Chemical feature-based pharmacophore

Another retrospective analysis of already known H DAC inhibitors was carried out by You et al. [68]. They generated a 3D chemical-feature-based pharmacophore model and compared the ligand-based model with the structural-functional requirements for the binding of the HDAC inhibitors. Using this model, the interactions between the benzamide MS-275 and HDAC were explored. The result showed that the type and spatial location of chemical features encoded in the pharmacophore are in full agreement with the enzyme-inhibitor interaction pattern identified from molecular docking. However, also in this study no experimental validation of the modeling results was provided. 

Chemical Feature-based Pharmacophores Used by LigandScout... 

E. M. Krovat, T. Langer. Non-peptide angiotensin II receptor antagonists chemical feature based pharmacophore identification. /. Med. Chem., 46, 716-726, 2003. 

Langer, T., Krovat, E. M. Chemical feature-based pharmacophores and virtual... 

Compounds and their conformational models were imported to Catalyst and subjected to the HypoGen routine to build chemical feature-based pharmacophore models using hydrogen bond acceptor lipid (HBA), hydrogen bond donor (HBD), positive ionizable (PI), ring aromatic (RA) and hydrophobic ... 

Langer, T., Krovat, E.-M. Chemical feature-based pharmacophores and virtual hbrary screening for discovery of new leads. Curr. Opin. Drug Discov. Dev. 2003, 6, 370-376. 

Catalyst [67] was launched 1992 by BioCAD (now Accelrys) as a tool for automated pharmacophore pattern recognition in a collection of compounds based on chemical features correlated with three-dimensional structure and biological activity data. 

Computer-assisted molecular design based on three-dimensional disposition of chemical features defining a pharmacophore bioactivities of hypothetical structures predicted based on their fit to models derived from known compounds. Silicon Graphics. 

Some hits also revealed sufficient selectivity of type 1 inhibition versus the type 2 isoform, which is advantageous for the side-effect profile of these compounds. Comparison of the model for llp-HSDl inhibitors with the X-ray crystal structure (which was published shortly after model generation and VS) showed good correlation of the chemical features responsible for ligand binding. In another study, a combination of common feature-based qualitative and quantitative models was used as 3D pharmacophore search query to successfully detect novel endothelin-A antagonistic lead structures. 

The pharmacophore concept is a successful and well-known approach - both ligand- and structure-based - for drug design as well as for VS. Several methods for describing pharmacophores have been established, showing significant differences and capabilities in the way in which they describe chemical features as... 

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