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Engineering indel and substitution variants of diverse and ancient enzymes using GRASP

Gabriel Foley, University of Queensland Abstract: Ancestral sequence reconstruction is a technique that can be used to predict the amino acid states of ancestral forms of protein families. It is increasingly being employed to study evolution and to effectively navigate sequence space in order to engineer novel proteins. In order to use larger and more complex data, we developed Graphical Representation of Ancestral Sequence Predictions (GRASP), which efficiently implements maximum likelihood methods to enable the inference of ancestors of families with more than 10,000 members. GRASP uses partial order graphs (POGs) as the key data structure in order to represent and infer insertion and deletion events across ancestors. We validated GRASP across three distinct enzyme families: glucose-methanol-choline (GMC) oxidoreductases, cytochromes P450, and dihydroxy/sugar acid dehydratases (DHAD). All tested ancestors demonstrated enzymatic activity. We additionally showed that modular blocks of content from insertions and deletion could be used to engineer novel enzymes and that these modular building blocks were capable of altering enzyme function, allowing for effective ways to explore sequence space. This talk introduces ancestral sequence reconstruction and specifically presents (1) the type of data that can be generated and (2) the advantages of using a tool such as GRASP that is capable of incorporating much larger scales of data set size. GRASP is available: http://grasp.scmb.uq.edu.au/ Preprint: https://www.biorxiv.org/content/10.11...