Virtual target screening: Validation using kinase inhibitors

Daniel N. Santiago, Yuri Pevzner, Ashley A. Durand, Minhphuong Tran, Rachel R. Scheerer, Kenyon Daniel, Shen Shu Sung, H. Lee Woodcock, Wayne C. Guida, Wesley H. Brooks

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Computational methods involving virtual screening could potentially be employed to discover new biomolecular targets for an individual molecule of interest (MOI). However, existing scoring functions may not accurately differentiate proteins to which the MOI binds from a larger set of macromolecules in a protein structural database. An MOI will most likely have varying degrees of predicted binding affinities to many protein targets. However, correctly interpreting a docking score as a hit for the MOI docked to any individual protein can be problematic. In our method, which we term "Virtual Target Screening (VTS)", a set of small drug-like molecules are docked against each structure in the protein library to produce benchmark statistics. This calibration provides a reference for each protein so that hits can be identified for an MOI. VTS can then be used as tool for: drug repositioning (repurposing), specificity and toxicity testing, identifying potential metabolites, probing protein structures for allosteric sites, and testing focused libraries (collection of MOIs with similar chemotypes) for selectivity. To validate our VTS method, twenty kinase inhibitors were docked to a collection of calibrated protein structures. Here, we report our results where VTS predicted protein kinases as hits in preference to other proteins in our database. Concurrently, a graphical interface for VTS was developed.

Original languageEnglish (US)
Pages (from-to)2192-2203
Number of pages12
JournalJournal of Chemical Information and Modeling
Volume52
Issue number8
DOIs
StatePublished - Aug 27 2012

Fingerprint

Screening
Phosphotransferases
Proteins
Molecules
drug
statistics
Testing
Metabolites
Computational methods
Macromolecules
Pharmaceutical Preparations
Protein Kinases
Toxicity
Statistics
Calibration

All Science Journal Classification (ASJC) codes

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

Cite this

Santiago, D. N., Pevzner, Y., Durand, A. A., Tran, M., Scheerer, R. R., Daniel, K., ... Brooks, W. H. (2012). Virtual target screening: Validation using kinase inhibitors. Journal of Chemical Information and Modeling, 52(8), 2192-2203. https://doi.org/10.1021/ci300073m
Santiago, Daniel N. ; Pevzner, Yuri ; Durand, Ashley A. ; Tran, Minhphuong ; Scheerer, Rachel R. ; Daniel, Kenyon ; Sung, Shen Shu ; Lee Woodcock, H. ; Guida, Wayne C. ; Brooks, Wesley H. / Virtual target screening : Validation using kinase inhibitors. In: Journal of Chemical Information and Modeling. 2012 ; Vol. 52, No. 8. pp. 2192-2203.
@article{55fbc80359434fa1b083a0e60f9e5010,
title = "Virtual target screening: Validation using kinase inhibitors",
abstract = "Computational methods involving virtual screening could potentially be employed to discover new biomolecular targets for an individual molecule of interest (MOI). However, existing scoring functions may not accurately differentiate proteins to which the MOI binds from a larger set of macromolecules in a protein structural database. An MOI will most likely have varying degrees of predicted binding affinities to many protein targets. However, correctly interpreting a docking score as a hit for the MOI docked to any individual protein can be problematic. In our method, which we term {"}Virtual Target Screening (VTS){"}, a set of small drug-like molecules are docked against each structure in the protein library to produce benchmark statistics. This calibration provides a reference for each protein so that hits can be identified for an MOI. VTS can then be used as tool for: drug repositioning (repurposing), specificity and toxicity testing, identifying potential metabolites, probing protein structures for allosteric sites, and testing focused libraries (collection of MOIs with similar chemotypes) for selectivity. To validate our VTS method, twenty kinase inhibitors were docked to a collection of calibrated protein structures. Here, we report our results where VTS predicted protein kinases as hits in preference to other proteins in our database. Concurrently, a graphical interface for VTS was developed.",
author = "Santiago, {Daniel N.} and Yuri Pevzner and Durand, {Ashley A.} and Minhphuong Tran and Scheerer, {Rachel R.} and Kenyon Daniel and Sung, {Shen Shu} and {Lee Woodcock}, H. and Guida, {Wayne C.} and Brooks, {Wesley H.}",
year = "2012",
month = "8",
day = "27",
doi = "10.1021/ci300073m",
language = "English (US)",
volume = "52",
pages = "2192--2203",
journal = "Journal of Chemical Information and Modeling",
issn = "1549-9596",
publisher = "American Chemical Society",
number = "8",

}

Santiago, DN, Pevzner, Y, Durand, AA, Tran, M, Scheerer, RR, Daniel, K, Sung, SS, Lee Woodcock, H, Guida, WC & Brooks, WH 2012, 'Virtual target screening: Validation using kinase inhibitors', Journal of Chemical Information and Modeling, vol. 52, no. 8, pp. 2192-2203. https://doi.org/10.1021/ci300073m

Virtual target screening : Validation using kinase inhibitors. / Santiago, Daniel N.; Pevzner, Yuri; Durand, Ashley A.; Tran, Minhphuong; Scheerer, Rachel R.; Daniel, Kenyon; Sung, Shen Shu; Lee Woodcock, H.; Guida, Wayne C.; Brooks, Wesley H.

In: Journal of Chemical Information and Modeling, Vol. 52, No. 8, 27.08.2012, p. 2192-2203.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Virtual target screening

T2 - Validation using kinase inhibitors

AU - Santiago, Daniel N.

AU - Pevzner, Yuri

AU - Durand, Ashley A.

AU - Tran, Minhphuong

AU - Scheerer, Rachel R.

AU - Daniel, Kenyon

AU - Sung, Shen Shu

AU - Lee Woodcock, H.

AU - Guida, Wayne C.

AU - Brooks, Wesley H.

PY - 2012/8/27

Y1 - 2012/8/27

N2 - Computational methods involving virtual screening could potentially be employed to discover new biomolecular targets for an individual molecule of interest (MOI). However, existing scoring functions may not accurately differentiate proteins to which the MOI binds from a larger set of macromolecules in a protein structural database. An MOI will most likely have varying degrees of predicted binding affinities to many protein targets. However, correctly interpreting a docking score as a hit for the MOI docked to any individual protein can be problematic. In our method, which we term "Virtual Target Screening (VTS)", a set of small drug-like molecules are docked against each structure in the protein library to produce benchmark statistics. This calibration provides a reference for each protein so that hits can be identified for an MOI. VTS can then be used as tool for: drug repositioning (repurposing), specificity and toxicity testing, identifying potential metabolites, probing protein structures for allosteric sites, and testing focused libraries (collection of MOIs with similar chemotypes) for selectivity. To validate our VTS method, twenty kinase inhibitors were docked to a collection of calibrated protein structures. Here, we report our results where VTS predicted protein kinases as hits in preference to other proteins in our database. Concurrently, a graphical interface for VTS was developed.

AB - Computational methods involving virtual screening could potentially be employed to discover new biomolecular targets for an individual molecule of interest (MOI). However, existing scoring functions may not accurately differentiate proteins to which the MOI binds from a larger set of macromolecules in a protein structural database. An MOI will most likely have varying degrees of predicted binding affinities to many protein targets. However, correctly interpreting a docking score as a hit for the MOI docked to any individual protein can be problematic. In our method, which we term "Virtual Target Screening (VTS)", a set of small drug-like molecules are docked against each structure in the protein library to produce benchmark statistics. This calibration provides a reference for each protein so that hits can be identified for an MOI. VTS can then be used as tool for: drug repositioning (repurposing), specificity and toxicity testing, identifying potential metabolites, probing protein structures for allosteric sites, and testing focused libraries (collection of MOIs with similar chemotypes) for selectivity. To validate our VTS method, twenty kinase inhibitors were docked to a collection of calibrated protein structures. Here, we report our results where VTS predicted protein kinases as hits in preference to other proteins in our database. Concurrently, a graphical interface for VTS was developed.

UR - http://www.scopus.com/inward/record.url?scp=84865453273&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84865453273&partnerID=8YFLogxK

U2 - 10.1021/ci300073m

DO - 10.1021/ci300073m

M3 - Article

C2 - 22747098

AN - SCOPUS:84865453273

VL - 52

SP - 2192

EP - 2203

JO - Journal of Chemical Information and Modeling

JF - Journal of Chemical Information and Modeling

SN - 1549-9596

IS - 8

ER -

Santiago DN, Pevzner Y, Durand AA, Tran M, Scheerer RR, Daniel K et al. Virtual target screening: Validation using kinase inhibitors. Journal of Chemical Information and Modeling. 2012 Aug 27;52(8):2192-2203. https://doi.org/10.1021/ci300073m