Engineering highly active and specific protease variants
Abstract
The reprogramming of enzyme catalytic activity and selectivity is a central issue in protein biochemistry and biotechnology. Numerous structure-guided and directed evolution strategies have been employed in search of enzyme variants that exhibit high catalytic rates with poor or inactive substrates of the parental enzyme. As impressive as these successes have been, the engineering of enzymes that exhibit turnover rates and selectivities with new substrates comparable to their natural counterparts has proven quite a challenge, especially when considering those enzymes for which a genetic selection strategy is not possible. By utilizing bacterial display and multi-parameter flow cytometry we have developed a novel methodology for emulating positive and negative selective pressure in vitro for the isolation of enzyme variants with reactivity for desired novel substrates, while simultaneously excluding those with reactivity towards undesired substrates. In order to demonstrate the application of the high-throughput flow-cytometric for protease engineering; we sought to evolve a set of highly active OmpT variants that have P1 specificities altered systematically to recognize one amino-acid from each of the six classes of amino acids By screening error-prone and multiple residue saturation libraries we describe the systematic directed evolution of a set of proteases with altered recognition sites. A set of OmpT variants were engineered that can specifically cleave substrates having a hydrophobic, polar, aromatic and even acidic residue at the P1 and Arg at the P1’. In particular we note that the change in electrostatic specificity from a basic amino acid (Arg) to an acidic (Glu) is unprecedented. After successfully changing P1 specificity, we then focused our attention on isolating OmpT mutants that recognize altered P1’ specificities such as Ala and Val. Towards this end, we show the isolation of highly active OmpT variants that cleave ArgVal and Glu-Ala sequences.