Automated Pharmacophore Identification for Large Chemical Data Sets.

By Xin Chen, A. Rusinko, A. Tropsha, S. Stanley Young. 1999

Subfields: Computational Chemistry & Drug Discovery

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Chemistry & Drug Discovery

1. Dina Schneidman-Duhovny
2. Andreas Zell
3. Glaucius Oliva
4. Haim J. Wolfson
5. Ruth Nussinov
6. Adriano Defini Andricopulo
7. Yuval Inbar
8. L. Ferreira

Citations in the corpus

• Molecular Docking and Structure-Based Drug Design Strategies (2015, background): “…[154,155] HypoGen [141] ALADDIN [156] HypoRefine [141] RAPID [157] GASP [142,143] DANTE [158] DiscoTech [143,144] APOLLO [159] GALAHAD [143,145] CLEW [160] LigandScout [146,147] MPHIL [161] MOE [148,149] GAMMA [162] PHASE [150,151] SCAMPI [163] XED [152,153] Apex-3D [164] LigBuilder [165,166]”
• PharmaGist: a webserver for ligand-based pharmacophore detection (2008, methodology): “Among them are SCAMPI (17), GAMMA (18–20), GASP (21,22) and GALAHAD (23,24) of Tripos and the MOGA-based method described in ref.”
• Optimal assignment kernels for attributed molecular graphs (2005, background): “The high relevance of such a pharmacophore mapping for QSAR models is also reported e.g. in (Chen et al., 1999; Oprea et al., 2002).”