Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Improving structure-based virtual screening by multivariate analysis of scoring data
Uppsala universitet, Avdelningen för organisk farmaceutisk kemi.
Stockholm University, Sweden.
Show others and affiliations
2003 (English)In: Journal of Medicinal Chemistry, ISSN 0022-2623, E-ISSN 1520-4804, Vol. 46, no 26, p. 5781-5789Article in journal (Refereed) Published
Abstract [en]

hree different multivariate statistical methods, PLS discriminant analysis, rule-based methods, and Bayesian classification, have been applied to multidimensional scoring data from four different target proteins: estrogen receptor alpha (ERalpha), matrix metalloprotease 3 (MMP3), factor Xa (fXa), and acetylcholine esterase (AChE). The purpose was to build classifiers able to discriminate between active and inactive compounds, given a structure-based virtual screen. Seven different scoring functions were used to generate the scoring matrices. The classifiers were compared to classical consensus scoring and single scoring functions. The classifiers show a superior performance, with rule-based methods being most effective. The precision of correctly predicting an active compound is about 90% for three of the targets and about 25% for acetylcholine esterase. On the basis of these results, a new two-stage approach is suggested for structure-based virtual screening where limited activity information is available.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2003. Vol. 46, no 26, p. 5781-5789
National Category
Computer and Information Sciences Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
URN: urn:nbn:se:kth:diva-221507DOI: 10.1021/jm030896tISI: 000187243700024PubMedID: 14667231Scopus ID: 2-s2.0-0346996357OAI: oai:DiVA.org:kth-221507DiVA, id: diva2:1175285
Note

QC 20180119

Available from: 2008-10-10 Created: 2018-01-17 Last updated: 2018-01-19Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMedScopus

Search in DiVA

By author/editor
Boström, Henrik
In the same journal
Journal of Medicinal Chemistry
Computer and Information SciencesMedical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 30 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf