The Computational Drug Discovery and Design Group (COMP3D)

The core research topics of our team include

• Target prediction: What are the likely biomacromolecular targets and anti-targets of small molecules?
• Xenobiotic metabolism prediction: How are molecules degraded in living organisms?
• Toxicity prediction: How can we design safe molecules?
• Assay interference prediction: What compounds may trigger false responses in biological assays and have hence the potential to mislead research?
• Conformer ensemble generation: How can we predict the protein-bound conformation of small molecules?
• Natural products research: How can computational methods guide natural products-based drug discovery?

Several of the in silico tools developed in our research group are accessible via NERDD, a secure public web service.

Together with many on-site, domestic and international partners, we also run a large number of projects in which we employ ligand-based and structure-based in silico methods to identify, design and optimise small-molecule modulators of macromolecules that are particularly challenging to target.

We maintain large virtual compound collections of millions of small molecules (including also many natural products) that are readily purchasable or can be sourced by our partners. Using methods such as machine learning, docking, pharmacophore modeling and many others, we identify the most promising compounds in silico, acquire them, and submit them to one of our partner labs for experimental testing. It is always an exciting experience for us to receive testing results for our predicted molecules. These results are then fed back into the model development cycle.

Further information on our research activities can be found here:

• Development of computational methods for drug discovery and molecular design
• Application of computational methods in drug discovery and molecular design