Comparison of structure fingerprint and molecular interaction file based methods in explaining biological similarity of small molecules in cell-based screens

Pekka Tiikkainen (Corresponding Author), Antti Poso, Olli Kallioniemi

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)

Abstract

In this work, we calculated the pair wise chemical similarity for a subset of small molecules screened against the NCI60 cancer cell line panel. Four different compound similarity calculation methods were used: Brutus, GRIND, Daylight and UNITY. The chemical similarity scores of each method were related to the biological similarity data set. The same was done also for combinations of methods. In the end, we had an estimate of biological similarity for a given chemical similarity score or combinations thereof. The data from above was used to identify chemical similarity ranges where combining two or more methods (data fusion) led to synergy. The results were also applied in ligand-based virtual screening using the DUD data set. In respect to their ability to enrich biologically similar compound pairs, the ranking of the four methods in descending performance is UNITY, Daylight, Brutus and GRIND. Combining methods resulted always in positive synergy within a restricted range of chemical similarity scores. We observed no negative synergy. We also noted that combining three or four methods had only limited added advantage compared to combining just two. In the virtual screening, using the estimated biological similarity for ranking compounds produced more consistent results than using the methods in isolation.
Original languageEnglish
Pages (from-to)227-239
JournalJournal of Computer-Aided Molecular Design
Volume23
Issue number4
DOIs
Publication statusPublished - 2009
MoE publication typeA1 Journal article-refereed

Fingerprint

Molecular interactions
Dermatoglyphics
molecular interactions
Molecular Structure
files
Molecules
cells
molecules
Screening
interactions
Data fusion
ranking
Ligands
Cells
screening
multisensor fusion
cultured cells
set theory
isolation
cancer

Keywords

  • Ligand-based virtual screening
  • NCI-60
  • Data fusion
  • Chemical similarity

Cite this

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title = "Comparison of structure fingerprint and molecular interaction file based methods in explaining biological similarity of small molecules in cell-based screens",
abstract = "In this work, we calculated the pair wise chemical similarity for a subset of small molecules screened against the NCI60 cancer cell line panel. Four different compound similarity calculation methods were used: Brutus, GRIND, Daylight and UNITY. The chemical similarity scores of each method were related to the biological similarity data set. The same was done also for combinations of methods. In the end, we had an estimate of biological similarity for a given chemical similarity score or combinations thereof. The data from above was used to identify chemical similarity ranges where combining two or more methods (data fusion) led to synergy. The results were also applied in ligand-based virtual screening using the DUD data set. In respect to their ability to enrich biologically similar compound pairs, the ranking of the four methods in descending performance is UNITY, Daylight, Brutus and GRIND. Combining methods resulted always in positive synergy within a restricted range of chemical similarity scores. We observed no negative synergy. We also noted that combining three or four methods had only limited added advantage compared to combining just two. In the virtual screening, using the estimated biological similarity for ranking compounds produced more consistent results than using the methods in isolation.",
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Comparison of structure fingerprint and molecular interaction file based methods in explaining biological similarity of small molecules in cell-based screens. / Tiikkainen, Pekka (Corresponding Author); Poso, Antti; Kallioniemi, Olli.

In: Journal of Computer-Aided Molecular Design, Vol. 23, No. 4, 2009, p. 227-239.

Research output: Contribution to journalArticleScientificpeer-review

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