Laboratory of Structural Biology and Cell Signaling

2021/01/08:
Collaboration with the Ludwig lab resulted in another paper on wood degrading enzymes. This time about chimeric CDHs in ACS Catalysis.
2020/12/18:
Paper on TEAD1-DNA interaction is now published in Structure. Enjoy 50 days of free access (till Feb 4, 2021).
2020/12/14:
Congratulations to Paja, now officially PhD in biochemistry!
2020/12/11:
Our HDX workflow combined with Ruza's experience on protein-DNA interaction studies was compiled into Methods Mol. Biol. chapter that has just been published.
2020/11/20:
Two new papers employing MALDI biotyping of sand flies are now in Parasit. Vectors. Collaboration of Petr with the Volf's lab.
2020/10/19:
Pleasant colaboration with Haitin Lab on cis-prenyltrasferase made it from BioRXiv to Nature Communications!. Thanks EU_FT-ICR_MS H2020 Project for support!

2020/11/17:
Call for EPIC-XS proposals is open till December 31, 2020. Next round will be till Mar 31, 2021! Submit via the online submission system.
2020/07/15:
Visitors coming to our lab from abroad should consult the web page of the Czech Ministry of Health regarding COVID-19 related travel restrictions.
2020/06/02:
We are looking for post-doc and PhD to join our team and work on various projects using structural mass spectrometry! Inquiries should be addressed to Petr Novak.
2019/03/27:
We are part of another Horizon 2020 project EPIC-XS (reg. no 823839) focused on the cutting edge proteomic techniques. This project provides Trans-National Access and also focuses on the development of the techniques.
2018/01/03:
Our lab is a part of Horizon 2020 project EU FT-ICR MS (reg. no 731077). Through this project you can access our expertise as well as other participating FT-ICR labs. Check Trans-National Acess web section for more details. Also, various FT-ICR focused courses and schools are organized by the labs participating in the project.
2017/12/20:
Bachelor and master theses are available in the lab. Areas of structrual biology, cutting edge mass spectrometry and cell signalling are awaiting new students. Check the tab Teaching.

Downloads

Software for interpretation of high-resolution MS data obtained after protein chemical cross-linking. The software is free to use. If you are using LinX for your research please cite the related publication.

Download here

This software is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 731077P.

DeutEx - Software for interpretation of HDX-MS data will be available here.

The software is free to use, however is distributed upon signing of Software Transfer Agreement. The download is password protected. For access please contact Petr Man. If you are using these tools for your research please consider to cite our work.

Other HDX-MS related tools for data processing and visualization are below.

Digestion_metrics - Microsoft Excel macro calculating simple digestion metrics (coverage, average peptide length, redundancy, etc.) Modified supplementary file to publication Kadek A et al Anal Chem. 2014, 86(9):4287-94.
HDXPeptideSplitter - Python script for preporcesing of HDX-MS results before using them in PyMol. Processed data are then used by data2bfactor Pymol script written by Robert L. Campbell. This version works with Python version 2.x. For version 3.x and higher use this modified data2bfactor script.

An integrated computational platform for biomolecular language processing

MatrixMotif, our novel hybrid algorithm for biomolecular language processing has been successfully applied during mining of hidden TFBS motifs from enriched NGS datasets. We primarily stacked on Hypergeometric Distribution Model allowing pseudo-random estimation of DNA motif seeds which are subsequently marginalized through eigenvalue of the Markov chain transition matrix. To get rid of local optima in our constraints we were iterating our motifs using property of Maximum Entropy to maximize our expectation. The maximum free motifs are then re-estimated using hidden Markov matrix and the SuperBinder motif is selected according its maximum log-likelihood score. Now we are hoping in the Docker daemon to come with MatrixMotif container as soon as possible. MatrixMotif chomps all models through SciPy and CRAN ecosystems under UNIX-like systems.
Individual R packages can be downloaded via the CRAN network (mHG, mHMMbayes, DCAM, IMMIGRATE, modeLLtest).

The software is free to use, final integrated package is under construction. In you need any assistance or more information please contact Karel Valis.