COVID-19 Measures

All CIISB Core facilities are fully functional. Visits of external foreign users are regulated by the Measures concerning foreigners and border crossing of the Czech Government. Please, check the current status on the web and contact the staff for details.

CIISB offers priority access to groups that need to use CIISB structural biology services for projects directly related to studies of the virus and projects aiming to develop an effective vaccine or treatment. To request priority access, please submit a research proposal with „COVID-19“ in the title of the proposal, through the online application system HERE. Successfully accepted proposals will be free of charge, and no financial contribution will be requested for the measurement/service.

Czech National Centre of the European Research Infrastructure Consortium INSTRUCT ERIC

CIISB video presentation

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.

Highlights of Coronavirus Structural Studies

Coronavirus Archive

Research Highlights

the best of science obtained using CIISB Core Facilities

Nature Communications 2021

Structural characterization of the PSMA/Glu-490 complex

a Molecular formula of the Glu-490. b A stereo view of the Gluo-490 inhibitor. The Fo-Fc omit map (green) is contoured at 3.0 σ and the inhibitor is shown in stick representation with atoms colored red (oxygen), blue (nitrogen), yellow (sulfur), and cyan (carbon). c Details of interactions between residues of the glutarate sensor (green carbons) and Glu-490 (cyan carbons). CH–π interactions are depicted as dashed lines with distances to the ring centers in Angstroms. The active-site zinc ions are shown as orange spheres. d Surface representation of PSMA with residues of the glutarate sensor interaction with the FMR moiety colored blue, PDB code (7BFZ).

Yiguang Wang, Cyril Bařinka & Xing Yang Research Groups


Surgery is an efficient way to treat localized prostate cancer (PCa), however, it is challenging to demarcate rapidly and accurately the tumor boundary intraoperatively, as existing tumor detection methods are seldom performed in real-time. To overcome those limitations, we develop a fluorescent molecular rotor that specifically targets the prostate-specific membrane antigen (PSMA), an established marker for PCa. The probes have picomolar affinity (IC50 = 63-118 pM) for PSMA and generate virtually instantaneous onset of robust fluorescent signal proportional to the concentration of the PSMA-probe complex. In vitro and ex vivo experiments using PCa cell lines and clinical samples, respectively, indicate the utility of the probe for biomedical applications, including real-time monitoring of endocytosis and tumor staging. Experiments performed in a PCa xenograft model reveal suitability of the probe for imaging applications in vivo.


Zhang, J., … Wang, Y., Bařinka, C. & Yang, X.: A prostate-specific membrane antigen activated molecular rotor for real-time fluorescence imaging,  Nature Comm. (2021)12:5460,

Nature Chemical Biology 2021

Overall architecture of the giant E3 ligase HUWE1N.

a, Domain architecture of HUWE1N. ARM repeats 1–34 are numbered, with the four insertions indicated. The positions of human HUWE1 insertions, absent in HUWE1N, are shown in brackets. b, Crystal structure of HUWE1Nc, Crystal structure of HUWE1N shown in cartoon representation from four different views, using the same color coding as in a (catalytic Cys in red). A schematic cartoon illustrates the snake-like organization of the E3 ligase. d, Negative-stain EM analysis of CeHUWE1. The obtained EM density is shown from two viewpoints, with approximate dimensions indicated. e, Organization and increasing complexity of HUWE1.

Tim Clausen Research Group


HUWE1 is a universal quality-control E3 ligase that marks diverse client proteins for proteasomal degradation. Although the giant HECT enzyme is an essential component of the ubiquitin–proteasome system closely linked with severe human diseases, its molecular mechanism is little understood. Here, we present the crystal structure of NematocidaHUWE1, revealing how a single E3 enzyme has specificity for a multitude of unrelated substrates. The protein adopts a remarkable snake-like structure, where the C-terminal HECT domain heads an extended alpha-solenoid body that coils in on itself and houses various protein–protein interaction modules. Our integrative structural analysis shows that this ring structure is highly dynamic, enabling the flexible HECT domain to reach protein targets presented by the various acceptor sites. Together, our data demonstrate how HUWE1 is regulated by its unique structure, adapting a promiscuous E3 ligase to selectively target unassembled orphan proteins.

Grabarczyk, D.B., Petrova,O.A., Deszcz, L., Kurzbauer, R., Murphy, P., Ahel, J., Vogel, A., Gogova, R., Faas, V., Kordic, D., Schleiffer, A., Meinhart, A:, Imre, R., Lehner, A., Neuhold, J., Bader, G., Stolt-Bergner, P., Böttcher, J., Wolkerstorfer, B., Fischer, G.,  Grishkovskaya, I., Haselbach, D., Kessler,D., and Clausen T.: HUWE1 employs a giant substrate-binding ring to feed and regulate its HECT E3 domain, Nat. Chem. Biol. (2021)

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 The section is being updated regularly.


20 Aug

Highly accurate protein structure prediction with AlphaFold (Nature)

Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort, the structures of around 100,000 unique proteins have been determined, but this represents a small fraction of the billions of known protein sequences. Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’—has been an important open research problem for more than 50 years. Despite recent progress, existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here, John Jumper, Richard Evans, Demis Hassabis et. al.provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. They validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14), demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm.

Reader’s Corner Archive

Quote of October

“We are an impossibility in an impossible universe.”

Ray Bradbury

You are running an old browser version. We recommend updating your browser to its latest version.