Enamine, a leading integrated drug discovery contract research organization (CRO) has today announced its participation in an open-science collaboration with Variational AI and the Agora Open Science Trust. This initiative aims to advance the discovery of novel small-molecule inhibitors targeting PRMT6, which is a therapeutic target implicated in Spinal and Bulbar Muscular Atrophy (SBMA), a rare neuromuscular disorder currently lacking approved treatments that slow or halt the progression of the disease.
The initiative brings together expertise in medicinal chemistry, generative artificial intelligence (AI), machine learning, structural biology, pharmacology, and preclinical development across a global network of partners, including the Structural Genomics Consortium (SGC), the University Health Network (UHN), the University of Oxford, the Venetian Institute of Molecular Medicine (VIMM), and Charles River Laboratories. In keeping with Agora’s open science principles, all data generated through the project, including molecular structures, assay results, and progress updates, will be made publicly available.
An Integrated Open-Science Discovery Framework
The collaboration operates within a fully transparent design–make–test–analyze (DMTA) framework that integrates AI-driven molecular design, rapid compound synthesis, and biological testing. Variational AI applies its Enki™ generative AI platform to design novel PRMT6 inhibitor scaffolds and discover lead candidates.
To ensure rapid execution and reduce downstream attrition, the initial Enki™ generation is constrained to Enamine REAL Space and its extended chemical space, Enamine xREAL, the world’s largest synthetically validated chemical space. By embedding synthetic feasibility directly into the design process, the collaboration emphasizes speed, learning, and iteration.
This collaboration demonstrates how early discovery can move faster when generative AI is paired with synthetically validated chemical space. Enamine’s xREAL Space enables the DMTA cycle to operate as intended — transforming the make step from a bottleneck into a strategic engine for rapid iteration, accelerating the identification of a novel PRMT6 inhibitor series.
— Iryna Iavniuk, CEO, Enamine US Inc.
By coupling Enki’s generative design capabilities with Enamine’s synthetically validated REAL/xREAL space, we dramatically improved the design step of the DMTA cycle, allowing the program to rapidly identify and validate additional PRMT6 inhibitor series.
— Handol Kim, CEO, Variational AI
This collaboration reflects a highly transparent and collaborative approach to rare disease drug discovery. By partnering with industry leaders such as Variational AI and Enamine, we can combine advanced AI-driven molecular design with world-class chemistry capabilities to accelerate the discovery of PRMT6 inhibitors for SBMA and expand therapeutic opportunities for this underserved disease.
— Dr. Peter Sampson, Vice President of Drug Discovery and Development at Agora Open Science Trust
Enamine’s Role in Accelerating the DMTA Cycle
Within the partnership, Enamine contributes its expertise in the ‘make’ step of DMTA, which is often the primary bottleneck in early discovery programs. Enamine’s contributions include:
- Access to synthetically validated chemical space
- Rapid synthesis of novel compounds
- Iterative SAR exploration through analog and scaffold-based synthesis