Correlated Mutation Analysis-assisted Chimeric-Engineering/Directed-Evolution of Novel Portein/Enzyme Function

Summary Chimeric protein engineering and directed-evolution are increasingly popular methods to obtain enzymes with desired activities and substrate specificities. Chimeric-engineering goes about this by grafting select components of two homologous enzymes together (preserving activity while combinatorially affecting substrate specificity), whereas directed-evolution mutagenizes ligand-binding pockets to perturb substrate specificity and/or catalytic sites to modify activity. The major experimental limitation afflicting these techniques is that the maximum number of enzyme constructs to be screened or selected is often many orders of magnitude smaller than the total number of possible constructs. For example, a typical library size for a selection is currently on the order of one billion (109) constructs. This only allows for five amino acid positions in the enzyme to be fully mutagenised (205 = 3.2 x 109), far fewer than the total number of residues normally implicated in the formation of a single substrate-binding pocket.

Applications This algorithm addresses the question is how to focus the screening/selection to those constructs with the highest likelihood of success, by eliminating those constructs from consideration that are likely to fail. The computational algorithm developed provides an answer. The method is generalized, requiring only a multiple sequence alignment of the target enzyme subfamily, and preferably (but not necessarily) a representative protein structure. The algorithm does not make predictions of substrate specificity, but rather identifies constructs that are not likely to be active due to other considerations. The output of the algorithm is a score assignment for every putative enzyme construct, and the standard deviation represents the difference in score between any two constructs. This output allows not only for a rank-ordering of the constructs, but also provides a confidence assessment that any given construct is likely to be more (or less) functional than another. The optimal subset of the full putative library to be screened/selected would contain a diverse collection of high ranking constructs that are more likely to be active than those not chosen. For Further Information Please Contact the Director of Business Development Michal Preminger Email: michal_preminger@hms.harvard.edu Telephone: (617) 432-0920

Inventor(s): Walsh, Christopher T.

Type of Offer: Licensing



Next Patent »
« More Engineering - Electrical Patents

Share on      


CrowdSell Your Patent