Using cryo-electron microscopy (cryoEM) numerous sub-nanometer resolution density maps of large macromolecular assemblies have been recently reported. Although no atomic detail is generally resolved in these density maps, at 7 Å resolution α-helices are observed as density rods. The Primary goal of this project is the development of a computational protein structure prediction algorithm that incorporates the experimental cryoEM density map as restraints. The placement of helices is restricted to regions where density rods are observed in the cryoEM density map. The Monte Carlo based protein folding algorithm is further driven by knowledge based energy functions.
The method has been benchmarked with eleven highly α-helical proteins of known structure. The chosen proteins range in size from 250 to 350 residues. Starting with knowledge of the true secondary structure for these proteins, the method can identify the correct topology within the top scoring 10 models. With more realistic secondary structure prediction information, the correct topology is found within the top scoring 5 models for eight of the eleven proteins.
Alumni Project Members: Steffen Lindert, Rene Startitzbichler, Mert Karakas, Nils Woetzel, Nathan Alexander, Michaela Fooksa