The platform's framework demonstrated linear scaling up to 5.6 million virtual central processing units (CPUs)—a new benchmark for cloud-based drug discovery—allowing billions of molecules to be screened without loss of efficiency. As proof of concept, the team identified potent inhibitors for existing and emerging cancer targets for which few inhibitors are known.

"AdaptiveFlow is the next generation in automated drug discovery platforms for routine ultra-large virtual screenings," said co-corresponding author Christoph Gorgulla, Ph.D., Center of Excellence for Data-Driven Discovery, St. Jude Department of Structural Biology. "With this platform, we are able to screen 69 billion molecules, representing the largest ready-to-dock library in the world."

Multidimensional grid allows for multibillion-molecule screening

The recent expansion of ultra-large molecule screening libraries prompted the drug discovery field to unlock their potential. While pioneering efforts saw success in billion-compound screens, AdaptiveFlow is the first of a new generation focused on efficiency, affordability and access. This is rooted in its economical approach to computation.

Gorgulla explained, "A lot of software loses communication efficiency with increasing CPU count, but with AdaptiveFlow, the scaling behavior is perfectly linear, even with millions of CPUs. That is special."