Hit Generation
Predictive models used for screening of fragments, de-novo designed compounds and our large
privileged compound collection to identify series of hits for all classes of targets.
Mapping of interactions to potency
On-target screening
Pharmacophore/QSAR/Docking models
Screening of large virtual databases
Identification of hits and compound design
Hit quality assessment through preliminary filters
Iterative design to optimize hits into leads
Fragment screening and de-novo design




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Key molecular interactions and their contribution to SAR
On-target screening using molecular docking, pharmacophore, molecular field approaches
Screening of our large privileged databases covering a wide chemical space
Enabling FBDD campaigns and evolution of fragments into hits
de novo designs of hits based on key interactions and novelty
Fast follow-ons with focus on differentiation
Hit quality assessment through ML models
Iterative designs for Hit -> Lead