The emerging fields of biomanufacturing and biopharmaceuticals require enzymes with improved or novel activities. Yet, our lack of total understanding of the intricacies of how enzymes function has constrained our ability to robustly engineer substrate specificity1–3
. Furthermore, the mechanisms of natural evolution leading to improved or novel substrate specificities are not wholly defined4
. In this talk we will present the use of a synthetic biology approach and deep mutational scanning to generate three comprehensive fitness landscapes for hydrolysis activity of an amidase with different aliphatic amide substrates: acetamide, propionamide, and isobutyramide. We assessed the function of >6500 point mutations and found that 20.6% of all variants from the isobutyramide selection had above wild-type fitness. Consistent with existing theories of adaptive molecular evolution, we also found that beneficial mutations were exponentially distributed5
. Remarkably, there was essentially no correlation between the fitness of beneficial mutations identified in the isobutyramide selection to the other two selections. In this talk we will also discuss the evaluation of fitness landscapes with respect to enzyme structure. Our results show that, at least for this enzyme, fitness effects for a mutation on one substrate cannot be predicted based on known effects for a different substrate.
1. Arnold, F. H. Combinatorial and computational challenges for biocatalyst design. Nature 409, 253–257 (2001).
2. Bornscheuer, U. T. et al. Engineering the third wave of biocatalysis. Nature 485, 185–194 (2012).
3. Liberles, D. A. et al. The interface of protein structure, protein biophysics, and molecular evolution. Protein Sci. 21, 769–785 (2012).
4. Khersonsky, O. & Tawfik, D. S. Enzyme promiscuity: a mechanistic and evolutionary perspective. Annu. Rev. Biochem. 79, 471–505 (2010).
5. Orr, H. A. The Population Genetics of Adaptation: The Distribution of Factors Fixed During Adaptive Evolution. Evolution (N. Y). 52, 935–949 (1998).