Statistical design of interactions between proteins that are both novel and specific

The ability of proteins to associate with each other in specific interactions is crucial to the functioning of vast multitudes of biological processes. In the crowded molecular soup that makes up the intracellular environment, a single protein will encounter many other proteins with which they could potentially interact. The interactions that help cells reproduce and survive may range from fleeting connections to the formation of long lasting complexes; however it is the specificity of these interactions that allows the exquisite levels of regulation observed in so many biological systems. I will focus on how proteins evolve specific interactions, and how we can elucidate interaction partners from the vast amounts of genomic data currently being generated. Each and every cell is packed with proteins, the interactions between these proteins form the foundation of almost all cellular processes. I am interested in the ways that proteins fit together to form complexes, and the constraints that complex formation imposes on the evolution of the sequences of interaction partners. If one amino acid on the surface of protein A changes shape, in order for protein B to bind to protein A an amino acid on the surface of B may also have to change - this is an example of a compensatory mutation. I will develop statistical and mathematical analyses that extract correlations between different residues of a protein of interest from alignments of orthologous and paralogous proteins. Detecting compensatory mutations in sequence data provides information about protein structure and function, and the specificity of protein-protein interactions. The specificity of binding interactions is crucial to the proper functioning of cellular processes, and determining the evolutionary rules that govern the specificity of protein interactions will inform the rational design of novel specific interactions between proteins. Our ability to understand and thus engineer the molecular determinants of specificity is vital to efforts to design and engineer effective drugs and other bio-molecules. There are numerous potential applications across a range of different industries, for example synthetic biology approaches to energy production, and the development of biomimetic materials.

I will make every effort to disseminate both the nature and results of my work beyond the confines of the international academic community. It is likely that there would be a high level of interest from industry in the ability to use statistical analyses to design novel interaction specificities. The Technology Transfer Group in the MRC Head Office is directly responsible for the management of exploitation of results from the council's laboratories and works in partnership with scientists to identify opportunities and develop and execute exploitation strategies. I would work closely with this group to ensure the protection of intellectual property. This might involve the patent process, to secure a proprietary position and thereby enhance the value of the opportunity for a prospective industrial partner. However, this process can be long, expensive, and often arduous and so will not be embarked upon lightly. I would also be interested in embarking on industrially funded collaborations. I am also happy to ensure that novel materials produced by this research are distributed to fellow academics under an appropriate Materials Transfer Agreement ensuring that the recipient does not commercially exploit without reference to the originator. The MRC-LMB has extensive experience of managing and exploiting results from the laboratory, and I would seek to benefit from this expertise. For example, antibody engineering technology was pioneered at the MRC-LMB, and the method of humanization of monoclonal antibodies through engineering the proteins was subsequently protected by a patent. Start up companies have also been founded by academics at the MRC-LMB in order to fully realize the potential of their scientific results. For example Cambridge Antibody Technology Ltd. (CAT) has disseminated a phage antibody screening technology that allows in vitro selection of novel antibodies from human repertoires to the wider public.