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Literature DB >> 12197666

Effectiveness of graph-based and fingerprint-based similarity measures for virtual screening of 2D chemical structure databases.

Abstract

This paper reports an evaluation of both graph-based and fingerprint-based measures of structural similarity, when used for virtual screening of sets of 2D molecules drawn from the MDDR and ID Alert databases. The graph-based measures employ a new maximum common edge subgraph isomorphism algorithm, called RASCAL, with several similarity coefficients described previously for quantifying the similarity between pairs of graphs. The effectiveness of these graph-based searches is compared with that resulting from similarity searches using BCI, Daylight and Unity 2D fingerprints. Our results suggest that graph-based approaches provide an effective complement to existing fingerprint-based approaches to virtual screening.

Mesh：

Year: 2002 PMID： 12197666 DOI： 10.1023/a:1016387816342

Source DB: PubMed Journal: J Comput Aided Mol Des ISSN： 0920-654X Impact factor: 3.686

4 in total

1. Combinatorial preferences affect molecular similarity/diversity calculations using binary fingerprints and Tanimoto coefficients

Authors:
Journal: J Chem Inf Comput Sci Date: 2000-01

Review 2. Effectiveness of retrieval in similarity searches of chemical databases: a review of performance measures.

Authors: S J Edgar; J D Holliday; P Willett
Journal: J Mol Graph Model Date: 2000 Aug-Oct Impact factor: 2.518

3. Heuristics for similarity searching of chemical graphs using a maximum common edge subgraph algorithm.

Authors: John W Raymond; Eleanor J Gardiner; Peter Willett
Journal: J Chem Inf Comput Sci Date: 2002 Mar-Apr

4. Grouping of coefficients for the calculation of inter-molecular similarity and dissimilarity using 2D fragment bit-strings.

Authors: J D Holliday; C-Y Hu; P Willett
Journal: Comb Chem High Throughput Screen Date: 2002-03 Impact factor: 1.339

4 in total

17 in total

Effectiveness of graph-based and fingerprint-based similarity measures for virtual screening of 2D chemical structure databases.

1. Combinatorial preferences affect molecular similarity/diversity calculations using binary fingerprints and Tanimoto coefficients

Review 2. Effectiveness of retrieval in similarity searches of chemical databases: a review of performance measures.

3. Heuristics for similarity searching of chemical graphs using a maximum common edge subgraph algorithm.

4. Grouping of coefficients for the calculation of inter-molecular similarity and dissimilarity using 2D fragment bit-strings.

1. Maximum common subgraph isomorphism algorithms for the matching of chemical structures.

2. Design of chemical space networks using a Tanimoto similarity variant based upon maximum common substructures.

3. Measuring CAMD technique performance: a virtual screening case study in the design of validation experiments.

4. Maximum common substructure-based Tversky index: an asymmetric hybrid similarity measure.

Review 5. Machine learning in chemoinformatics and drug discovery.

6. Optimal assignment methods for ligand-based virtual screening.

7. Small Molecule Subgraph Detector (SMSD) toolkit.

8. Semantic similarity for automatic classification of chemical compounds.

9. Influence relevance voting: an accurate and interpretable virtual high throughput screening method.

Review 10. Five Years of the KNIME Vernalis Cheminformatics Community Contribution.