
Spark
Scaffold hopping and bioisosteric replacement for discovering novel chemistries in drug discovery projects.
Overview
Spark™ is a scaffold hopping and bioisosteric replacement software tool developed by Cresset, designed to accelerate molecular discovery in drug and agrochemical research. By working in electrostatic and shape space, Spark matches the nature of molecules more precisely than competing tools, enabling medicinal chemists and computational scientists to generate diverse, non-obvious bioisostere ideas starting from fragments of real molecules.
Spark is widely used to find freedom to operate in congested IP spaces, avoid patent-related issues, expand proprietary IP portfolios, and reduce the risk of late-stage attrition by identifying replacements for functional groups that are critical for binding but problematic in terms of ADMET properties. Customers have described Spark as the best scaffold hopping software they have ever used.
Core Capabilities and Available Methods
- Scaffold Hopping: Find novel cores and scaffolds for molecule discovery projects, enabling exploration of entirely new chemical series.
- Bioisosteric Replacement: Generate highly innovative bioisostere ideas grounded in real chemistry, using electrostatic and shape-based matching to identify functionally equivalent replacements.
- R-Group Replacement: Identify novel, biologically relevant R-groups for existing molecules to improve potency or properties.
- Ligand Growing: Pick up additional interactions from the active site of a target protein by growing the ligand in a guided, field-based manner.
- Ligand Linking and Joining: Find linkers derived from real chemistry to join two ligands, supporting fragment-based and bifunctional molecule design.
- Macrocyclization: Address difficult binding pockets through ligand macrocyclization strategies.
- Water Replacement: Gain additional ligand-protein interactions by displacing crystallographic water molecules with appropriate chemical groups.
Key Benefits for Drug Discovery
- Escape IP traps by identifying structurally novel alternatives in crowded patent landscapes.
- Overcome ADMET liabilities by replacing problematic functional groups while maintaining binding affinity.
- Accelerate lead optimization through rapid generation of innovative, synthesisable ideas.
- Generate nanomolar hits from scaffold hopping campaigns, as demonstrated in published customer case studies including identification of novel leads against oncology targets.
- Support heterobifunctional molecule design, including degrader and PROTAC-type compounds, using electrostatic complementarity approaches.
- Apply searches focused on sp3-rich and spirocyclic fragments to achieve compound designs with improved physicochemical properties.
Scientific Applications and Research Areas
- Small molecule drug discovery across a broad range of therapeutic targets, including oncology and infectious disease.
- Agrochemical research, supported by a dedicated Spark Agrochemical Database based on PubChem agrochemical classifications.
- Fragment-based drug design and free energy perturbation (FEP) studies, including work on SARS-CoV-2 Mpro cysteine protease inhibitors and METTL3 inhibitors.
- Integration with absolute binding free energy calculations to accurately rank scaffold hopping candidates.
- Active learning FEP workflows to prioritise the most promising molecules for synthesis and testing.
Integration and Deployment
- Spark functionality is available within Cresset's broader CADD platform, Flare™, including as part of the Flare V9 release which introduced Spark bioisostere replacement directly within the Flare environment.
- KNIME integration is supported through Cresset KNIME nodes (version 3.0.0 and above), enabling Spark to be used within automated and customisable computational workflows.
- Fragment databases used by Spark are regularly updated, with new collections released to support evolving research needs including agrochemical applications.
Spark is backed by an extensive library of scientific resources including articles, case studies, whitepapers, and posters, reflecting Cresset's commitment to combining rigorous science with AI-enriched molecular design tools for the life sciences and agrochemical industries.


