Biology subjects

Topf, M.

Publications and source records attributed to Topf, M..

At least 19 recordsLinked to original sources

bioRxiv2026

ProNA3D: Distance-Based Analysis of Nucleic Acid-Containing Interfaces

1.Biomolecular interactions are central to many essential cellular processes, but RNA-containing complexes remain challenging to resolve structurally, even as experimental methods and AI-based prediction have expanded structural coverage. Tools for the integrated analysis of complex interfaces remain limited. We present ProNA3D, a tool that provides a unified platform for analyzing protein-nucleic acid and nucleic acid-only complexes, bridging the gap between structure prediction and functional interpretation. ProNA3D supports both experimental and computationally predicted structures, incorporating scoring metrics for AlphaFold3 predictions. It also offers interactive two-dimensional interface visualization and secondary-structure topology plots for RNA and DNA. An interface-based density zoning feature facilitates structure analysis in cryo-EM maps, allowing evaluation of dynamic complexes in the context of heterogeneous density. We demonstrate ProNA3D on diverse complexes solved by X-ray crystallography or cryo-EM, as well as on computational models. For example, in a trimeric complex of HIV-1 RNA and a human antibody, ProNA3D identified a high-connectivity nucleotide with potential functional relevance. Applying ProNA3D to the entire Protein Data Bank revealed distinct interface connectivity trends and interaction modes characteristic of specific complexes (e.g., in methyltransferase-DNA and CRISPR-associated) in nucleic acid-containing interfaces. The method is available as both a UCSF ChimeraX plug-in for visualization and a command-line tool at https://gitlab.com/topf-lab/ProNA3D. In addition, the repository contains the results of the large-scale analyses.

bioinformatics↗

bioRxiv2025

Structural mechanisms of drebrin-mediated F-actin network modulation

Drebrin modulates F-actin networks and links them to other intracellular components, regulating crucial processes including neuritogenesis, synaptic plasticity, virus internalisation and cancer invasion. Using single-particle cryo-EM we characterise drebrins interaction with F-actin through two separate conserved actin binding domains (ABD1 and ABD2), revealing structural bases for its F-actin-modulating properties. We describe a multimodal interaction where drebrins ABD1 can adopt two conformations and a long flexible loop connecting to ABD2 allows the two ABDs to occupy multiple relative positions along F-actin. Despite harbouring two separated ABDs, we find that drebrin is not a strong direct F-actin bundler. Drebrins ABDs bind across multiple actin protomers and their subdomains and modify the longitudinal inter-protomer interface, explaining their F-actin stabilising properties. Furthermore, we show drebrins binding site on F-actin is shared with other critical actin-binding and regulatory proteins, explaining their competitive displacement.

biochemistry↗

bioRxiv2025

Assessing scoring metrics for AlphaFold2 and AlphaFold3 protein complex predictions

1.Recent breakthroughs in AI-driven protein structure prediction have revolutionized structural biology, unlocking new possibilities to model complex biomolecular interactions. We evaluated widely-used scoring metrics for assessing models predicted by ColabFold with templates, ColabFold without templates, and AlphaFold3. We benchmarked the optimal cutoffs for these assessment scores using a set of 223 heterodimeric, high-resolution protein structures and their predictions. Our results show that ColabFold with templates and AlphaFold3 perform similarly and both outperform ColabFold without templates. However, the assessment scores perform best on ColabFold without templates. Furthermore, interface-specific scores are more reliable for evaluating protein complex predictions compared to the corresponding global scores. Notably, ipTM and model confidence achieve the best discrimination between correct and incorrect predictions. Based on our results, we developed a weighted combined score, C2Qscore, to improve model quality assessment. We used C2Qscore to analyse dimers from large assemblies solved by cryoEM, revealing potential limitations of the existing metrics when multiple configurations of heterodimers are possible. This study provides insights into the strengths and weaknesses of current scores and offers guidance for improving protein complex model assessment under realistic use case conditions. C2Qscore has been integrated as a tool into our ChimeraX plug-in PICKLUSTER v.2.0 and is also available as a command-line tool on https://gitlab.com/topf-lab/c2qscore. Impact of this workMany essential cellular functions rely on protein complexes, which are now predominantly predicted using AlphaFold by both experts and non-experts. This study systematically evaluates the performance of multiple widely used scoring metrics for distinguishing accurate from poor predictions. The new C2Qscore developed in this study improves the reliability of AlphaFold model assessments, enabling a more consistent and accessible evaluation of protein structures. These advancements support downstream applications in biomedicine, drug discovery, and computational protein design.

bioinformatics↗

bioRxiv2023

Key Proteins for Regeneration in A. mexicanum: Transcriptomic Insights from Aged and Juvenile Limbs

The axolotl is an animal with remarkable regenerative abilities, making it an ideal model for studying potential regenerative therapies in mammals, including humans. However, the molecular mechanisms involved in regeneration remain unclear. We conducted a transcriptomic analysis of juvenile axolotls limbs and their blastema and compared the results with aged axolotls that failed to regenerate after amputation. We identified a set of genes involved in cell differentiation, transcriptional regulation, cartilage development, bone morphogenesis, and extracellular matrix remodeling. Four highly expressed genes (FSTL1, ADAMTS17, GPX7, and CTHRC1) were identified in regenerating tissue, but underexpressed in aged axolotls. Structural and homology analysis showed that these genes are conserved and have important roles in development, bone morphogenesis, and cartilage formation. Our findings propose a novel set of axolotl genes involved in tissue regeneration that could be a starting point for further studies in other vertebrates. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/556684v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@11184f5org.highwire.dtl.DTLVardef@13023a3org.highwire.dtl.DTLVardef@173ac2corg.highwire.dtl.DTLVardef@12c9c38_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2023

Modeling flexible protein structure with AlphaFold2 and cross-linking mass spectrometry

We propose a pipeline that combines AlphaFold2 (AF2) and crosslinking mass spectrometry (XL-MS) to model the structure of proteins with multiple conformations. The pipeline consists of two main steps: ensemble generation using AF2, and conformer selection using XL-MS data. For conformer selection, we developed two scores - the monolink probability score (MP) and the crosslink probability score (XLP), both of which are based on residue depth. We benchmarked MP and XLP on a large dataset of decoy protein structures, and showed that our scores outperform previously developed scores. We then tested our methodology on three proteins having an open and closed conformation in the Protein Data Bank: Complement component 3 (C3), luciferase, and glutamine-binding periplasmic protein (QBP), first generating ensembles using AF2, which were then screened for the open and closed conformations using experimental XL-MS data. In five out of six cases, the most accurate model within the AF2 ensembles - or a conformation within 1 [A] of this model - was identified using crosslinks, as assessed through the XLP score. In the remaining case, only the monolinks (assessed through the MP score) successfully identified the open conformation of QBP. This serves as a compelling proof-of-concept for the effectiveness of monolinks. In contrast, the AF2 assessment score (pTM) was only able to identify the most accurate conformation in two out of six cases. Our results highlight the complementarity of AF2 with experimental methods like XL-MS, with the MP and XLP scores providing reliable metrics to assess the quality of the predicted models.

biochemistry↗

bioRxiv2023

CASP15 cryoEM protein and RNA targets: refinement and analysis using experimental maps

CASP assessments primarily rely on comparing predicted coordinates with experimental reference structures. However, errors in the reference structures can potentially reduce the accuracy of the assessment. This issue is particularly prominent in cryoEM-determined structures, and therefore, in the assessment of CASP15 cryoEM targets, we directly utilized density maps to evaluate the predictions. A method for ranking the quality of protein chain predictions based on rigid fitting to experimental density was found to correlate well with the CASP assessment scores. Overall, the evaluation against the density map indicated that the models are of high accuracy although local assessment of predicted side chains in a 1.52 [A] resolution map showed that side-chains are sometimes poorly positioned. The top 136 predictions associated with 9 protein target reference structures were selected for refinement, in addition to the top 40 predictions for 11 RNA targets. To this end, we have developed an automated hierarchical refinement pipeline in cryoEM maps. For both proteins and RNA, the refinement of CASP15 predictions resulted in structures that are close to the reference target structure, including some regions with better fit to the density. This refinement was successful despite large conformational changes and secondary structure element movements often being required, suggesting that predictions from CASP-assessed methods could serve as a good starting point for building atomic models in cryoEM maps for both proteins and RNA. Loop modeling continued to pose a challenge for predictors with even short loops failing to be accurately modeled or refined at times. The lack of consensus amongst models suggests that modeling holds the potential for identifying more flexible regions within the structure.

bioinformatics↗

bioRxiv2023

PICKLUSTER: A protein-interface clustering and analysis plug-in for UCSF ChimeraX

MotivationThe identification and characterization of interfaces in protein complexes is crucial for understanding the mechanisms of molecular recognition. These interfaces are also attractive targets for protein inhibition. However, targeting protein interfaces can be challenging for large interfaces that consist of multiple interacting regions. We present PICKLUSTER -a program for identifying sub-interfaces in protein-protein complexes using distance clustering. The division of the interface into smaller "sub-interfaces" offers a more focused approach for targeting protein-protein interfaces. Availability and implementationThe plug-in PICKLUSTER is implemented for the molecular visualization program UCSF ChimeraX 1.4 and subsequent versions and and is freely available in the ChimeraX toolshed or, together with the source code, from https://gitlab.com/topf-lab/pickluster.git). Contactmaya.topf@cssb-hamburg.de

bioinformatics↗

bioRxiv2023

Assessment of three-dimensional RNA structure prediction in CASP15

The prediction of RNA three-dimensional structures remains an unsolved problem. Here, we report assessments of RNA structure predictions in CASP15, the first CASP exercise that involved RNA structure modeling. Forty two predictor groups submitted models for at least one of twelve RNA-containing targets. These models were evaluated by the RNA-Puzzles organizers and, separately, by a CASP-recruited team using metrics (GDT, lDDT) and approaches (Z-score rankings) initially developed for assessment of proteins and generalized here for RNA assessment. The two assessments independently ranked the same predictor groups as first (AIchemy_RNA2), second (Chen), and third (RNAPolis and GeneSilico, tied); predictions from deep learning approaches were significantly worse than these top ranked groups, which did not use deep learning. Further analyses based on direct comparison of predicted models to cryogenic electron microscopy (cryo-EM) maps and X-ray diffraction data support these rankings. With the exception of two RNA-protein complexes, models submitted by CASP15 groups correctly predicted the global fold of the RNA targets. Comparisons of CASP15 submissions to designed RNA nanostructures as well as molecular replacement trials highlight the potential utility of current RNA modeling approaches for RNA nanotechnology and structural biology, respectively. Nevertheless, challenges remain in modeling fine details such as non- canonical pairs, in ranking among submitted models, and in prediction of multiple structures resolved by cryo-EM or crystallography.

biophysics↗

bioRxiv2023

ChemEM: flexible docking of small molecules in Cryo-EM structures using difference maps

The rapid advancement of the "resolution revolution" has propelled cryo-electron microscopy (cryo-EM) to the forefront of structure-based drug discovery. However, the majority of cryo-EM structures are solved at medium resolution (3-4[A]), an unexplored territory for small-molecule docking, due to difficulty in positioning ligands and the surrounding side-chains. Therefore, the development of software capable of reliably and automatically docking ligands into cryo-EM maps at such resolutions is of utmost importance. ChemEM is a novel method that employs cryo-EM data, difference mapping, and a physico-chemical scoring function to flexibly dock one or multiple ligands in a protein binding site. To validate its effectiveness, ChemEM was assessed using a highly curated benchmark containing 33 experimental cryo-EM structures, spanning a resolution range of 2.2-5.6 [A]. In all but one case, the method placed the ligands in the density in an accurate conformation, often better than the PDB deposited solutions. Even without the use of cryo-EM density, the ChemEM scoring function outperformed the well-established docking software AutoDock Vina. Furthermore, the study demonstrates that useful information is present in the map even at low resolutions. ChemEM unlocks the potential of medium-resolution cryo-EM structures for drug discovery.

bioinformatics↗

bioRxiv2022

Structural journey of an insecticidal pore-forming protein targeting western corn rootworm

Broad adoption of transgenic crops has revolutionized agriculture. However, resistance to insecticidal proteins by agricultural pests poses a continuous challenge to maintaining crop productivity and new proteins are urgently needed to replace existing transgenic traits. We identified an insecticidal membrane attack complex/perforin (MACPF) protein, Mpf2Ba1, with strong activity against western corn rootworm larvae and a novel site of action. By integrating X-ray crystallography, cryo-EM, and modelling, we determined monomeric, pre-pore and pore structures, revealing changes between structural states at atomic resolution. We discovered a monomer inhibition mechanism, a molecular "switch" associated with pre-pore activation/oligomerization upon gut fluid incubation and solved the highest resolution MACPF pore structure to-date. Our findings provide a mechanistic basis for Mpf2Ba1 effectiveness as an insecticidal protein with potential for biotechnology development. One-Sentence SummaryThe molecular mechanism of an insecticidal protein is revealed through 3D structures of the three main pore formation states

molecular biology↗

bioRxiv2022

GOAT: Deep learning-enhanced Generalized Organoid Annotation Tool

Organoids have emerged as a powerful technology to investigate human development, model diseases and for drug discovery. However, analysis tools to rapidly and reproducibly quantify organoid parameters from microscopy images are lacking. We developed a deep-learning based generalized organoid annotation tool (GOAT) using instance segmentation with pixel-level identification of organoids to quantify advanced organoid features. Using a multicentric dataset, including multiple organoid systems (e.g. liver, intestine, tumor, lung), we demonstrate generalization of the tool to annotate a diverse range of organoids generated in different laboratories and high performance in comparison to previously published methods. In sum, GOAT provides fast and unbiased quantification of organoid experiments to accelerate organoid research and facilitates novel high-throughput applications.

bioinformatics↗

bioRxiv2022

Cryo-EM structure and B-factorrefinement with ensemble representation

Cryo-EM experiments produce images of macromolecular assemblies that are combined to produce three-dimensional density maps. It is common to fit atomic models of the contained molecules to interpret those maps, followed by a density-guided refinement. Here, we propose TEMPy-REFF, a novel method for atomic structure refinement in cryo-EM density maps. By representing the atomic positions as components of a mixture model, their variances as B-factors, and a model ensemble description, we significantly improve the fit to the map compared to what is currently achievable with state-of-the-art methods. We validate our method on a large benchmark of 366 cryo-EM maps from EMDB at 1.8-7.1[A] resolution and their corresponding PDB assembly models. We also show that our approach can provide newly-modelled regions in EMDB deposited maps by combining it with AlphaFold-Multimer. Finally, our method provides a natural interpretation of maps into components, allowing us to accurately create composite maps.

biophysics↗

bioRxiv2021

The pore conformation of lymphocyte perforin

Perforin is a pore-forming protein that facilitates rapid killing of pathogen-infected or cancerous cells by the immune system. Perforin is released from cytotoxic lymphocytes, together with pro-apoptotic granzymes, to bind to the plasma membrane of the target cell where it oligomerises and forms pores. The pores allow granzyme entry, which rapidly triggers the apoptotic death of the target cell. Here we present a 4 [A] resolution cryo-EM structure of the perforin pore, revealing new inter- and intra-molecular interactions stabilising the pore. During assembly and pore formation, the helix-turn-helix motif at the bend in the central {beta}-sheet moves away from the bend to form an intermolecular contact. Cryo-electron tomography shows that prepores form on the membrane surface with minimal conformational changes. Our findings suggest the sequence of conformational changes underlying oligomerisation and membrane insertion, and explain how several pathogenic mutations affect function.

biochemistry↗

bioRxiv2021

Molecular mechanism of a parasite kinesin motor and implications for its inhibition

Plasmodium parasites cause malaria and are responsible annually for hundreds of thousands of deaths. They have a complex life cycle in which distinct stages are transmitted between, and reproduce in, human and mosquito hosts. In the light of emerging resistance to current therapies, components of the parasite replicative machinery are potentially important targets for anti-parasite drugs. Members of the superfamily of kinesin motors play important roles in the microtubule-based replicative spindle machinery, and kinesin-5 motors are established anti-mitotic targets in other disease contexts. We therefore studied kinesin-5 from Plasmodium falciparum (PfK5) and characterised the biochemical properties and structure of the PfK5 motor domain. We found that the PfK5 motor domain is an ATPase with microtubule plus-end directed motility. We used cryo-EM to determine the motors microtubule-bound structure in no nucleotide and AMPPNP-bound states. Despite significant sequence divergence in this motor, these structures reveal that this parasite motor exhibits classical kinesin mechanochemistry. This includes ATP-induced neck-linker docking to the motor domain, which is consistent with the motors plus-ended directed motility. Crucially, we also observed that a large insertion in loop5 of the PfK5 motor domain creates a dramatically different chemical environment in the well characterised human kinesin-5 drug-binding site. Our data thereby reveal the possibility for selective inhibition of PfK5 and can be used to inform future exploration of Plasmodium kinesins as anti-parasite targets.

biophysics↗

bioRxiv2020

Assessment of protein-protein interfaces in cryo-EM derived assemblies

Structures of macromolecular assemblies derived from cryo-EM maps often contain errors that become more abundant with decreasing resolution. Despite efforts in the cryo-EM community to develop metrics for the map and atomistic model validation, thus far, no specific scoring metrics have been applied systematically to assess the interface between the assembly subunits. Here, we have assessed protein-protein interfaces in macromolecular assemblies derived by cryo-EM. To this end, we developed PI-score, a density-independent machine learning-based metric, trained using protein-protein interfaces features in high-resolution crystal structures. Using PI-score, we were able to identify errors at interfaces in the PDB-deposited cryo-EM structures (including SARS-CoV-2 complexes) and in the models submitted for cryo-EM targets in CASP13 and the EM model challenge. Some of the identified errors, especially at medium-to-low resolution structures, were not captured by density-based assessment scores. Our method can therefore provide a powerful complementary assessment tool for the increasing number of complexes solved by cryo-EM.

bioinformatics↗

bioRxiv2020

Gut Microbiota-Targeted Diets Modulate Human Immune Status

Diet modulates the gut microbiome, and gut microbes, in turn, can impact the immune system. Here, we used two gut microbiota-targeted dietary interventions, plant-based fiber or fermented foods, to determine how each influences the human microbiome and immune system in healthy adults. Using a 17-week randomized, prospective study design combined with -omics measurements of microbiome and host, including extensive immune profiling, we found distinct effects of each diet. High-fiber consumers showed increased gut microbiome-encoded glycan-degrading CAZymes despite stable community diversity. Three distinct immunological trajectories in high fiber-consumers corresponded to baseline microbiota diversity. Alternatively, the high-fermented food diet steadily increased microbiota diversity and decreased inflammatory markers. The data highlight how coupling dietary interventions to deep and longitudinal immune and microbiome profiling can provide individualized and population-wide insight. Our results indicate that fermented foods may be valuable in countering the decreased microbiome diversity and increased inflammation pervasive in the industrialized society.

microbiology↗

bioRxiv2020

TopoStats - an automated tracing program for AFM images

We present TopoStats, a Python toolkit for automated editing and analysis of Atomic Force Microscopy images. The program automates identification and tracing of individual molecules in circular and linear conformations without user input. TopoStats was able to identify and trace a range of molecules within AFM images, finding, on average, 90% of all individual molecules and molecular assemblies within a wide field of view, and without the need for prior processing. DNA minicircles of varying size, DNA origami rings and pore forming proteins were identified and accurately traced with contour lengths of traces typically within 10 nm of the predicted contour length. TopoStats was also able to reliably identify and trace linear and enclosed circular molecules within a mixed population. The program is freely available via GitHub (https://github.com/afm-spm/TopoStats) and is intended to be modified and adapted for use if required.

biophysics↗

bioRxiv2020

Combining Information from Crosslinks and Monolinks in the Modelling of Protein Structures

Monolinks are produced in a Chemical Crosslinking Mass Spectrometry experiment and are more abundant than crosslinks. They convey residue exposure information, but so far have not been used in the modelling of protein structures. Here we present the Monolink Depth Score (MoDS), for assessing structural models based on the depth of monolinked residues, corresponding to their distance to the nearest bulk water. Using simulated and reprocessed experimental data from the Proteomic Identification Database, we compare the performance of MoDS to MNXL - our previously-developed score for assessing models based on crosslinking data. Our results show that MoDS can be used to effectively score model structures based on monolinks, and that combining it with MNXL leads to overall higher scoring performance. The work strongly supports the use of monolink data in the context of integrative structure determination. We also present XLM-Tools, a programme to assist in this effort, available at: https://github.com/Topf-Lab/XLM-Tools.

bioinformatics↗