CSD-Discovery

• Perform protein-ligand docking experiments and virtual screening using GOLD
  

• Validate your receptor-bound ligand geometry using the same CSD routines in place at the Protein Data Bank
• Drive the design of your ligands by knowledge driven prediction of their geometry
• Generate conformers derived directly from all the latest validated experimental data from the CSD

• Analyse, predict and understand protein and ligand interactions using Full Interaction Maps and Superstar

• Utilise our knowledge based virtual screening workflow to find new hits using protein-ligand docking or ligand-based approaches 

• Interrogate the CSD and the PDB for common interaction patterns using CSD-CrossMiner

This year we’ve focussed on improving programmatic access to CSD-CrossMiner through our CSD Python API. The new release allows users to automate pharmacophoric searches in their own workflow using these methods. We’ve added a simple but much requested feature in the latest version, to be able to filter down results to remove classes of hits. It’s now possible to express ‘non-3D’ filters on substructures in hit results, so users can restrict hits to remove or only include compounds that contain a particular substructure.

2018 also saw delivery of new CSD Python API methodologies for non-sequence-based cavity searching. The CSD Python API now contains 3 different approaches for cavity & pocket searching in proteins which allow a trade-off between very high speed and very high accuracy.

• Identify fragment binding sites on an apo protein

• Ultrafast binding site comparison methodology