About This Project

Delivering best-in-class enzymes for biomanufacturing.

Ask the Scientists

What is the context of this research?

Biomanufacturing offers a sustainable supply chain of everyday products, from our food to life-saving therapies, replacing fossil fuels and reducing carbon emissions with precision fermentation[1,2]. Valued at 1 trillion dollars and projected to grow to 30 trillion[3], the bioeconomy will reshape entire industries. Despite its breakthrough promise, scalability is a challenge. Our lab has two decades of experience engineering microbial factories. A highly complex enzyme, the cytochrome P450s, is a common bottleneck across multiple biomanufacturing applications[4,5]. Its poor activity leads to microbial production loss, making bioproducts economically unviable. To unlock and scale a new era of sustainable products powered by biology, making enhanced P450s biocatalysts is essential.

What is the significance of this project?

P450s are hard engineering problems due to their structural complexity and intricate electron transfer sourcing via redox partners[6]. Despite being a driving force of the chemistry of life, its poor kinetics and processivity limit its application [7]. In commercial biotech, companies tackle the challenge of enhancing one P450 enzyme at a time by testing thousands of homologs or mutations through sophisticated automation, a costly strategy inaccessible to labs. We propose using novel machine learning tools to accelerate P450 optimization at a fraction of the cost, building a versatile framework for diverse enzyme scaffolds. Our pipeline will enable the rapid delivery of enhanced industrial biocatalysts, debottlenecking biomanufacturing towards scalability and sustainability.

What are the goals of the project?

What if, by engineering one highly functional P450, we uncovered the data to enhance an entire family of enzymes?

Round 1: Deploying ML for the engineering of a P450

- We will benchmark ML tools[8,9] to predict P450 protein fitness using sequence diversity as an input.

- We will select 100 mutations targeting the improved activity of one representative of the most ubiquitous and diverse family of P450s: the CYP716[10].

Round 2: A framework for P450 optimization

- We will transfer and combinatorially stack[11] the top 5 beneficial mutations to the corresponding modifications in diverse scaffolds from the CYP716 family, delivering best-in-class P450s for various biomanufacturing applications.