About

The prediction of biomolecular structures is routed in the translation from protein or nucleic acid sequence to 3D structure. In reality, these 3D structures result from a delicate interplay with small molecules, ions, fatty acids and solvents. At the same time, the predicted structures are a product of the underlying machine-learning models. By combining the applicability range of the method with the limitations of modeling biological systems, we can provide confidence estimates in the context of the respective research question. We aim to extend our offer beyond general models like AlphaFold to more specific tools in the field of sequence based predictions to provide researchers with the ideal tools to their specific needs.

Embedding the Bio-Structure Hub in the SSC enables, building research software sustainably and in accordance with good scientific practice. This entails on the one hand making use of software engineering tools and methods such as version control, development and production environments, testing frameworks, documentation and release workflows, and a development process, to name a few; and on the other hand, acknowledging that research software is an infrastructure that is the foundation of cutting-edge research, and as such needs to be drafted, designed, operated and maintained in a purposeful manner.

Projects

Current projects in the Bio-Structure Hub range from carefully cofolding the components of large protein complex structures, to adding molecular cofactors to improve the quality of predicted structures, or modeling interaction sites for various species. We assist in leveraging structure predictions to plan future experiments, or run preliminary simulations to be used in proposals for future projects.

A list of current projects is provided here.