Proteins are the essential tools inside the cells that perform nearly all cellular functions.
Just like macroscopic tools, their shape defines their function. Recent reports show that the protein structure prediction community is making progress, but that the qualities of the models they generate do not meet yet the stringent accuracy requirements to become useful to the biologists.
Based on sets of decoys (perturbed protein structures) of each of 1326 native protein structures, we have developed a technique for constructing a smooth knowledge-based potential by optimizing the local minimae around protein native structures. See the poster.
This project continues this work by iteratively using the constructed potential for refining protein structures and adding refined structures to the set of decoys if the optimization gets stuck or gets further away from the native structure.
Requirements: Knowledge and experience with geometry, spline functions and numerical optimization together with basic knowledge of or interest in computational structural biology.
You will be part of the geometry group and also associated with the applied functional analysis group – both at DTU Mathematics.
Contact persons: Peter Røgen and Mathias Stolpe