Proteins are the major functional group of molecules in biology. The impact of protein science on medicine and chemical productions is rapidly increasing. However, the greatest potential remains to be realized. The field of protein design has advanced computational modeling from a tool of support to a central method that enables new developments. For example, novel enzymes with functions not found in natural proteins have been de novo designed to give enough activity for experimental optimization.
This thesis presents the current state-of-the-art within computational design methods together with a novel method based on probability theory. With the aim of assembling a complete pipeline for protein design, this work touches upon several aspects of protein design. The presented work is the computational half of a design project where the other half is dedicated to the experimental part of the pipeline. Thus, experimentally evaluations are presented. The conclusion of the thesis arrives at a protocol and identies key strengths and limitations of the individual steps.