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.
Together, machine learning combines with the DNA-encoded libraries (DEL) to supercharge Enko’s discovery process. Each DEL experiment results in massive datasets with billions of binding observations across enzymes within our target pests. These high-quality training data points feed into our machine learning models, enabling us to find the right molecules with more favorable properties more quickly and effectively.
Enko is building large novel datasets. We leverage physics-based models, advanced data analytics, Artificial Intelligence, and Machine Learning to discover novel molecules that meet our product safety and sustainability goals.
DNA-encoded libraries (DEL) are changing the way the pharmaceutical industry discovers new compounds. Enko is among the firs to apply this technology to the agriculture industry. By using DEL, Enko is able to tap vast new molecular space and to screen billions of compounds against each of our targets very quickly and cost effectively.