The Mutagenesis Assistant Program (MAP) is a statistical tool used to benchmark random mutagenesis methods at the protein level. This blog summarises the key aspects of this tool. A detailed description of the algorithm used in this tool is given in the articles and a book chapter by the authors and collaborators [1,2,4]. Development began in 2005 while I was working at the International University of Bremen, Germany. I collaborated with Prof. Ulrich Schwaneberg (now at RWTH Aachen, Germany) and his Ph.D. student Dr. Tuck Seng Wong (now a senior lecturer at the University of Sheffield, UK).  We were studying enzymes in organic solvents. As our collaboration progressed, I became intrigued by the experimental method of directed evolution, which improves protein performance. This method cleverly uses nature’s billions of years of evolution to all living organisms on Earth.  By applying these methods, we can optimise and engineer proteins for enhanced performance. Bacteria serve as the factory for this process, capable of rapid reproduction within a coffee break. You provide the blueprint of your idea in the form of DNA genes, and they produce the required protein nanomachine. In this generation, you can tweak their production machinery using random mutagenesis to introduce errors in the nanomachines’ structure, hopefully increasing their performance. The next step is designing a method to select only the bacteria mutants containing the optimised nanomachine. These selected mutants can undergo further rounds of mutation to further improve the protein.