New features that improve the pharmacophore tools from Accelrys

Area of Science:

• Computational chemistry and cheminformatics.
• Drug discovery and medicinal chemistry.
• Molecular modeling and simulation.

Background:

• Pharmacophore modeling is a crucial early step in drug discovery, aiding in understanding receptor-ligand interactions.
• Accelrys' pharmacophore tools have a proven track record in various drug discovery projects, including lead generation and database mining.

Purpose of the Study:

• To provide a comprehensive review of pharmacophore tools developed at Accelrys.
• To highlight both established ligand-based algorithms and novel structure-based design approaches.

Main Methods:

• Review of ligand-based pharmacophore algorithms: HipHop and HypoGen.
• Discussion of extensions: HipHopRefine and HypoGenRefine.
• Introduction of new structure-based pharmacophore derivation methods from receptor and complex data.

Main Results:

• Established ligand-based tools (HipHop, HypoGen) are well-validated and widely used.
• New structure-based tools offer novel capabilities for pharmacophore generation.
• The reviewed tools support diverse drug discovery applications.

Conclusions:

• Accelrys offers a robust suite of pharmacophore modeling tools.
• Both ligand-based and structure-based approaches are essential for modern drug discovery.
• These tools facilitate lead generation, optimization, and database mining.