Charles University Structural Bioinformatics Group

An interdisciplinary research group between the Faculty of Mathematics and Physics and Faculty of Science of the Charles University in Prague


Our group is formed by researchers from the Faculty of Mathematics and Physics and Faculty of Science of the Charles University. Being at the interface of biology and computer science allows us to efficiently combine the expertise of our respective research fields in order to understand cellular processes on the molecular level and to develop biologicaly-plausible, high-quality software solutions.

The main focus of our group is in the following areas:

  • Understanding mechanisms of cellular processes using 3D structure information
  • Predictive modeling focused on the detection of macromolecular interaction sites such as protein-ligand, protein-protein, protein-dna or phosphorylation sites.
  • 3D structure prediction
  • Visualization of macromolecular structures



P2Rank is a state-of-the-art machine learning-based method for ligand binding sites prediction based on protein structure.


MolArt is a responsive, easy-to-use JavaScript plugin which enables users to view annotated protein sequence and overlay the annotations over a corresponding experimental or predicted protein structure.


Traveler is an RNA sescondary structure visualization tool implementing a template-based approach enabling to lay out even the largest RNA structures in the standard orientation.


AHoJ (Apo-Holo Juxtaposition) is a webserver and a command-line tool for search of Apo (unbound) protein structures from Holo (bound) forms and vice versa.


INSPiRE is a state-of-the-art knowledge-based protein-protein INteraction Sites PREdictor.


SETTER (SEcondary sTructure-based TERtiary Structure Similarity Algorithm) is a set of tools for fast pairwise and multiple RNA 3D structure superposition.


Molpher (Molecular morphing) aims to be scalable interactive software framework to aid the exploration of the chemical space.


Main publications of our group. Go here and here to see the full list.


Current members of CUSBG

Marian Novotný

Faculty of Science, Assistant Professor

Marian is the head of the biology branch of the group. Marian is interested in using 3D structural information to understand cellular processes and their evolution. Marian was involved in a 3D structural prediction, a development of methods for structure validation (accessible surface area-calculation precision) and a development of methods for structure-based function prediction (left-handed helices) .

David Hoksza

Faculty of Mathematics and Physics, Associate Professor

David is the head of the computer science branch of the group. He is interested in the development of efficient algorithms in the area of structural bioinformatics and data visualization. He has been involved in projects dealing mostly with protein and RNA structure with occasional excursions to the fields of cheminformatics (ligand-based virtual screening, exploration of chemical space), computational genomics (analysis of MinION data) and systems biology (visualization and analysis of molecular networks).

Petr Škoda

Faculty of Mathematics and Physics, Assistant Professor

Petr, an assistant professor at Charles University, is a researcher and a developer. He focuses mainly on fields of similarity modelling, ligand-based virtual screening, data transformation, and linked data. Petr is an open-source contributor to projects such as LinkedPipes ETL, DCAT-AP Viewer, and p2rank web interface.

Andrea Šoltésová

Faculty of Mathematics and Physics, Postdoc

Andrea is a postdoctoral researcher in the computer science branch of the group. Main expertise of Andrea Šoltésová lies in the field of computational biology, machine learning and data mining in general. Her main research area is in structural bioinformatics. Her research interest focuses on predictive modelling of protein-DNA interaction through machine learning.

Radoslav Krivák

Faculty of Mathematics and Physics, PhD student

Radoslav has a background in theoretical computer science and machine learning. His research interests include applying machine learning to analyze and map protein surfaces and exploring protein and chemical structural spaces. Radoslav is the main author of P2Rank, ligand-binding site prediction software.

Christos Feidakis

Faculty of Science, PhD student

Using informatics in order to make sense out of biological data, specifically structure-related data and processes, such as the interactions of proteins with other proteins and smaller molecules.
Interests: Structural bioinformatics, comparative modeling, evolution, in-silico drug design, Python

Jan Jelínek

Faculty of Mathematics and Physics, PhD student

Jan is a PhD. student in the computer science branch of the group. He focuses on machine learning and structural bioinformatics. His main research area is a protein structure prediction, however he is also involved in a projects dealing with protein structure identification using mass spectroscopy, RNA structure prediction, and statistical analysis of Ribo-Seq data.

Hamza Gamouh

Faculty of Mathematics and Physics, PhD student

A PhD student in computer science with a background in artificial intelligence and machine learning. Main focus is on the applying machine learning for detecting protein interaction sites. Main research areas include protein-ligand binding sites prediction, cryptic binding sites, protein-protein interaction sites and protein function prediction.


Dávid Jakubec

Faculty of Mathematics and Physics, Postdoc

David is a postdoctoral researcher in the computer science branch of the group. His main expertise lies in molecular modelling and computational chemistry, with additional background in molecular biology and biochemistry. David is primarily interested in the nature of forces driving molecular interactions and recognition. He is further interested in molecular evolution and has been developing tools for its computational study.


Opened positions in our group

Charles University Structural Bioinformatics Group is looking for a candidate to help maintain and advance software tools developed in the group and extend the portfolio of existing analytics approaches and software tools

The role will require the candidate to carry out maintenance tasks of existing tools along with maintaining data workflows for sharing our data with partner institutions such as PDBe-KB or RNAcentral.

To advance the tools and methods, the group is oriented towards developing approaches utilizing advanced machine learning (ML) approaches such as language models, CNNs, graph neural networks, vision transformers, and the like. The candidate is expected to have a working knowledge of ML and willingness to familiarize themself with the newest advances in ML, as well as the most recent development in structural molecular biology.

Although this is primarily a research position, in the longer run, it might include minor teaching duties.

  • Maintenance and further development of existing software tools
  • Supporting research partners and students utilizing the tools
  • Coming up with novel ideas regarding the orientation of further research/development
  • Ms.C. or Ph.D. in bioinformatics, computer science, machine learning, or a related quantitative field
  • Strong interest in algorithms, machine learning, and data science/processing
  • Strong algorithmic and programming skills (familiarity with languages such as C++ and/or Java and scripting languages such as Python)
  • Knowledge of working in UNIX/Linux environment
  • Basic functional knowledge of statistics
  • Ability to work independently and to organise own workload
  • Fluency in written and spoken English
  • Knowledge of web-based programming
  • Basic knowledge of molecular biology
  • Experience with structural bioinformatics
  • Knowledge of software development principles and tools such as source control/versioning systems, continuous integration and development, software/unit testing
We offer
  • A one-year contract renewable based on performance
  • Flexible working time
  • A pleasant working environment in the Prague city center
  • Please send a CV and a motivation letter in English or Czech by email to Dr. David Hoksza (
  • Start date: April 2023 or later (negotiable). The position is opene until a suitable candidate is found.
  • Position opened until a suitable candidate is found

If you are interested in pursuing PhD in the area of structural bioinformatics, visualization of molecular data, integration of bioinformatics data, or a related field, get in touch with us and we can discuss how to align your ideas and interests with our preferences.

Contact Us

Lab at the Faculty of Mathematics and Physics

Malostranské nám. 25
118 00 Prague
Czech Republic

+420 95155 4406

Lab at the Faculty of Science

Albertov 6
128 00 Prague
Czech Republic

+420 22195 1076