Pharmacophore modeling and three-dimensional database searching for drug design using catalyst.

By Y. Kurogi, O. Güner. Current Medicinal Chemistry, 2001

317 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/5896dc8e406abefa441758c33c62aa48408d27ed

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Citations in the corpus

In silico pharmacology for drug discovery: applications to targets and beyond (2007, methodology): “…stories in computer-aided design, which covers a large number of proteins that have been targets for all manner of in silico methods (Kubinyi, 2006), as well as other reviews that have dealt with the successes of individual methods (Fujita, 1997; Kurogi and Guner, 2001a; Guner et al ., 2004).”
Recent advances in ligand-based drug design: relevance and utility of the conformationally sampled pharmacophore approach. (2011, background): “There are several review articles available that elaborately discuss various techniques of 3D QSAR modeling [2,3,9,19, 28 , 34 ,70,71,74-76].”
Effects of multiple conformers per compound upon 3-D similarity search and bioassay data analysis (2012, methodology): “It was found that, whereas the pharmacophore-based screening using CATALYST [34,35] was able to identify the greatest number of known actives even with very small conformer ensembles, the shape-based screening using ROCS showed an increased accuracy with larger conformer models.”
Virtual ligand screening: strategies, perspectives and limitations (2006, unknown): “UNITY (UNITY Chemical Information Software, version 4.1, Tripos) and CATALYST [89] are prototypes of such database engines supporting this screening step.”
Computational Methods in Drug Discovery (2014, methodology): “Finally, HypoGen performs an optimization routine that attempts to improve the predictive power of the pharmacophore by making adjustments and scoring the accuracy in predicting the specific experimental activities (Güner, 2000; Kurogi and Guner, 2001).”