R&D partnership will give farmers more options for fighting weeds worldwide
Crop health company Enko has partnered with Bayer to develop diverse chemistries for crop protection. Applying drug discovery approaches from pharma to crop protection will allow the companies to identify unexpected product candidates that safely target pests in new ways.
The partnership uses Enko’s toolkit of proven pharma technologies—DNA-encoded libraries, machine learning and structural biology—to quickly assess more than 140 billion molecules based on specific target pest enzymes not found in people. The process identifies novel product starting points in new chemical families that haven’t been explored yet, eliminating pests through new pathways and combating resistance. The resulting molecules bind with the target pest like a lock and key, which means they are more effective in lower quantities and don’t interact with the surrounding environment. Farmers can apply less product, less often.
“There’s a vast chemical universe that can help growers with the urgent crop threats they’re facing—those molecules are just waiting to be found,” said Jacqueline Heard, CEO, Enko. “Borrowing from and building upon pharma innovations can help the agriculture industry solve these problems faster while building in safety guardrails from the start. Bayer has understood the synergies between these two industries for decades and is the right partner to accelerate our technology expertise.”
Enko’s target-based approach makes sure pesticide candidates are going to be safe, sustainable and effective before sinking years of resources into them. Only molecules that bind with the specific pest enzyme and don’t impact similar enzymes in other organisms continue in discovery. This de-risks development, increases success rates and speeds up the time to market. The process is also trait-independent, so growers worldwide will be able to choose the best seeds for their operation when using the future herbicide and increase field resilience.
The partnership is targeting the most common weeds worldwide, and the proof-of-concept phase will narrow down the best application.
