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Czech National Centre of the European Research Infrastructure Consortium INSTRUCT ERIC

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The structural biology of today is the pharmacology, therapy, and biotechnology of tomorrow

A gateway to realm of structural data for biochemists, biophysicists, molecular biologist, and all scientists whose research benefits from accurate structure determination of biological macromolecules, assemblies, and complex molecular machineries at atomic resolution.

Open access to 10 high-end core facilities and assisted expertise in NMR, X-ray crystallography and crystallization, cryo-electron microscopy and tomography, biophysical characterization of biomolecular interaction, nanobiotechnology, proteomics and structural mass spectrometry.

A distributed infrastructure constituted by Core Facilities of CEITEC (Central European Institute of Technology), located in Brno, and BIOCEV (Biotechnology and Biomedicine Centre), located in Vestec near Prague, Central Bohemia.

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News

16 Apr

Open position Junior/medior backend developer in data management (IBT Biocev)

The Institute of Biotechnology of the Academy of Sciences of the Czech Republic at the Biotechnology and Biomedicine Centre of the Academy of Sciences and Charles University in Vestec announces an open position:

Junior/medior backend developer in data management

We are looking for an enthusiast to join our team focused on management of biophysical data within the European project MOSBRI and the National Repository Platform.

We offer work connected to development of data management infrastructure for biophysical data in the frame of an international project at the Institute of Biotechnology in the BIOCEV Centre of Excellence.

31 Mar

New instrumentation in Proteomics core facility

In March, two new high resolution mass spectrometers were installed in our core facility thanks to CIISB project (CZ.02.01.01/00/23_015/0008175). First we upgraded our timsTOF Pro 2 instrument to timsTOF HT improving our performance in whole proteome analyses with faster scanning speed and a wider dynamic range. In second, Ultra 2 mass spectrometer was installed. This timsTOF instrument opens doors to deeper analysis of samples with limited amount of input material due to its ultimate sensitivity.

News archive

CIISB Research Results

Y. Luo, et al.: A sodium/potassium switch for G4-prone G/C-rich sequences, Nucleic Acids Res., 52 (2024) 448-461, 10.1093/nar/gkad1073

M. Soltysová, et al.: Structural characterization of two prototypical repressors of SorC family reveals tetrameric assemblies on DNA and mechanism of function, Nucleic Acids Res., 52 (2024) 7305-7320, 10.1093/nar/gkae434

D. Jankovská, et al.: Anticholinesterase Activity of Methanolic Extract of Amorpha fruticosa Flowers and Isolation of Rotenoids and Putrescine and Spermidine Derivatives, Plants-Basel, 13 (2024) 10, 10.3390/plants13091181

M. Anastasina, et al.: The structure of immature tick-borne encephalitis virus supports the collapse model of flavivirus maturation, Sci. Adv., 10 (2024) 13, 10.1126/sciadv.adl1888

P. Lapcik, et al.: A hybrid DDA/DIA-PASEF based assay library for a deep proteotyping of triple-negative breast cancer, Sci. Data, 11 (2024) 7, 10.1038/s41597-024-03632-2

N. Kunová, et al.: Polyphosphate and tyrosine phosphorylation in the N-terminal domain of the human mitochondrial Lon protease disrupts its functions, Sci Rep, 14 (2024) 17, 10.1038/s41598-024-60030-9

J. Sistkova, et al.: Insight into antibacterial effect of titanium nanotubular surfaces with focus on Staphylococcus aureus and Pseudomonas aeruginosa, Sci Rep, 14 (2024) 20, 10.1038/s41598-024-68266-1

F. Niro, et al.: Fibrotic extracellular matrix impacts cardiomyocyte phenotype and function in an iPSC-derived isogenic model of cardiac fibrosis, Transl. Res., 273 (2024) 58-77, 10.1016/j.trsl.2024.07.003

More publications

Events

Event calendar

CIISB Research Highlights

the best of science obtained using CIISB Core Facilities

  • Nature Communications 2025

    Nature Communications 2025

    Lumír Krejčí Research Group

    RECQ4 cooperates with MUS81 to prevent ultrafine bridges formation.

    Significance

    Replication stress, particularly in hard-to-replicate regions such as telomeres and centromeres, leads to the accumulation of replication intermediates that must be processed to ensure proper chromosome segregation. In this study, we identify a critical role for the interaction between RECQ4 and MUS81 in managing such stress. We show that RECQ4 physically interacts with MUS81, targeting it to specific DNA substrates and enhancing its endonuclease activity. Loss of this interaction, results in significant chromosomal segregation defects, including the accumulation of micronuclei, anaphase bridges, and ultrafine bridges (UFBs). Our data further demonstrate that the RECQ4-MUS81 interaction plays an important role in ALT-positive cells, where MUS81 foci primarily colocalise with telomeres, highlighting its role in telomere maintenance. We also observe that a mutation associated with Rothmund-Thomson syndrome, which produces a truncated RECQ4 unable to interact with MUS81, recapitulates these chromosome instability phenotypes. This underscores the importance of RECQ4-MUS81 in safeguarding genome integrity and suggests potential implications for human disease. Our findings demonstrate the RECQ4-MUS81 interaction as a key mechanism in alleviating replication stress at hard-to-replicate regions and highlight its relevance in pathological conditions such as RTS.

    Ashraf, et al.: RECQ4-MUS81 interaction contributes to telomere maintenance with implications to Rothmund-Thomson syndrome

    Nature Communications 2025, 10.1038/s41467-025-56518-1

  • JACS Au 2025

    JACS Au 2025

    Loschmidt Laboratories

    The scheme of the variational autoencoder-based pipeline for the design of novel sequences.

    Significance

    Enzymes play a crucial role in sustainable industrial applications, with their optimization posing a formidable challenge due to the intricate interplay among residues. Computational methodologies predominantly rely on evolutionary insights of homologous sequences. However, deciphering the evolutionary variability and complex dependencies among residues presents substantial hurdles. Here, we present a new machine-learning method based on variational autoencoders and evolutionary sampling strategy to address those limitations. We customized our method to generate novel sequences of model enzymes, haloalkane dehalogenases. Three design–build–test cycles improved the solubility of variants from 11% to 75%. Thorough experimental validation including the microfluidic device MicroPEX resulted in 20 multiple-point variants. Nine of them, sharing as little as 67% sequence similarity with the template, showed a melting temperature increase of up to 9 °C and an average improvement of 3 °C. The most stable variant demonstrated a 3.5-fold increase in activity compared to the template. High-quality experimental data collected with 20 variants represent a valuable data set for the critical validation of novel protein design approaches. Python scripts, jupyter notebooks, and data sets are available on GitHub (https://github.com/loschmidt/vae-dehalogenases), and interactive calculations will be possible via https://loschmidt.chemi.muni.cz/fireprotasr/.

    Kohout, et al.: Engineering Dehalogenase Enzymes Using Variational Autoencoder-Generated Latent Spaces and Microfluidics

    JACS Au 2025, 5(2), 10.1021/jacsau.4c01101

  • The FEBS Journal 2025

    The FEBS Journal 2025

    Lukáš Žídek Research Group

    Electrostatic potential of unphosphorylated and phosphorylated MAP2c.

    Significance

    Microtubule associated protein 2 (MAP2) interacts with the regulatory protein 14-3-3ζ in a cAMP-dependent protein kinase (PKA) phosphorylation dependent manner. Using selective phosphorylation, calorimetry, nuclear magnetic resonance, chemical crosslinking, and X-ray crystallography, we characterized interactions of 14-3-3ζ with various binding regions of MAP2c. Although PKA phosphorylation increases the affinity of MAP2c for 14-3-3ζ in the proline rich region and C-terminal domain, unphosphorylated MAP2c also binds the dimeric 14-3-3ζ via its microtubule binding domain and variable central domain. Monomerization of 14-3-3ζ leads to the loss of affinity for the unphosphorylated residues. In neuroblastoma cell extract, MAP2c is heavily phosphorylated by PKA and the proline kinase ERK2. Although 14-3-3ζ dimer or monomer do not interact with the residues phosphorylated by ERK2, ERK2 phosphorylation of MAP2c in the C-terminal domain reduces the binding of MAP2c to both oligomeric variants of 14-3-3ζ.

    Jansen, et al.: Characterization of multiple binding sites on microtubule associated protein 2c recognized by dimeric and monomeric 14‐3‐3ζ

    The FEBS Journal, DOI: 10.1111/febs.17405

More publications Research Highlights archive

Reader’s Corner

literature to read, science to follow

In this section, a distinct selection of six highly stimulating research publications and reviews published during past 6 months is presented. It is our hope that links to exciting science, which deserves attention of the structural biology community, will help you to locate gems in the steadily expanding jungle of scientific literature. You are welcome to point out to any paper you found interesting by sending a link or citation to readerscorner@ciisb.org. The section is being updated regularly.

 

2 Jan

CLEM-Reg: An automated point cloud based registration algorithm for correlative light and volume electron microscopy

Correlative light and volume electron microscopy (vCLEM) is a powerful imaging technique that enables the visualisation of fluorescently labelled proteins within their ultrastructural context on a subcellular level. Currently, expert microscopists align vCLEM acquisitions using time-consuming and subjective manual methods. This paper presents CLEM-Reg, an algorithm that automates the 3D alignment of vCLEM datasets by leveraging probabilistic point cloud registration techniques. These point clouds are derived from segmentations of common structures in each modality, created by state-of-the-art open-source methods, with the option to leverage alternative tools from other plugins or platforms. CLEM-Reg drastically reduces the time required to register vCLEM datasets to a few minutes and achieves correlation of fluorescent signal to sub-micron target structures in EM on three newly acquired vCLEM benchmark datasets (fluorescence microscopy combined with FIB-SEM or SBF-SEM). CLEM-Reg was then used to automatically obtain vCLEM overlays to unambiguously identify TGN46-positive transport carriers involved in the trafficking of proteins between the trans-Golgi network and plasma membrane. The datasets are available in the EMPIAR and BioStudies public image archives for reuse in testing and developing multimodal registration algorithms by the wider community. A napari plugin integrating the algorithm is also provided to aid end-user adoption. DOI: 10.1101/2023.05.11.540445

2 Jan

Boltz-1: Democratizing Biomolecular Interaction Modeling

Understanding biomolecular interactions is fundamental to advancing fields like drug discovery and protein design. In this paper, we introduce Boltz-1, an open-source deep learning model incorporating innovations in model architecture, speed optimization, and data processing achieving AlphaFold3-level accuracy in predicting the 3D structures of biomolecular complexes. Boltz-1 demonstrates a performance on-par with state-of-the-art commercial models on a range of diverse benchmarks, setting a new benchmark for commercially accessible tools in structural biology. By releasing the training and inference code, model weights, datasets, and benchmarks under the MIT open license, we aim to foster global collaboration, accelerate discoveries, and provide a robust platform for advancing biomolecular modeling. DOI: 10.1101/2024.11.19.624167

2 Jan

Fast protein structure searching using structure graph embeddings

Comparing and searching protein structures independent of primary sequence has proved useful for remote homology detection, function annotation and protein classification. Fast and accurate methods to search with structures will be essential to make use of the vast databases that have recently become available, in the same way that fast protein sequence searching underpins much of bioinformatics. We train a simple graph neural network using supervised contrastive learning to learn a low-dimensional embedding of protein structure. The method, called Progres, is available as software at https://github.com/greener-group/progres and as a web server at https://progres.mrc-lmb.cam.ac.uk. It has accuracy comparable to the best current methods and can search the AlphaFold database TED domains in a tenth of a second per query on CPU. DOI: 10.1101/2022.11.28.518224​

26 Nov 2024

Structural ubiquitin contributes to K48 linkage-specificity of the HECT ligase Tom1

Homologous to E6AP C-Terminus (HECT) ubiquitin ligases play key roles in essential pathways such as DNA repair, cell cycle control or protein quality control. Tom1 is one of five HECT ubiquitin E3 ligases encoded in the S. cerevisiae genome and prototypical for a ligase with pleiotropic functions such as ubiquitin chain amplification, orphan quality control and DNA damage response. Structures of full-length HECT ligases, including the Tom1 ortholog HUWE1, have been reported, but how domains beyond the conserved catalytic module contribute to catalysis remains largely elusive. Here, through cryogenic electron microscopy (cryo-EM) of Tom1 during an active ubiquitylation cycle, we demonstrate that the extended domain architecture directly contributes to activity. We identify a Tom1-ubiquitin architecture during ubiquitylation involving a non-canonical ubiquitin binding site in the solenoid shape of Tom1. We demonstrate that this ubiquitin binding site coordinates a structural ubiquitin contributing to the fidelity of K48 poly-ubiquitin chain assembly.​

26 Nov 2024

Large-Scale Quantitative Cross-Linking and Mass Spectrometry Provides New Insight on Protein Conformational Plasticity within Organelles, Cells, and Tissues (Biorxiv)

Many proteins can exist in multiple conformational states in vivo to achieve distinct functional roles. These states include alternative conformations, variable PTMs, and association with interacting protein, nucleotide, and ligand partners. Quantitative chemical cross-linking of live cells, organelles, or tissues together with mass spectrometry provides the relative abundance of cross-link levels formed in two or more compared samples, which depends both on the relative levels of existent protein conformational states in the compared samples as well as the relative likelihood of the cross-link originating from each. Because cross-link conformational state preferences can vary widely, one expects intra-protein cross-link levels from proteins with high conformational plasticity to display divergent quantitation among samples with differing conformational ensembles. Here we use the large volume of quantitative cross-linking data available on the public XLinkDB database to cluster intra-protein cross-links according to their quantitation in many diverse compared samples to provide the first widescale glimpse of cross-links grouped according to the protein conformational state(s) from which they predominantly originate. We further demonstrate how cluster cross-links can be aligned with any protein structure to assess the likelihood that they were derived from it.​

25 Nov 2024

Improved automated model building for cryo-EM maps using CryFold (Biorxiv)

Constructing atomic models from cryogenic electron microscopy (cryo-EM) density maps is essential for interpreting molecular mechanisms. In this study, we present CryFold, an approach for de novo model building in cryo-EM that leverages recent advancements in AlphaFold2 to improve the state-of-the-art method ModelAngelo. To incorporate the cryo-EM map information, CryFold replaces the global attention mechanism in AlphaFold2 to local attention, further enhanced by a novel 3D rotary position embedding. It produces more complete models, accelerates the modeling, and reduces the resolution requirement. Applying CryFold to new maps results in accurate differentiation between paralog sequences in noisy regions, detection of previously uncharacterized proteins with unknown functions, precise compartmentalisation of the map for isolation of non-protein components, and improved modeling of conformational changes. In a particular case, a 104-protein complex was modeled within only 5.6 hours, and a minor conformational change of a single protein domain was detected at the periphery when models from two different maps were compared. CryFold stands as an accurate method currently available for model building of proteins in cryo-EM structure determination. CryFold is open-source software available at https://github.com/SBQ-1999/CryFold.​

Reader’s Corner Archive

Quote of May

“The virtues of science are skepticism and independence of thought.”

Walter Gilbert

Partner webs

https://ec.europa.eu/info/research-and-innovation/research-area/health-research-and-innovation/coronavirus-research-and-innovation/covid-research-manifesto_en

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