Protein 3D Modelling


Associated Scientists

Facts & Details: 

Proteins are gene products that fold from a linear amino acid sequence to a strictly determined 3D structure. In general, they have stable, but flexible structures that perform specialized biological functions in the cell. In the course of evolution, genes evolved leading to proteins with varying shapes, biochemical activities and different amounts in specific cell types. The detailed analysis and comparison of these proteins, with regard to their sequence, structure, functional sites, regulation and pathways is crucial for understanding their molecular activity and biological role.

Gene mutations may interfere with protein abundance in the cell by modifying regulatory regions that determine the amount of protein that is produced. In addition, some mutations can lead to the immediate degradation of the molecule. Other mutations can have a direct impact on protein activity by causing local structural rearrangements that affect protein stability or change the functional regions, such as interaction and active sites.

We perform different types of bioinformatic analyses on candidate variants of interest, identified by the latest sequencing and genotyping technologies in the investigation of the genetic basis of disease. In particular, we analyze mutated positions regarding sequence conservation, their location relative to known functional sites, including active sites, and ligand or protein interaction sites.

In some cases where a protein structure is available, the effect of the amino acid exchange is analyzed in atomic detail (e.g. mutations in XIAP and IL10 as shown below). More frequently, a reliable experimental structural model is not available for the protein of interest. In these instances we construct homology models to investigate the effect of the mutated position (e.g. SH2B3 and NDP52). The collected evidence is combined with relevant information available in the scientific literature in order to determine possible consequences of the mutation and better understand disease processes and mechanisms. If you are interested in our work or want to collaborate, please contact: Gabriele Mayr.