Target-specific support vector machine scoring in structure-based virtual screening

Computational validation, in vitro testing in kinases, and effects on lung cancer cell proliferation

Liwei Li, May Khanna, Inha Jo, Fang Wang, Nicole M. Ashpole, Andy Hudmon, Samy Meroueh

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

We assess the performance of our previously reported structure-based support vector machine target-specific scoring function across 41 targets, 40 among them from the Directory of Useful Decoys (DUD). The area under the curve of receiver operating characteristic plots (ROC-AUC) revealed that scoring with SVM-SP resulted in consistently better enrichment over all target families, outperforming Glide and other scoring functions, most notably among kinases. In addition, SVM-SP performance showed little variation among protein classes, exhibited excellent performance in a test case using a homology model, and in some cases showed high enrichment even with few structures used to train a model. We put SVM-SP to the test by virtual screening 1125 compounds against two kinases, EGFR and CaMKII. Among the top 25 EGFR compounds, three compounds (1-3) inhibited kinase activity in vitro with IC50 of 58, 2, and 10 μM. In cell cultures, compounds 1-3 inhibited nonsmall cell lung carcinoma (H1299) cancer cell proliferation with similar IC50 values for compound 3. For CaMKII, one compound inhibited kinase activity in a dose-dependent manner among 20 tested with an IC50 of 48 μM. These results are encouraging given that our in-house library consists of compounds that emerged from virtual screening of other targets with pockets that are different from typical ATP binding sites found in kinases. In light of the importance of kinases in chemical biology, these findings could have implications in future efforts to identify chemical probes of kinases within the human kinome.

Original languageEnglish
Pages (from-to)755-759
Number of pages5
JournalJournal of Chemical Information and Modeling
Volume51
Issue number4
DOIs
StatePublished - Apr 25 2011

Fingerprint

Cell proliferation
proliferation
Support vector machines
Screening
cancer
Phosphotransferases
Adenosinetriphosphate
Testing
Binding sites
Cell culture
performance
Cells
Calcium-Calmodulin-Dependent Protein Kinase Type 2
Proteins
biology
recipient
Values
Adenosine Triphosphate
Binding Sites

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)
  • Computer Science Applications
  • Library and Information Sciences

Cite this

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title = "Target-specific support vector machine scoring in structure-based virtual screening: Computational validation, in vitro testing in kinases, and effects on lung cancer cell proliferation",
abstract = "We assess the performance of our previously reported structure-based support vector machine target-specific scoring function across 41 targets, 40 among them from the Directory of Useful Decoys (DUD). The area under the curve of receiver operating characteristic plots (ROC-AUC) revealed that scoring with SVM-SP resulted in consistently better enrichment over all target families, outperforming Glide and other scoring functions, most notably among kinases. In addition, SVM-SP performance showed little variation among protein classes, exhibited excellent performance in a test case using a homology model, and in some cases showed high enrichment even with few structures used to train a model. We put SVM-SP to the test by virtual screening 1125 compounds against two kinases, EGFR and CaMKII. Among the top 25 EGFR compounds, three compounds (1-3) inhibited kinase activity in vitro with IC50 of 58, 2, and 10 μM. In cell cultures, compounds 1-3 inhibited nonsmall cell lung carcinoma (H1299) cancer cell proliferation with similar IC50 values for compound 3. For CaMKII, one compound inhibited kinase activity in a dose-dependent manner among 20 tested with an IC50 of 48 μM. These results are encouraging given that our in-house library consists of compounds that emerged from virtual screening of other targets with pockets that are different from typical ATP binding sites found in kinases. In light of the importance of kinases in chemical biology, these findings could have implications in future efforts to identify chemical probes of kinases within the human kinome.",
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T2 - Computational validation, in vitro testing in kinases, and effects on lung cancer cell proliferation

AU - Li, Liwei

AU - Khanna, May

AU - Jo, Inha

AU - Wang, Fang

AU - Ashpole, Nicole M.

AU - Hudmon, Andy

AU - Meroueh, Samy

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