Extracting useful information from the vast amounts of data generated by genome projects requires a multitude of bioinformatics applications and the knowledge to apply them. In the case of drug design, multiple sequence alignments of target family members reveal the conservation of binding site(s) and suggest a means to design molecules with specificity. The localisation of SNPs can have a direct effect on the final protein 3D structure and hence, lead directly into pharmacogenomics and the future development of 'personalised medicines'.

Chemical information management and data analysis are encompassed within the term chemoinformatics. The direct relationship between biological activity and chemical structure of a compound or QSAR is still an immensely powerful method for lead/drug design.

ADMET property profiling is of crucial importance going from lead to drug and should be taken into account in early hit selection.

Molecular Modelling

  • Homology modelling
  • Protein electrostatics
  • Site analysis
  • GPCR modelling
  • Molecular Dynamics


  • Sequence analysis
  • Database searching
  • Genome analysis (SNPs)
  • Pairwise and multiple alignments
  • Data mining
  • Pattern searching
  • Clustering


  • Database filtering
  • Target focussed screening
  • Property calculations
  • QSAR
  • ADMET profiling

Drug Design

  • Pharmacophore mapping
  • Ligand docking
  • Virtual screening
  • Fragment screening
  • De novo design
  • Library design