Core contributor across PELICO, SAFER, AEGIS, ALISE, and BENOVELTY — all centered on designing bioactive compounds for therapeutic use.
ENAMINE LIMITED LIABILITY COMPANY,RESEARCH AND PRODUCTION ENTERPRISE
Ukrainian medicinal chemistry SME specializing in compound libraries, photopharmacology, bioisostere design, and AI-driven drug discovery.
Their core work
Enamine is a Ukrainian chemical compound supplier and contract research organization specializing in building blocks, screening libraries, and custom synthesis for drug discovery. In H2020, they contribute medicinal chemistry expertise — designing photocontrolled drug candidates, saturated bioisosteres for pharmaceutical applications, and compound libraries for AI-driven drug screening. They bridge the gap between synthetic chemistry and early-stage pharmaceutical R&D, providing both physical compound collections and deep chemistry know-how to European research consortia.
What they specialise in
Coordinated PELICO (photocontrolled biological activity) and ALISE (light-controllable antibody-peptide conjugates); BENOVELTY includes photochemical synthesis methods.
Coordinated BENOVELTY (ERC Consolidator Grant, EUR 2M) focused on benzene bioisosteres including bicyclo[1.1.1]pentanes and cyclobutanes for drug design.
Participant in AIDD (advanced ML for drug discovery) and partner in BIGCHEM (big data in chemistry), applying deep learning and generative models to chemical reactions and screening.
Contributed screening compound expertise to AEGIS (early-stage drug discovery), BIGCHEM (big data in chemistry), and AIDD (phenotypic screening, yield prediction).
How they've shifted over time
In the early period (2016–2019), Enamine focused on traditional medicinal chemistry — photocontrolled peptides (PELICO), serotonin receptor agonists (SAFER), and participating in big-data and accelerated drug discovery consortia (BIGCHEM, AEGIS). From 2021 onward, the focus shifted sharply toward AI-integrated drug discovery (AIDD with deep learning and generative models) and advanced molecular design (bioisosteres in BENOVELTY, antibody-drug conjugates in ALISE). The evolution shows a company moving from compound supplier toward research-driven innovation in computational chemistry and targeted therapeutics.
Enamine is integrating AI and machine learning into its core chemistry capabilities, positioning itself at the intersection of computational drug discovery and advanced synthetic chemistry.
How they like to work
Enamine splits evenly between leading and contributing: 3 projects as coordinator (including an ERC Consolidator Grant) and 4 as partner or participant. With 57 unique partners across 16 countries, they maintain a wide and diverse network rather than relying on a small circle of repeat collaborators. This suggests an organization comfortable both driving research agendas and integrating into larger consortia as a specialized chemistry partner.
Enamine has built a broad European network spanning 57 unique partners across 16 countries, reflecting deep integration into the EU drug discovery research community. As a Ukrainian SME, their wide geographic reach across Western and Central Europe is particularly notable.
What sets them apart
Enamine combines industrial-scale compound supply with genuine research capability — a rare combination among SMEs. Their ERC Consolidator Grant (BENOVELTY) signals that they are recognized as a research leader, not just a service provider. For consortium builders, they offer both the practical compound libraries needed for screening campaigns and the scientific depth to co-develop new molecular scaffolds and drug candidates.
Highlights from their portfolio
- BENOVELTYERC Consolidator Grant worth EUR 2M — the largest single award, focused on benzene bioisosteres for drug design, signaling strong independent research capacity.
- ALISECoordinated project combining antibody-drug conjugates with photoswitches — an innovative intersection of targeted cancer therapy and photopharmacology.
- AIDDLarge MSCA network applying AI, deep learning, and generative models to drug discovery — marks Enamine's pivot into computational chemistry.