Our CADD scientists leverage their extensive expertise and our cutting-edge computing infrastructure to shed light on the molecular interactions between ligands and proteins. We have an excellent track record of successfully applying bespoke SBDD techniques across target classes and therapeutic areas throughout the drug discovery process.

Target validation

We harness proven algorithms to assess the ligandability of biological targets by predicting and ranking binding sites (cryptic, transient, allosteric, etc.) likely to be involved in eliciting the desired biological response. We apply advanced molecular dynamics simulations to rationalise postulated mechanisms of actions.

Hit generation

We perform homology modelling studies using commercial software along with Artificial Intelligence algorithms to predict the 3D structures of yet uncharacterised proteins. We use these models, as well as structures deposited in the Protein Data Bank (or generated as part of our integrated drug discovery offering) across a wide range of SBDD activities including the virtual screening of large compounds collections.

Lead identification

We use state-of-the-art docking software to model the interactions of proteins with small molecules covering a range of modalities such as PROTACs , Fragments, peptides, macrocycles and  covalent drugs. This empowers our drug hunters to efficiently optimise the potency and selectivity of in vitro hits.

Lead optimisation

Once Lead series are identified, our drug hunters carry out fine structural tuning to generate a suitable clinical candidate. These efforts are greatly facilitated by our CADD scientist expertise in applying advanced modelling techniques such as Free Energy Perturbation and water mapping.

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