RAPID: randomized pharmacophore identification for drug design
By P. Finn, Lydia E. Kavraki, Jean-Claude Latombe, Rajeev Motwani, Christian R. Shelton, Suresh Venkatasubramanian, A. Yao. 1997
This paper describes a randomized approach for finding invariants in a set of flexible ligands (drug molecules) that underlies an integrated software system called RAPID currently under development. An invariant is a collection of features embedded in 3 which is present in one or more of the possible low-energy conformations of each ligand. Such invariants of chemically distinct molecules are useful for computational chemists since they may represent candidate pharmacophores. A pharmacophore contains the parts of the ligand that are primarily responsible for its interaction and binding with a specific receptor. It is regarded as an inverse image of a receptor and is used as a template for building more effective pharmaceutical drugs. The identification of pharmacophores is crucial in drug design since the structure of the targeted receptor is frequently unknown, but a number of molecules that interact with the receptor have been discovered by experiments. It is expected that our techniques and the results produced by our system will prove useful in other applications such as molecular database screening and comparative molecular field analysis.
Subfields: Computational Chemistry & Drug Discovery
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In Computational Chemistry & Drug Discovery
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Citations in the corpus
- Principles of docking: An overview of search algorithms and a guide to scoring functions (2002, methodology): “To extend the algorithm to multiple structures, Finn et al. 178 iteratively take all solutions of a certain pairwise problem.”
- PharmaGist: a webserver for ligand-based pharmacophore detection (2008, methodology): “Examples for such methods include RAPID ( 8 ), MPHIL (9) and the commercial programs DISCO (10), Phase (11) of Schrodinger and HipHop and HypoGen, which are part of the Catalyst software package of Accelrys (12–16).”
- Navigation Strategies for Exploring Indoor Environments (2002, methodology): “The matching algorithm implemented in our system is based on a technique previously used to discover and align substructures shared by 3D molecular structures (Finn et al. 1998).”