GRASP Enzyme Technology - Prozomix


Genomics-based Related Activity Screening Protocol

Significance of Genomic Data to Future Enzyme Technologies

The incessant logarithmic generation of DNA sequence data from the global Genomics effort continues to challenge efforts to harness this expanding resource at both the in silico and in vitro level.  The successful application of Genomics data in R&D must establish a very fine balance between making use of what we know today, and preparing to make use of what we are going to know tomorrow.  Standing still in this area of biology for any length of time is a luxury that can be afforded by none.

Natural or Forced Evolution – a Choice?

Especially since the mid 1990s, laboratory techniques for the evolution of enzymes have become a very powerful force.  A variety of methods, with site-directed mutagenesis (SDM) and error-prone PCR / DNA shuffling being only notable examples, can now be employed in order to either radically change, or fine tune, an enzyme’s biophysical or biochemical attributes to those more aligned with a desired application.  As powerful as these techniques are though, the unstoppable march of genome sequencing projects, and other sources of DNA sequence data, most notably Metagenomics (see seperate page added late in 2014 on proprietary meta-GRASP technology), presents a pool of naturally evolved / optimised enzymes so large as to justify primary screening against, when it comes to the development of certain classes of ubiquitous biocatalyst, such as aldo-keto reductases (KREDs).  The viability of such an approach, however, when compared to forced evolution approaches, relies on two main aspects.  The first is being able to efficiently “mine” genomic data in order to select a subset of sequences most likely to give an equal as possible sampling of all available enzyme attributes of interest (substrate specificity, solvent tolerance, temperature optimum, etc).  Such a rendering down of available primary “sequence space” can only be achieved by customising powerful bioinformatics approaches against specific objectives.  Secondly, when a list of target sequences has been defined in silico, high-throughput in vitro methodology must be on-hand to ensure rapid and cost-effective development of the biocatalyst library.

Genomics-based Related Activity Screening Protocol (GRASP™)

The GRASP™ protocol was developed by Prozomix to satisfy the in silico and in vitro challenges presented by Genomics with respect to the development of large representative panels of enzymes for biocatalysis and other applications.  For example, GRASP™ is being used to develop and expand the Prozomix “Biocatalysis Enzyme Toolkit“, where the latest Genomics data released is exploited continually to update the different panels of enzymes that comprise the overall kit.


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Advanced meta-GRASP technology