CHEESE Electrostatics

Fast Partial Charges | DFT Quality | Compute in 3 seconds

ESP and RESP Charges
DFT Quality

  • Trained on 100k ESP surfaces

  • ESP and RESP (restrained) charges fitted to Connolly surface

  • Quantum Functional ωB97X-D/def2-svp

  • 95-98% Correlation with DFT

  • Validated on OOD scaffold-split (molecules less than 0.3 Morgan Tanimoto to training set)

  • 3s for molecules taking 3hours with DFT

A Revolution in Speed
3D Shape and Electrostatic
CHEESE Embeddings

  • Billion Scale Chemical Spaces

  • 3D Shape | Electrostatics | Activity Screening

  • Saves Years of Time in Virtual Screening

  • Enamine, ZINC, 5+ DBs Coming Soon

  • Screening based on 3D Shape and Electrostatics

  • Similarity calculated based on overlap integral of sampled conformers

  • Isometric Embeddings induced by AI

  • Chemical Space is a Vector Space

  • Versatility of CHEESE Embeddings allows their usage across all our products

  • High-Dimensional Euclidean Vectors Allow Efficient Clustering of Billion-Scale Chemical Spaces

  • Square root time complexity & GPU compatibility

On-Prem

100% Privacy | Behind Your Firewall | Integrate with proprietary data

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    CHEESE Electrostatics On-Prem can be installed privately in your company

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    Seamless integration with your datasets and with other tools in CHEESE Platform

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    Company-wide license: Fixed price, No limits on the number of users

Services

Fast Partial Charges Computation

With our help navigating large chemical spaces will be a breeze. Do you want to allow your chemists access their vastness and perform quick screens in a single click?

Large Scale Clustering

Chemical Spaces need organization and structure. In such a large scale it wasn't possible before CHEESE.

Database subset selection

To proceed with virtual screening you need to select a database subset to work with. What about using fine-grained 3D shape or electrostatic similarity instead of  a rough LogP threshold?

Collaboration with Deep MedChem has significantly streamlined the implementation of AI/ML technologies for processing chemoinformatics data in our drug discovery processes. Through a series of open consultations, the members of Deep MedChem quickly and effectively understood our needs. As a result of this collaboration, we now possess several proprietary models that provide us with significant competitive advantage over other solutions.
Jan Skácel
Research Group Lead, IOCB Prague
CHEESE Modeller has been a game-changer for our drug discovery projects.
The tool accurately predicted docking scores in our virtual screening saving us 200 days of computation time, while achieving unprecedented hit rate. Its simplicity and ease of use set it apart from competitors. Additionally, their customer support is outstanding, always providing prompt and effective assistance including updates in their product. Collaborating with Deep MedChem has boosted our research capabilities and competitive advantage.
Chief Scientific Officer
A San Francisco Bay Area Biotech Company

Contact us

We look forward to helping you make your project a success!

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