Recent advances in computational, structure-based protein design methods, developed in my laboratory, successfully predict mutations that drastically alter the ligand-binding specificity of receptor proteins. Using these design techniques, several members of the E. coli periplasmic binding protein (PBP) superfamily that normally bind sugars or amino acids have been converted into receptors that recognize chemically diverse ligands with high affinity and specificity. Introduction of fluorescent and electrochemical reporter groups has permitted the engineered PBPs to be used as reagentless optical or bioelectronic biosensors. The receptors also can be re-introduced into E. coli where they control synthetic signal transduction pathways that mediate transcriptional activation response to non-natural, extracellular chemical signals. These early results are highly encouraging and suggest that the computational design of a wide variety of biological functions can be contemplated. However, in order for this capability to become a reality, it is necessary to further develop the computational design techniques, and to extend them to dealing with binding sites of increasing complexity, such as protein-protein and protein-DNA interactions. The ability to engineer proteins with a high degree of precision and sophistication has numerous biomedical applications. I propose to further develop and experimentally test the computational design techniques for manipulating molecular recognition in proteins, using specific, biomedically relevant applications as design targets that guide the choice of receptor systems and ligands that will be engineered. The tasks identified below are therefore intended to have clear practical applications, illustrating the potential wide-ranging utility of computational protein engineering to the biomedical sciences, while at the same time exploring basic scientific questions regarding molecular recognition in proteins.
Aims 1 -3 are focused on the development of receptors with drastically altered ligand-binding properties. These explore different applications in clinical science (Aim 1), pharmacology (Aim 2), and cell biology (Aim 3). From a basic science point of view, they will allow us to develop the techniques for engineering binding sites, and to explore scaffolds other than the PBPs (Aim 2).
Aim 4 is intended to extend the design technique to much more complex systems. ? ?
| Benson, David E; Haddy, Alice E; Hellinga, Homme W (2002) Converting a maltose receptor into a nascent binuclear copper oxygenase by computational design. Biochemistry 41:3262-9 |
| Looger, L L; Hellinga, H W (2001) Generalized dead-end elimination algorithms make large-scale protein side-chain structure prediction tractable: implications for protein design and structural genomics. J Mol Biol 307:429-45 |
