Invited Speaker

Structure Based Pharmacophore Design in Computer Aided Drug Discovery
R. Raghu
India

Computer-aided drug design techniques such as ligand based pharmacophore modeling and structure-based protein ligand docking have become an integral part of drug discovery. Research organizations in both industry and academia use these techniques to aid in the efficient discovery and design of active molecules. Large compound databases can be screened computationally to reduce the number of compounds for bioassay screens, thereby saving time and resources.
Ligand-based technologies, such as 2D fingerprint similarity searching, shape-based screening, and 3D-pharmacophore modeling are traditionally recognized as fast methods for screening large compound databases. Structure-based approaches, on the other hand, are generally more computationally expensive but can lead to structural insights and have been shown to yield more diverse actives.

It is thus of particular relevance to drug discovery campaigns involving targets that are difficult to crystallize, such as ion channels, transporters, or G protein-coupled receptors (GPCRs).

Screening a 3D database against a pharmacophore hypothesis is generally more computationally efficient than structure-based docking, which involves many energy evaluations as part of the conformational searching and scoring process. Recently, methods have emerged that attempt to capitalize on the speed of pharmacophore screening coupled with structure-based information by developing pharmacophore hypotheses derived from protein-ligand complexes.These methods show promise and have been used to discover novel leads.

We describe a novel method to develop energetically optimized, structure-based pharmacophores for use in rapid in silico screening. We derive energy-optimized pharmacophore hypotheses for 30 pharmaceutically relevant crystal structures and screen a database to assess the enrichment of active compounds. The method is compared to three other approaches: (1) pharmacophore hypotheses derived from a systematic assessment of receptor-ligand contacts, (2) Glide SP docking, and (3) 2D ligand fingerprint similarity. The method developed here shows better enrichments than the other three methods and yields a greater diversity of actives than the contact-based pharmacophores or the 2D ligand similarity. Docking produces the most cases (28/30) with enrichments greater than 10.0 in the top 1% of the database and on average produces the greatest diversity of active molecules. The combination of energy terms from a structure-based analysis with the speed of a ligand-based pharmacophore search results in a method that leverages the strengths of both approaches to produce high enrichments with a good diversity of active molecules.