Explore the vital role farmers play in combating climate change and securing our global food supply. Join us as we showcase dedicated farmers, sustainable food production, and tackle urgent global crises.
"The Future of Food" documentary series by Zinc Media Group in partnership with the World Farmers' Organisation (WFO).
DNA Encoded Libraries (DELs) are changing the way the pharmaceutical industry approaches compound discovery and Enko is among the first to bring the approach to the agriculture industry. By using DELs, we can screen 100’s of billions of compounds against each of our targets very cost effectively.
Using DELs to identify molecules that act on proteins of interest from target organisms and do not act on the equivalent proteins from non-target organisms (e.g., humans and beneficial organisms) yields an unprecedented number of effective and selective molecules which are high value starting points for developing safe and effective products.
Finding molecules that are potent, specific, safe, and which have the other characteristics of a successful crop production product is a complex challenge. Enko’s proprietary datasets fuel an Artificial Intelligence (AI) platform that improves our capabilities and accelerates our research by rapidly putting results into the hands of researchers and allowing them to seamlessly incorporate the data from all previous research.
Our AI enables better identification and characterization of targets that meet key product concepts as well as the rapid discovery and improvement of molecules that hit these targets.
The result is that we can achieve potency and selectivity with far fewer resources creating opportunities to pursue projects not practical for other organizations.
DNA-encoded library screening provides rich datasets of billions of observations for a target screened under multiple, biologically relevant conditions.
These data are too large and complex for a human to interpret yet embedded within, are the roadmaps to making better products. Machine Learning (ML) models built upon these large datasets help us uncover key properties of the target we want to exploit as well as properties we want to avoid. Our state-of-the-art ML pipelines rapidly build powerful and insightful models with these data.
We then use trained ML models to search virtual chemical space and to support compound optimization. By using these models in tandem with scientists’ insights, we can efficiently discover potent and selective molecules with favorable properties.
Enko’s target-based approach, and our ability to develop deep biochemical and structural understanding of these targets, allows us to leverage Structure-Based Design principles in our programs.
Protein structures are atomic-scale maps we use to understand how our molecules interact with target proteins to change their function. We use this understanding to optimize our molecules using Structure-Based Design; an approach where we leverage physics-based modeling techniques and simulations to effectively identify the parts of a molecule which can be altered to improve its commercial characteristics. This power enables us to dial-in safety, selectivity, potency, and other properties that are essential to delivering safe, effective, and sustainable solutions to growers.
