| Torsten Schwede | |
| Birth Date: | 2 October 1967 |
| Birth Place: | Coburg, Germany |
| Nationality: | Swiss, German |
| Field: | Bioinformatics |
| Work Institutions: | University of Bayreuth, University of Freiburg, Swiss Institute of Bioinformatics, Biozentrum University of Basel |
Torsten Schwede (born 2 October 1967 in Coburg) is a German and Swiss bioinformatics scientist and Professor at the Biozentrum of the University of Basel, Switzerland.[1] He is also Vice Rector for Research at the University of Basel.[2]
Torsten Schwede studied biochemistry at the University of Bayreuth and the University of Freiburg in Germany. After completing his PhD in 1998 he worked in research at the global pharmaceutical company GlaxoSmithKline in Geneva. In 2001, Torsten Schwede was appointed as Assistant Professor of Structural Bioinformatics to the Biozentrum, university of Basel. The following year he also became a group leader at the SIB Swiss Institute of Bioinformatics. In 2007 the bioinformatician became Associate Professor and 2018 Full Professor for Structural Bioinformatics at the Biozentrum. From 2014 to 2019 he was scientific director of sciCORE, responsible for the central infrastructure for scientific computing at the University of Basel.[3] In 2018, Torsten Schwede was appointed Vice Rector for Research at the University of Basel.
Torsten Schwede develops methods[4] [5] and algorithms to model the three-dimensional structures of proteins and their properties, in order to gain knowledge about their function at an atomic level. The main focus of his work is on methods for homology modeling,[6] [7] which allow the structure of proteins to be modeled using structures of experimentally characterized structures of homologues proteins as templates. Torsten Schwede has developed Swiss-model, a fully automated web server for modeling of protein structures which allows the prediction of protein structures based on experimentally characterized structures of homologues proteins. In order to estimate the accuracy of predicted structures, his group developed the QMEAN[8] method for models of soluble and membrane proteins.[9] He has initiated the CAMEO project for the continuous automated blind assessment of structure prediction techniques, which complements the activities of the biannual CASP experiment.
In addition to the prediction of protein structures, his group is working on modeling protein-ligand interactions. Using in-silico screening, they have been able to identify new potential inhibitors against the dengue virus. Through X-ray crystallography of the enzyme histidine ammonia-lyase (histidase). Torsten Schwede elucidated a novel electrophilic co-factor in enzymes, which is formed by the autocatalytic modification of the protein backbone.[10]