What do we do?
At the Computational Structural Biology (CSB) Group we are focusing on the development of methods and algorithms to model, simulate and analyse three-dimensional protein structures and their molecular properties in order to apply these techniques to understanding biological processes at a molecular level. Our main emphasis is on homology modelling approaches – using evolutionary information to model protein tertiary and quaternary structures. Applications in biomedical research include the study of protein-ligand interactions from different perspectives, such as the identification of small antiviral molecules to support drug development, the structure-guided engineering of enzymes or the interpretation of disease causing mutations in proteins.
In 2016 we released a new re-engineered SWISS-MODEL Repository, which integrates the latest developments in the SWISS-MODEL pipeline and features a newly designed graphical interface. Proteins of model organisms are modeled on a weekly basis. Users of the Repository can also trigger an almost instantaneous update of a given entry if no models are available for a specific UniProt sequence.
According to the magazine “Horizonte” (March 2016) of the SNF Swiss National Science Foundation, our 2014 publication describing the developments of the SWISS-MODEL expert system was ranked as the 6th highest impact scientific publications published in Switzerland in 2014/2015.
Our group participated in the TecDays at the Gymnasium Stadelhofen in Zürich and at the Liceo Cantonale in Bellinzona with a module about Structural Bioinformatics. This event is organized by the Swiss Academy of Engineering Sciences to promote the study of technical and natural sciences among students of Swiss schools.
Main publications 2016
- Bienert S et al. The SWISS-MODEL Repository-new features and functionality. Nucleic acids research 2016;Epub ahead of print:gkw1132.
- Moult J, Fidelis K, Kryshtafovych A, Schwede T, Tramontano A. Critical assessment of methods of protein structure prediction: Progress and new directions in round XI. Proteins 2016;84 Suppl 1:4-14.
- Kryshtafovych A, Barbato A, Monastyrskyy B, Fidelis K, Schwede T, Tramontano A. Methods of model accuracy estimation can help selecting the best models from decoy sets: Assessment of model accuracy estimations in CASP11. Proteins 2016; 84 Suppl 1:349-69.