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Literature DB >> 15154787

Comparison of fingerprint-based methods for virtual screening using multiple bioactive reference structures.

Jérôme Hert¹, Peter Willett, David J Wilton, Pierre Acklin, Kamal Azzaoui, Edgar Jacoby, Ansgar Schuffenhauer.

Abstract

Fingerprint-based similarity searching is widely used for virtual screening when only a single bioactive reference structure is available. This paper reviews three distinct ways of carrying out such searches when multiple bioactive reference structures are available: merging the individual fingerprints into a single combined fingerprint; applying data fusion to the similarity rankings resulting from individual similarity searches; and approximations to substructural analysis. Extended searches on the MDL Drug Data Report database suggest that fusing similarity scores is the most effective general approach, with the best individual results coming from the binary kernel discrimination technique.

Mesh：
Molecular Structure

Year: 2004 PMID： 15154787 DOI： 10.1021/ci034231b

Source DB: PubMed Journal: J Chem Inf Comput Sci ISSN： 0095-2338

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Cited

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Comparison of fingerprint-based methods for virtual screening using multiple bioactive reference structures.

1. Virtual target screening: validation using kinase inhibitors.

2. A CROC stronger than ROC: measuring, visualizing and optimizing early retrieval.

Review 3. Evaluation of machine-learning methods for ligand-based virtual screening.

4. Feature-map vectors: a new class of informative descriptors for computational drug discovery.

Review 5. Cheminformatics analysis and learning in a data pipelining environment.

6. Virtual screening applications: a study of ligand-based methods and different structure representations in four different scenarios.

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9. Molecular Scaffold Hopping via Holistic Molecular Representation.

10. Estimation of the applicability domain of kernel-based machine learning models for virtual screening.