Forschungsgruppe Torsten Schwede
Computational structure biology
Protein structure modeling and evaluation
The main interest of my group is the development of methods and algorithms for molecular modeling and simulations of three-dimensional protein structures and their interactions. One of the major limitations for using structure-based methods in biomedical research is the limited availability of experimentally determined protein structures. Prediction of the 3D structure of a protein from its amino acid sequence remains a fundamental scientific problem, and it is considered as one of the grand challenges in computational biology. Comparative or homology modeling, which uses experimentally elucidated structures of related protein family members as templates, is currently the most accurate approach to model the structure of the protein of interest. Template-based protein modeling techniques exploit the evolutionary relationship between a target protein and templates with known experimental structures, based on the observation that evolutionarily related sequences generally have similar 3D structures. The SWISS-MODEL expert system developed by our group is a fully automated web-based workbench, which greatly facilitates the process of computing of protein structure homology models.
Estimating the expected quality of predicted structural models is a vital step in homology modeling. Especially when the sequence identity between target and template is low, individual models may contain considerable errors. To identify such inaccuracies, scoring functions have been developed which analyze different structural features of the protein models in order to derive a quality estimate. To this end, we have introduced the composite scoring function QMEAN, which consists of four statistical potential terms and two components describing the agreement between predicted and observed secondary structure and solvent accessibility. We have shown that QMEAN can not only be used to assess the quality of theoretical protein models, but also to identify experimental structures of poor quality. Ultimately, the quality of a model determines its usefulness for different biomedical applications such as planning mutagenesis experiments for functional analysis, or studying protein-ligand interactions, e.g. for structure based drug design. In the following, three exemplar projects involving molecular modeling of protein-ligand interactions at different levels of model resolution are briefly presented.
Molecular modeling of protein-ligand interactions
Dengue fever is a viral disease that is transmitted between human hosts by Aedes mosquitoes, particularly Aedes aegyptii. In 1997, 20 million cases of dengue fever were estimated to occur annually. Partially because of increased urbanization and failure to effectively control the spread of the insect vector, more recent estimates suggest this number has risen to 50 –100 million, and dengue fever is now seen as one of the most important emerging infectious diseases in many areas of the world. We have used a structure based virtual screening approach to identify novel inhibitors of Dengue virus RNA methyltransferase (MTase), which is necessary for virus replication. In a multistage molecular docking approach in the MTase crystal structure, we screened a library of more than 5 million commercially available compounds against the two binding sites of this enzyme. In 263 compounds selected for experimental verification at the Novartis Institute for Tropical Diseases in Singapore, 10 inhibitors with IC50 values of <100 μM were identified, of which four exhibited IC50 values of <10 μM in in vitro assays.
Olfaction refers to the sense of smell which is mediated by specialized sensory cells in the nasal cavity of vertebrates and in the antennae of invertebrates. Activated olfactory receptors are the initial player in a signal transduction cascade which ultimately produces a nerve impulse which is transmitted to the brain. These receptors are members of the class A rhodopsin-like family of G protein-coupled receptors (GPCRs), which can detect a limited range of different odorant substances. In a collaborative project with the group of Horst Vogel (Ecole Polytechnique Federale de Lausanne, CH), we aim to explore the molecular determinants of specific olfactory receptors. We have modeled the mouse Eugenol olfactory receptor based on the crystal structure of β2-adrenergic receptor. Based on this model, we have designed a series of site directed mutagenesis experiments to study the structural determinants of receptor specificity on various chemically diverse odorant molecules.
Second messengers control a wide range of important cellular functions in eukaryotes and prokaryotes. Cyclic di-GMP, is a ubiquitous second messenger that regulates cell surface-associated traits in bacteria. Genome sequencing data revealed several large and near-ubiquitous families of bacterial c-di-GMP related signaling proteins. In pathogenic bacteria, this switch is often accompanied by the transition from an acute to a chronic phase of infection. This makes c-di-GMP signal transduction an attractive target for novel antibiotics that interfere with bacterial persistence. We are collaborating in-house with the groups of Urs Jenal, Tilman Schirmer and Dagmar Klostermeier in a Sinergia project aiming to discover novel components of the c-di-GMP signaling network and to uncover their molecular mechanisms.