2003
DOI: 10.1007/s00894-002-0110-0
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The Compressed Feature Matrix—a novel descriptor for adaptive similarity search

Abstract: The Compressed Feature Matrix (CFM) is a new molecular descriptor for adaptive similarity searching. Depending on the requirements, it is based on a distance or geometry matrix. Thus, the CFM permits topological and three-dimensional comparisons of molecules. In contrast to the common distance matrix, the CFM is based on features instead of atoms. Each kind of these features may be weighted separately, depending on its (estimated) contribution to the biological effect of the molecule. In this work, we show tha… Show more

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Cited by 7 publications
(12 citation statements)
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“…In section 4 we experimentally evaluate our approach and compare it to classical descriptor-based QSAR models. Our experiments include prediction of HIA [25 -31], Blood-Brain-Barrier (BBB) penetration [32,33], bioavailability [34], and grouping inhibitors into four different classes [35]. We show that by using our approach we achieve a generalization performance comparable to a descriptor-based model, which includes only descriptors that are a-priori known to be relevant for the problem.…”
Section: Full Papersmentioning
confidence: 99%
See 1 more Smart Citation
“…In section 4 we experimentally evaluate our approach and compare it to classical descriptor-based QSAR models. Our experiments include prediction of HIA [25 -31], Blood-Brain-Barrier (BBB) penetration [32,33], bioavailability [34], and grouping inhibitors into four different classes [35]. We show that by using our approach we achieve a generalization performance comparable to a descriptor-based model, which includes only descriptors that are a-priori known to be relevant for the problem.…”
Section: Full Papersmentioning
confidence: 99%
“…Finally, we investigated a set of 296 molecules published in [35] as a test dataset for the SOL project 4 . The dataset consists of 4 different classes of inhibitors: thrombin inhibitors (75 molecules), serotonin inhibitors of the 5HT2 class (75 molecules), monoamine oxidase inhibitors (71 molecules) and 5-hydroxytryptamine oxidase (75 molecules).…”
Section: Datasetsmentioning
confidence: 99%
“…1,[3][4][5][6][7][8][9][10][11][12][13] The ability to move to new scaffolds can be of interest in situations where the natural ligands or substrates of protein targets are known but synthetic inhibitors are not and structural information about the target protein is not available. An ideal similarity search method could use endogenous ligand structures to discover drug-like mimetics in large databases in an automated manner.…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, it is important that the users-especially experts in a certain topic-can define terms in this topic in the adapted domain with the topic-specific relevant features that they want as search criteria. The use of relevant features as criteria for similarity searches has been, up to now, a typical application in databases [28][29][30][31][32][33][34][35][36][37][38]. This restriction, however, is not necessary.…”
Section: User-defined Global Similarity Search Of Informationmentioning
confidence: 99%