides most of the kinetochore-microtubule stabilization. By contrast, protofilament bending, commonly thought to drive force transduction, is sensitive to the arrangement of protofilaments along the ring and insufficient on its own to establish a robust coupling. The architecture of the dynamic microtubule end unifies these mechanisms by controlling both the progressive loss of fuzzy contacts and the resistance generated by protofilament bending. By accounting for the full conformational ensemble of microtubule structures, our model produces rupture forces similar to those previously measured and explains the distinct, tension-dependent behavior of kinetochore attachments to growing versus shortening microtubule ends. We propose that the Dam1 complex ring acts as a biased-diffusion coupler that probes and gradually remodels the evolving conformational landscape of the microtubule end under tension.

biophysics↗

bioRxiv2025

UBE2J2 sensitizes the ERAD ubiquitination cascade to changes in membrane lipid saturation

Protein-lipid crosstalk is fundamental to homeostasis in the endoplasmic reticulum (ER). The ER-associated degradation (ERAD) pathway, a branch of the ubiquitin-proteasome system, maintains ER membrane properties by degrading lipid metabolic enzymes. However, the ERAD components that sense membrane properties and their mechanisms remain poorly defined. Using reconstituted systems with purified ERAD factors, we show that membrane composition modulates the ubiquitination cascade at multiple levels. The membrane-anchored E2 UBE2J2 acts as a sensor for lipid packing: in loosely packed membranes, UBE2J2 becomes inactive due to membrane association that impedes ubiquitin loading, while tighter packing promotes its active conformation and interaction with E1. UBE2J2 activity directs ubiquitin transfer by the E3 ligases RNF145, MARCHF6, and RNF139, targeting both themselves and the substrate squalene monooxygenase. Additionally, RNF145 senses cholesterol, altering its oligomerization and activity. These findings reveal that ERAD integrates multiple lipid signals, with UBE2J2 relaying and extending the effect of lipid signals through its cooperation with multiple E3 ligases.

biochemistry↗

bioRxiv2025

Influence of ULK1 activity on the memory of ATG101 auto-activation dynamics

The initiation of autophagy is marked by the prompt convergence of initiation proteins to form super molecular complexes in spatially-defined autophagic hubs. The recruitment and activation of the ULK-kinase complex is a pivotal event in starting the initiation cascade. ULK complex-component ATG101 is required for initiating autophagy in mammalian cells, but its function is unknown. Its HORMA domain interacts with the HORMA domain of ATG13 and transmembrane protein ATG9A to collectively form the essential autophagy initiation complex ATG9A-ATG13-ATG101. ATG101 has structurally malleable elements, reminiscent of topological conversions used in related metamorphic HORMA domain proteins to control the rate of complex formation. To elucidate the function of ATG101, we monitored the interaction kinetics of ATG101 with ATG13 and ATG9A, and observed that the interaction of ATG101 with ATG9A and ATG13 is exceptionally slow. Dramatic acceleration of complex formation is observed upon a change in the fold of ATG101 induced by its transient homo-dimerization, which in turn is initiated by phosphorylation by the ULK1 kinase. In an auto-catalytic mechanism, ATG101 dimers create a positive feedback to propagate activation to further ATG101 molecules in the absence of ULK1 activity. Despite the competitive nature of the interaction interfaces, homo-dimerization of ATG101 surprisingly accelerates its association to ATG13. Memory of ATG101 activation persists for many hours after dephosphorylation and continues to accelerate the assembly of the ATG9A-ATG13-ATG101 complex. Overall, this work proposes an unusual regulatory mechanism where UKL1 initiates an ATG101 auto activation cascade, whose memory creates a responsive positive feedback that dictates the assembly rate of a key complex in autophagy initiation.

biochemistry↗

bioRxiv2025

Bimodal peptide collision cross section distribution reflects two stable conformations in the gas phase

Recent high throughput applications to shotgun proteomics have shown great benefits of coupling ion mobility spectrometry (IMS) to mass spectrometry. IMS adds a separation dimension by differentiating biomolecules by their size and shape. We (and others) find that the distribution of peptide collision cross section (CCS) is often bimodal, which limits the utility of current machine learning predictions for peptide identification. Molecular dynamics simulations indicate that the peptides in the drift tube can adopt multiple stable conformations and that the two modes correspond to predominantly extended (mostly helical) and more compact (globular and less ordered) conformations. Most peptides have a charge-dependent strong preference for one of the two conformations, while some can adapt both, as evidenced by a simple geometric model of the CCS data. We suggest a novel two-valued CCS predictor allowing for multiple peptide conformations. Its integration into data-independent acquisition proteomics increases identification rates of peptides compared to single-value predictors.

bioinformatics↗

bioRxiv2024

Microtubule dynamics are defined by conformations and stability of clustered protofilaments

Microtubules are dynamic cytoskeletal polymers that add and lose tubulin dimers at their ends. Microtubule growth, shortening and transitions between them are linked to GTP hydrolysis. Recent evidence suggests that flexible tubulin protofilaments at microtubule ends adopt a variety of shapes, complicating structural analysis using conventional techniques. Therefore, the link between GTP hydrolysis, protofilament structure and microtubule polymerization state is poorly understood. Here, we investigate the conformational dynamics of microtubule ends using coarse-grained modeling supported by atomistic simulations and cryo-electron tomography. We show that individual bent protofilaments organize in clusters, transient precursors to a straight microtubule lattice, with GTP-bound ends showing elevated and more persistent cluster formation. Differences in the mechanical properties of GTP- and GDP-protofilaments result in differences in intra-cluster tension, determining both clustering propensity and protofilament length. We propose that conformational selection at microtubule ends favors long-lived clusters of short GTP-protofilaments that are more prone to form a straight microtubule lattice and accommodate new tubulin dimers. Conversely, microtubule ends trapped in states with unevenly long and stiff GDP-protofilaments are more prone to shortening. We conclude that protofilament clustering is the key phenomenon that links the hydrolysis state of single tubulins to the polymerization state of the entire microtubule.

biophysics↗

bioRxiv2023

A Reference Data Set for Circular Dichroism Spectroscopy Comprised of Validated Intrinsically Disordered Protein Models

Circular Dichroism (CD) spectroscopy is an analytical technique that measures the wavelength-dependent differential absorbance of circularly polarized light, and is applicable to most biologically important macromolecules, such as proteins, nucleic acids, and carbohydrates. It serves to characterize the secondary structure composition of proteins, including intrinsically disordered proteins, by analyzing their recorded spectra. Several computational tools have been developed to interpret protein CD spectra. These methods have been calibrated and tested mostly on globular proteins with well-defined structures, mainly due to the lack of reliable reference structures for disordered proteins. It is therefore still largely unclear how accurately these computational methods can determine the secondary structure composition of disordered proteins. Here, we provide such a required reference data set consisting of model structural ensembles and matching CD spectra for eight intrinsically disordered proteins. Using this set of data, we have assessed the accuracy of several published CD prediction and secondary structure estimation tools, including our own CD analysis package SESCA. Our results show that for most of the tested methods, their accuracy for disordered proteins is generally lower than for globular proteins. In contrast, SESCA, which was developed using globular reference proteins, but was designed to be applicable to disordered proteins as well, performs similarly well for both classes of proteins. The new reference data set for disordered proteins should allow for further improvement of all published methods.

biophysics↗

bioRxiv2021

Bending-torsional elasticity and energetics of the plus-end microtubule tip

Microtubules (MTs), mesoscopic cellular filaments, grow primarily by the addition of GTP-bound tubulin dimers at their dynamic flaring plus-end tips. They operate as chemomechanical energy transducers with stochastic transitions to an astounding shortening motion upon hydrolyzing GTP to GDP. Time-resolved dynamics of the MT tip - a key determinant of this behavior - as a function of nucleotide state, internal lattice strain, and stabilizing lateral interactions have not been fully understood. Here, we use atomistic simulations to study the spontaneous relaxation of complete GTP-MT and GDP-MT tip models from unfavorable straight to relaxed splayed conformations and to comprehensively characterize the elasticity of MT tips. Our simulations reveal the dominance of viscoelastic dynamics of MT protofilaments during the relaxation process, driven by the stored bending-torsional strain and counterbalanced by the inter-protofilament interactions. We show that the post-hydrolysis MT tip is exposed to higher activation energy barriers for straight lattice formation, which translates into its inability to elongate. Our study provides an information ratchet mechanism for the elastic energy conversion and release by MT tips and offers new insights into the mechanoenzymatics of MTs.

biophysics↗

bioRxiv2021

Time-lagged Independent Component Analysis of Random Walks and Protein Dynamics

Time-lagged independent component analysis (tICA) is a widely used dimension reduction method for the analysis of molecular dynamics (MD) trajectories and has proven particularly useful for the construction of protein dynamics Markov models. It identifies those slow collective degrees of freedom onto which the projections of a given trajectory show maximal autocorrelation for a given lag time. Here we ask how much information on the actual protein dynamics and, in particular, the free energy landscape that governs these dynamics the tICA-projections of MD-trajectories contain, as opposed to noise due to the inherently stochastic nature of each trajectory. To answer this question, we have analyzed the tICA-projections of high dimensional random walks using a combination of analytical and numerical methods. We find that the projections resemble cosine functions and strongly depend on the lag time, exhibiting strikingly complex behaviour. In particular, and contrary to previous studies of principal component projections, the projections change non-continuously with increasing lag time. The tICA-projections of selected 1 s protein trajectories and those of random walks are strikingly similar, particularly for larger proteins, suggesting that these trajectories contain only little information on the energy landscape that governs the actual protein dynamics. Further the tICA-projections of random walks show clusters very similar to those observed for the protein trajectories, suggesting that clusters in the tICA-projections of protein trajectories do not necessarily reflect local minima in the free energy landscape. We also conclude that, in addition to the previous finding that certain ensemble properties of non-converged protein trajectories resemble those of random walks, this is also true for their time correlations. Due to the higher complexity of the latter, this result also suggests tICA analyses as a more sensitive tool to test MD simulations for proper convergence.

biophysics↗

bioRxiv2020

Implementation of a Bayesian Secondary Structure Estimation Method for the SESCA Circular Dichroism Analysis Package

Circular dichroism spectroscopy is a structural biology technique frequently applied to determine the secondary structure composition of soluble proteins. Our recently introduced computational analysis package SESCA aids the interpretation of protein circular dichroism spectra and enables the validation of proposed corresponding structural models. To further these aims, we present the implementation and characterization of a new Bayesian secondary structure estimation method in SESCA, termed SESCA_bayes. SESCA_bayes samples possible secondary structures using a Monte Carlo scheme, driven by the likelihood of estimated scaling errors and non-secondary-structure contributions of the measured spectrum. SESCA_bayes provides an estimated secondary structure composition and separate uncertainties on the fraction of residues in each secondary structure class. It also assists efficient model validation by providing a posterior secondary structure probability distribution based on the measured spectrum. Our presented study indicates that SESCA_bayes estimates the secondary structure composition with a significantly smaller uncertainty than its predecessor, SESCA_deconv, which is based on spectrum deconvolution. Further, the mean accuracy of the two methods in our analysis is comparable, but SESCA_bayes provides more accurate estimates for circular dichroism spectra that contain considerable non-SS contributions. PROGRAM SUMMARYProgram Title: SESCA_bayes CPC Library link to program files: (to be added by Technical Editor) Developers repository link: https://www.mpibpc.mpg.de/sesca Code Ocean capsule: (to be added by Technical Editor) Licensing provisions: GPLv3 Programming language: Python Supplementary material: Nature of problem: The circular dichroism spectrum of a protein is strongly correlated with its secondary structure composition. However, determining the secondary structure from a spectrum is hindered by non-secondary structure contributions and by scaling errors due the uncertainty of the protein concentration. If not taken properly into account, these experimental factors can cause considerable errors when conventional secondary-structure estimation methods are used. Because these errors combine with errors of the proposed structural model in a non-additive fashion, it is difficult to assess how much uncertainty the experimental factors introduce to model validation approaches based on circular dichroism spectra. Solution methodFor a given measured circular dichroism spectrum, the SESCA_bayes algorithm applies Bayesian statistics to account for scaling errors and non-secondary structure contributions and to determine the conditional secondary structure probability distribution. This approach relies on fast spectrum predictions based on empirical basis spectrum sets and joint probability distribution maps for scaling factors and non-secondary structure distributions. Because SESCA_bayes estimates the most probable secondary structure composition based on a probability-weighted sample distribution, it avoids the typical fitting errors that occur during conventional spectrum deconvolution methods. It also estimates the uncertainty of circular dichroism based model validation more accurately than previous methods of the SESCA analysis package.

biophysics↗

bioRxiv2020

How Accurate Are Circular Dichroism Based Secondary Structure Estimates?

Circular dichroism (CD) spectroscopy is highly sensitive to the secondary structure (SS) composition of proteins. Several methods exist to either estimate the SS composition of a protein or to validate existing structural models using its CD spectrum. The accuracy and precision of these methods depend on the quality of both the measured CD spectrum and the used reference structure. Using a large reference protein set with high quality CD spectra and synthetic data derived from this set, we quantified deviations from both ideal spectra and reference structures due to experimental limitations. We also determined the impact of these deviations on SS estimation, CD prediction, and SS validation methods of the SESCA analysis package. With regard to the CD spectra, our results suggest intensity scaling errors and non-SS contributions as the main causes of inaccuracies. These factors also can lead to overestimated model errors during validation. The errors of the used reference structures combine non-additively with errors caused by the CD spectrum, which increases the uncertainty of model validation. We have further shown that the effects of scaling errors in the CD spectrum can be nearly eliminated by appropriate re-scaling, and that the accuracy of model validation methods can be improved by accounting for typical non-SS contributions. These improvements have now been implemented within the SESCA package.

biophysics↗

bioRxiv2020

Microtubule instability driven by longitudinal and lateral strain propagation

Tubulin dimers associate longitudinally and laterally to form metastable microtubules (MTs). MT disassembly is preceded by subtle structural changes in tubulin fueled by GTP hydrolysis. These changes render the MT lattice unstable, but it is unclear exactly how they affect lattice energetics and strain. We performed long-time atomistic simulations to interrogate the impacts of GTP hydrolysis on tubulin lattice conformation, lateral inter-dimer interactions, and (non-)local lateral coordination of dimer motions. The simulations suggest that most of the hydrolysis energy is stored in the lattice in the form of longitudinal strain. While not significantly affecting lateral bond stability, the stored elastic energy results in more strongly confined and correlated dynamics of GDP-tubulins, thereby entropically destabilizing the MT lattice.

biophysics↗