Final Report Summary - ABEL (Alpha-helical Barrels: Exploring, Understanding and Exploiting a New Class of Protein Structure) The ABEL Grant was based on the serendipitous discovery of a new protein structure that is very rare in natural biology, and which we call alpha-helical barrels (aHBs). These are interesting structures because they have central accessible channels to which new functions could be added. The premise of the proposal was that if we could learn to build these aHBs from first principles, i.e. by so-called de novo design, they might provide a powerful platform for understanding other protein structures, and for building new types of proteins that might be useful in biotechnology and medicine as catalysts, storage materials, and as parts of sensor devices.To tackle this challenge, we developed a theoretical framework for designing aHBs and related de novo proteins. This led to new computational design software, which we have made available online for others to use freely. We have also developed computational tools for analysing, visualising and studying the broader class of proteins that the aHBs belong to.We have used this understanding and the computational tools to design a whole series of new aHBS, which we have made and characterised experimentally. In short, we can now make many 10s – 100s of aHBs at will. Considering that we discovered just one by chance in 2011 this is quite an achievement.Next, we added function to the experimental aHBs, which might be considered as blank protein canvasses to work with. In this way, we have added catalytic and binding functionalities; we have made aHBs that form conducting ion channels in membranes, and we have turned the aHBs into fibrous and nanotube materials.These new designer aHBs may well find applications in biotechnology and biomedicine. For example, we have shown that different aHBs with different sized channels and internal chemistry can distinguish between small molecules, including biomarkers for cancer, and drug & explosive precursors. Moreover, arrays of the barrels can be used to sense differences in complex mixtures. These complex mixtures can be drinks and foodstuffs, or fluids from healthy and diseased patients. We call this technology Barrel-Array Diagnostics and SenSing, or BADASS, and we believe that it has potential in medical diagnostics and other types of sensing.
