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.
Our deep understanding of plant, insect, and fungal biochemistry enables us to select targets and molecules that are most likely to meet our product goals while minimizing off-target effects. By knowing the target from the start, we can quickly achieve potency and selectivity through structure-based design.
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.
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.